Anthropic’s $30B Ramp, Mythos Doomsday, OpenClaw Ankled, Iran War Ceasefire, Israel's Influence

How many PRs you think are going to get How many PRs you think are going to get pushed to the core structural internet pushed to the core structural internet pushed to the core structural internet in 100 days? What's the overunder in 100 days? What's the overunder in 100 days? What's the overunder number? Cuz I'll give you a number. number? Cuz I'll give you a number. number? Cuz I'll give you a number. >> You're going to say zero. My my answer >> You're going to say zero. My my answer >> You're going to say zero. My my answer to that is to that is to that is >> I'll say like 10,000. But it's going to >> I'll say like 10,000. But it's going to >> I'll say like 10,000. But it's going to be immediately be immediately be immediately >> if it prevents your browser history from >> if it prevents your browser history from >> if it prevents your browser history from being released to everybody in the being released to everybody in the being released to everybody in the world, Chamath, that may be something world, Chamath, that may be something world, Chamath, that may be something that you're willing to, you know, let that you're willing to, you know, let that you're willing to, you know, let 100 days pass on. 100 days pass on. 100 days pass on. >> I think you got Chimat's attention when >> I think you got Chimat's attention when >> I think you got Chimat's attention when you said browser history. you said browser history. you said browser history. >> What about the dickpicks? >> Chamat is he's going to release them >> Chamat is he's going to release them himself. himself. himself. We'll let your winners ride. >> We open source it to the fans and >> We open source it to the fans and they've just gone crazy with it. Love they've just gone crazy with it. Love they've just gone crazy with it. Love you. >> All right, everybody. Welcome back to >> All right, everybody. Welcome back to the number one podcast in the world. the number one podcast in the world. the number one podcast in the world. David Freeberg is out this week. But in David Freeberg is out this week. But in David Freeberg is out this week. But in his place, the one, the only, his place, the one, the only, his place, the one, the only, our fifth bestie, Brad Gersonner. I our fifth bestie, Brad Gersonner. I our fifth bestie, Brad Gersonner. I mean, why don't you ever give me puts a mean, why don't you ever give me puts a mean, why don't you ever give me puts a little namaste in your payday anymore? little namaste in your payday anymore? little namaste in your payday anymore? You used to be You used to be You used to be >> I'm going to bring back the greatest >> I'm going to bring back the greatest >> I'm going to bring back the greatest moderator, but now it's just kind of You moderator, but now it's just kind of You moderator, but now it's just kind of You know what? These guys beat me up. They know what? These guys beat me up. They know what? These guys beat me up. They beat me up and they just beat the the beat me up and they just beat the the beat me up and they just beat the the joy out of me doing this program. joy out of me doing this program. joy out of me doing this program. >> It's because you're a Roana apologist >> It's because you're a Roana apologist >> It's because you're a Roana apologist now. now. now. >> No, I We'll get into it. Okay. Save it >> No, I We'll get into it. Okay. Save it >> No, I We'll get into it. Okay. Save it for the Roana apologist. just for the Roana apologist. just for the Roana apologist. just because I said like, "Hey, they've because I said like, "Hey, they've because I said like, "Hey, they've stopped maxing and they've stopped maxing and they've stopped maxing and they've started doing like some logical things." started doing like some logical things." started doing like some logical things." Uh, yeah. Okay, here we go. Uh, yeah. Okay, here we go. Uh, yeah. Okay, here we go. >> It's great to be here. Great to be here. >> It's great to be here. Great to be here. >> It's great to be here. Great to be here. >> Good to have you. Good to have you here. >> Good to have you. Good to have you here. >> Good to have you. Good to have you here. And of course, uh, we have David Saxs is And of course, uh, we have David Saxs is And of course, uh, we have David Saxs is back. Everybody wants to hear from David back. Everybody wants to hear from David back. Everybody wants to hear from David Sax. We missed you last week, bestie. Sax. We missed you last week, bestie. Sax. We missed you last week, bestie. >> We didn't beat the joy out of you. We >> We didn't beat the joy out of you. We >> We didn't beat the joy out of you. We just try to beat some of the hot air. just try to beat some of the hot air. just try to beat some of the hot air. Turn Turn Turn >> any any fluff that you can put on the >> any any fluff that you can put on the >> any any fluff that you can put on the show that just involves you talking and show that just involves you talking and show that just involves you talking and saying nothing is saying nothing is saying nothing is >> that's the stuff we got. >> that's the stuff we got. >> that's the stuff we got. >> Turn up. Yeah. Turn up. Okay. Yeah, >> Turn up. Yeah. Turn up. Okay. Yeah, >> Turn up. Yeah. Turn up. Okay. Yeah, we'll cut it right out. Um we'll cut it we'll cut it right out. Um we'll cut it we'll cut it right out. Um we'll cut it out and we'll just put a promo in for out and we'll just put a promo in for out and we'll just put a promo in for the syndicate.com. Thank you. Also with the syndicate.com. Thank you. Also with the syndicate.com. Thank you. Also with us, Jamalet is here. us, Jamalet is here. us, Jamalet is here. >> How's your maxing going since >> How's your maxing going since >> How's your maxing going since last week? Did you have a a a last week? Did you have a a a last week? Did you have a a a maxing full weekend? Did you have a good maxing full weekend? Did you have a good maxing full weekend? Did you have a good full weekend of just smoking cigars in full weekend of just smoking cigars in full weekend of just smoking cigars in the back deck and not ruminating about the back deck and not ruminating about the back deck and not ruminating about all the chaos you've caused in the last all the chaos you've caused in the last all the chaos you've caused in the last 20 years? 20 years? 20 years? >> I think I've done generally more good >> I think I've done generally more good >> I think I've done generally more good >> than than not. >> than than not. >> than than not. >> Oh, you have. But there's been some >> Oh, you have. But there's been some >> Oh, you have. But there's been some chaotic moments. Don't think about it. chaotic moments. Don't think about it. chaotic moments. Don't think about it. >> You can't, bro. You can't have ups >> You can't, bro. You can't have ups >> You can't, bro. You can't have ups without downs, man. It's like, what are without downs, man. It's like, what are without downs, man. It's like, what are you there to do? Just like plate you there to do? Just like plate you there to do? Just like plate everybody and be a loser? Are you there everybody and be a loser? Are you there everybody and be a loser? Are you there to be a winner? Yes, you're in the to be a winner? Yes, you're in the to be a winner? Yes, you're in the arena, but have you stopped going to arena, but have you stopped going to arena, but have you stopped going to therapy after realizing ruminating? therapy after realizing ruminating? therapy after realizing ruminating? >> What's up with this uh sudden interest >> What's up with this uh sudden interest >> What's up with this uh sudden interest in maxing? Are you like the in maxing? Are you like the in maxing? Are you like the clavvicular for maxing? clavvicular for maxing? clavvicular for maxing? >> No, the world finally caught up with me. >> No, the world finally caught up with me. >> No, the world finally caught up with me. That's it. What do you I mean, I've been That's it. What do you I mean, I've been That's it. What do you I mean, I've been maxing this whole time. THEY JUST maxing this whole time. THEY JUST maxing this whole time. THEY JUST DIDN'T HAVE A name for it, guys. DIDN'T HAVE A name for it, guys. DIDN'T HAVE A name for it, guys. >> Wow. Okay. Eli's videos are really good. >> Wow. Okay. Eli's videos are really good. >> Wow. Okay. Eli's videos are really good. I watched two more this week. I watched two more this week. I watched two more this week. What take us through what's so appealing What take us through what's so appealing What take us through what's so appealing about not ruminating, smoking a cigar, about not ruminating, smoking a cigar, about not ruminating, smoking a cigar, and just living your life? and just living your life? and just living your life? >> Because what he says actually works at >> Because what he says actually works at >> Because what he says actually works at every level of society and every sort of every level of society and every sort of every level of society and every sort of thing that you may want to achieve. Even thing that you may want to achieve. Even thing that you may want to achieve. Even if you're trying to like climb the if you're trying to like climb the if you're trying to like climb the rungs, rungs, rungs, you very quickly learn that the more you you very quickly learn that the more you you very quickly learn that the more you want something, the less you're going to want something, the less you're going to want something, the less you're going to get it. And I think that's like his real get it. And I think that's like his real get it. And I think that's like his real message is let go, live life, and just message is let go, live life, and just message is let go, live life, and just try stuff or don't try stuff. And I try stuff or don't try stuff. And I try stuff or don't try stuff. And I think that that detachment is really think that that detachment is really think that that detachment is really healthy for people. I like it. I like it healthy for people. I like it. I like it healthy for people. I like it. I like it a lot. a lot. a lot. >> Who's the guy who says this? I actually >> Who's the guy who says this? I actually >> Who's the guy who says this? I actually didn't know. didn't know. didn't know. >> Elisha Long. Well, Eli, I think, is how >> Elisha Long. Well, Eli, I think, is how >> Elisha Long. Well, Eli, I think, is how he goes by. he goes by. he goes by. >> But he's fantastic. He Mark YouTube >> But he's fantastic. He Mark YouTube >> But he's fantastic. He Mark YouTube channel. channel. channel. >> Mark Andre found him >> Mark Andre found him >> Mark Andre found him >> and he's like, "This is this guy is the >> and he's like, "This is this guy is the >> and he's like, "This is this guy is the new guy. new guy. new guy. >> Modernday philosopher. He gives you a >> Modernday philosopher. He gives you a >> Modernday philosopher. He gives you a road map for how to live your life, road map for how to live your life, road map for how to live your life, right? A new age sage. right? A new age sage. right? A new age sage. >> What's the name of the guy? The >> What's the name of the guy? The >> What's the name of the guy? The character's name from Dune. character's name from Dune. character's name from Dune. >> I was into girls books. I was dating >> I was into girls books. I was dating >> I was into girls books. I was dating girls. girls. girls. >> He's the Lison Algib of the modern >> He's the Lison Algib of the modern >> He's the Lison Algib of the modern internet. internet. internet. >> This is why we need Freeberg here is to >> This is why we need Freeberg here is to >> This is why we need Freeberg here is to explain these deep holes. All right, explain these deep holes. All right, explain these deep holes. All right, listen. We got a lot to get to. Don't listen. We got a lot to get to. Don't listen. We got a lot to get to. Don't The basic point is build something and The basic point is build something and The basic point is build something and don't ruminate. Okay, ruminating is just don't ruminate. Okay, ruminating is just don't ruminate. Okay, ruminating is just not worth it. Just everybody go for it. not worth it. Just everybody go for it. not worth it. Just everybody go for it. >> No, just do stuff. Stop blathering in >> No, just do stuff. Stop blathering in >> No, just do stuff. Stop blathering in your own head. Just do stuff. your own head. Just do stuff. your own head. Just do stuff. Absolutely. All right. Listen, speaking Absolutely. All right. Listen, speaking Absolutely. All right. Listen, speaking of doing so, Anthropic is withholding of doing so, Anthropic is withholding of doing so, Anthropic is withholding its newest model, Mythos. I'm using the its newest model, Mythos. I'm using the its newest model, Mythos. I'm using the Greek uh pronunciation, its newest Greek uh pronunciation, its newest Greek uh pronunciation, its newest model, Mythos, uh saying it is far too model, Mythos, uh saying it is far too model, Mythos, uh saying it is far too dangerous for any of us to have access dangerous for any of us to have access dangerous for any of us to have access to it. According to the company, the to it. According to the company, the to it. According to the company, the model autonomously found thousands of model autonomously found thousands of model autonomously found thousands of vulnerabilities, including bugs in every vulnerabilities, including bugs in every vulnerabilities, including bugs in every major operating system and web browser. major operating system and web browser. major operating system and web browser. This uh little study they did included This uh little study they did included This uh little study they did included 20 year old exploits that had been 20 year old exploits that had been 20 year old exploits that had been missed by security audits for decades. missed by security audits for decades. missed by security audits for decades. Uh some examples, they found a 27y old Uh some examples, they found a 27y old Uh some examples, they found a 27y old vulnerability in OpenBSD used in vulnerability in OpenBSD used in vulnerability in OpenBSD used in firewalls and critical infrastructure. firewalls and critical infrastructure. firewalls and critical infrastructure. They found a 16-year-old bug in FFmpeg They found a 16-year-old bug in FFmpeg They found a 16-year-old bug in FFmpeg that was missed by automated tools after that was missed by automated tools after that was missed by automated tools after 5 million scans. The Linux kernel, all 5 million scans. The Linux kernel, all 5 million scans. The Linux kernel, all kinds of uh bugs they found. They kinds of uh bugs they found. They kinds of uh bugs they found. They released a hype video hyping up why they released a hype video hyping up why they released a hype video hyping up why they were not going to share this model. were not going to share this model. were not going to share this model. Here's Dario. Come on the program Here's Dario. Come on the program Here's Dario. Come on the program anytime, brother. anytime, brother. anytime, brother. >> But as a side effect of being good at >> But as a side effect of being good at >> But as a side effect of being good at code, it's also good at cyber. code, it's also good at cyber. code, it's also good at cyber. >> The model that we're experimenting with >> The model that we're experimenting with >> The model that we're experimenting with is by and large as good as a is by and large as good as a is by and large as good as a professional human at identifying bugs. professional human at identifying bugs. professional human at identifying bugs. It's good for us because we can find It's good for us because we can find It's good for us because we can find more vulnerabilities sooner and we can more vulnerabilities sooner and we can more vulnerabilities sooner and we can fix them. fix them. fix them. >> It has the ability to chain together >> It has the ability to chain together >> It has the ability to chain together vulnerabilities. So what this means is vulnerabilities. So what this means is vulnerabilities. So what this means is you find two vulnerabilities, either of you find two vulnerabilities, either of you find two vulnerabilities, either of which doesn't really get you very much which doesn't really get you very much which doesn't really get you very much independently, but this model is able to independently, but this model is able to independently, but this model is able to create exploits out of three, four, create exploits out of three, four, create exploits out of three, four, sometimes five vulnerabilities that in sometimes five vulnerabilities that in sometimes five vulnerabilities that in sequence give you some kind of very sequence give you some kind of very sequence give you some kind of very sophisticated end outcome. sophisticated end outcome. sophisticated end outcome. >> All right, Brad, uh, by the way, that >> All right, Brad, uh, by the way, that >> All right, Brad, uh, by the way, that set they're using there, that's the same set they're using there, that's the same set they're using there, that's the same room those guys play Dungeons and room those guys play Dungeons and room those guys play Dungeons and Dragons in every Sunday. Brad, you're Dragons in every Sunday. Brad, you're Dragons in every Sunday. Brad, you're Brad, you're an investor in this Brad, you're an investor in this Brad, you're an investor in this company. Is this virtue signaling or is company. Is this virtue signaling or is company. Is this virtue signaling or is it reality? Is this a good move by them it reality? Is this a good move by them it reality? Is this a good move by them to not release this model and be to not release this model and be to not release this model and be thoughtful, give it to a handful of thoughtful, give it to a handful of thoughtful, give it to a handful of people and just find all the bugs it can people and just find all the bugs it can people and just find all the bugs it can before releasing it to the public? And before releasing it to the public? And before releasing it to the public? And we've got a lot more issues to discuss. we've got a lot more issues to discuss. we've got a lot more issues to discuss. >> I I actually think they deserve a ton of >> I I actually think they deserve a ton of >> I I actually think they deserve a ton of credit here and let me walk you through credit here and let me walk you through credit here and let me walk you through why, right? They the company could have why, right? They the company could have why, right? They the company could have just released Mythos, broken a lot of just released Mythos, broken a lot of just released Mythos, broken a lot of core things on the internet. Often times core things on the internet. Often times core things on the internet. Often times in Silicon Valley, we say move fast and in Silicon Valley, we say move fast and in Silicon Valley, we say move fast and break things. In this case, it means break things. In this case, it means break things. In this case, it means just releasing the model to move further just releasing the model to move further just releasing the model to move further ahead of your competition. But here the ahead of your competition. But here the ahead of your competition. But here the company realized it would wreak havoc. company realized it would wreak havoc. company realized it would wreak havoc. They ran their own vulnerability They ran their own vulnerability They ran their own vulnerability testing. They saw that it would allow testing. They saw that it would allow testing. They saw that it would allow offensive hacking and people to expose offensive hacking and people to expose offensive hacking and people to expose browsers and browser history, expose browsers and browser history, expose browsers and browser history, expose credit cards, you know, on the internet. credit cards, you know, on the internet. credit cards, you know, on the internet. So, you know what I like about this is So, you know what I like about this is So, you know what I like about this is they didn't need government to hold they didn't need government to hold they didn't need government to hold their hand on this. We have plenty of their hand on this. We have plenty of their hand on this. We have plenty of government regulations. They know it's government regulations. They know it's government regulations. They know it's in the best long-term interest of the in the best long-term interest of the in the best long-term interest of the company and the industry, you know. So, company and the industry, you know. So, company and the industry, you know. So, they set up Project Glass Wing. It's an they set up Project Glass Wing. It's an they set up Project Glass Wing. It's an AIdriven, you know, kind of cyber AIdriven, you know, kind of cyber AIdriven, you know, kind of cyber coalition. Apple, Microsoft, Google, coalition. Apple, Microsoft, Google, coalition. Apple, Microsoft, Google, Amazon, JP Morgan, 40 of the most Amazon, JP Morgan, 40 of the most Amazon, JP Morgan, 40 of the most important companies. And their goal is important companies. And their goal is important companies. And their goal is very simple. Let's spend a 100 days use very simple. Let's spend a 100 days use very simple. Let's spend a 100 days use advanced AI to find and to fix and to advanced AI to find and to fix and to advanced AI to find and to fix and to harden these software vulnerabilities harden these software vulnerabilities harden these software vulnerabilities before hackers exploit them. Now, what I before hackers exploit them. Now, what I before hackers exploit them. Now, what I think this represents, Jason, is a think this represents, Jason, is a think this represents, Jason, is a threshold that we're crossing. Mythos threshold that we're crossing. Mythos threshold that we're crossing. Mythos and Spud, which is going to be out from and Spud, which is going to be out from and Spud, which is going to be out from OpenAI any day now, which is the first OpenAI any day now, which is the first OpenAI any day now, which is the first Blackwell trained model at OpenAI. They Blackwell trained model at OpenAI. They Blackwell trained model at OpenAI. They represent the beginning of what I would represent the beginning of what I would represent the beginning of what I would call AGI models. These are models with call AGI models. These are models with call AGI models. These are models with massive step function improvements and massive step function improvements and massive step function improvements and intelligence. Um, and they're just too intelligence. Um, and they're just too intelligence. Um, and they're just too smart to be released immediately, smart to be released immediately, smart to be released immediately, you know. And by the way, there was you know. And by the way, there was you know. And by the way, there was nothing that said that every time you nothing that said that every time you nothing that said that every time you you finish a model, you got to you finish a model, you got to you finish a model, you got to immediately release it GA. So they set immediately release it GA. So they set immediately release it GA. So they set up this idea of sandboxing, building up this idea of sandboxing, building up this idea of sandboxing, building defensive alliances, defensive alliances, defensive alliances, you know, in order to move away from you know, in order to move away from you know, in order to move away from that regime. I I think it shows, and that regime. I I think it shows, and that regime. I I think it shows, and Saxon and I have talked about this a Saxon and I have talked about this a Saxon and I have talked about this a lot, so I'm interested to hear what he lot, so I'm interested to hear what he lot, so I'm interested to hear what he thinks. It shows you can trust the thinks. It shows you can trust the thinks. It shows you can trust the industry and market forces in industry and market forces in industry and market forces in coordination with the government. They coordination with the government. They coordination with the government. They were talking to the government about were talking to the government about were talking to the government about this. But they're not relying on some this. But they're not relying on some this. But they're not relying on some top- down regulation in order to do top- down regulation in order to do top- down regulation in order to do this. They laid out a blueprint that this. They laid out a blueprint that this. They laid out a blueprint that seems to me very pragmatic that now that seems to me very pragmatic that now that seems to me very pragmatic that now that we're at this threshold, we're going to we're at this threshold, we're going to we're at this threshold, we're going to sandbox these things. I think that open sandbox these things. I think that open sandbox these things. I think that open AAI will end up doing the same thing. I AAI will end up doing the same thing. I AAI will end up doing the same thing. I think Google will end up doing the same think Google will end up doing the same think Google will end up doing the same thing. It's an aggressive way to keep thing. It's an aggressive way to keep thing. It's an aggressive way to keep the RA, you know, the pressure on and the RA, you know, the pressure on and the RA, you know, the pressure on and and win the race at AI while making the and win the race at AI while making the and win the race at AI while making the tradeoffs to protect safety. So, you tradeoffs to protect safety. So, you tradeoffs to protect safety. So, you know, I think you're always going to know, I think you're always going to know, I think you're always going to have to make these trade-offs. I think have to make these trade-offs. I think have to make these trade-offs. I think in this case, it was a great move by in this case, it was a great move by in this case, it was a great move by Dario and team and I think they deserve Dario and team and I think they deserve Dario and team and I think they deserve a lot of credit. Sachs, when you look at a lot of credit. Sachs, when you look at a lot of credit. Sachs, when you look at this, we had Emil Michael on the program this, we had Emil Michael on the program this, we had Emil Michael on the program a couple weeks ago. It might have been a couple weeks ago. It might have been a couple weeks ago. It might have been four or five weeks ago, and we had a four or five weeks ago, and we had a four or five weeks ago, and we had a very thoughtful discussion about, hey, very thoughtful discussion about, hey, very thoughtful discussion about, hey, if the government is going to have these if the government is going to have these if the government is going to have these tools, you know, an anthropic wants to tools, you know, an anthropic wants to tools, you know, an anthropic wants to withhold them and, you know, what is the withhold them and, you know, what is the withhold them and, you know, what is the proper relationship there, you have to proper relationship there, you have to proper relationship there, you have to think that the government, and I know think that the government, and I know think that the government, and I know you don't speak for all parts of the you don't speak for all parts of the you don't speak for all parts of the government. If you were just going to government. If you were just going to government. If you were just going to run through the game theory, they must run through the game theory, they must run through the game theory, they must have gone to the government and said, have gone to the government and said, have gone to the government and said, "Listen, this thing is so powerful, it "Listen, this thing is so powerful, it "Listen, this thing is so powerful, it can put together two or three hacks, can put together two or three hacks, can put together two or three hacks, create a novel attack vector, and this create a novel attack vector, and this create a novel attack vector, and this is incredibly dangerous. What if China is incredibly dangerous. What if China is incredibly dangerous. What if China has it? And if this thing is as powerful has it? And if this thing is as powerful has it? And if this thing is as powerful as Daario says it is, then this is an as Daario says it is, then this is an as Daario says it is, then this is an offensive weapon as well for us to take offensive weapon as well for us to take offensive weapon as well for us to take out, let's just pick, you know, uh, a out, let's just pick, you know, uh, a out, let's just pick, you know, uh, a pressing issue, the North Korea's pressing issue, the North Korea's pressing issue, the North Korea's ballistic missile program. This is ballistic missile program. This is ballistic missile program. This is equivalent the way it's being described equivalent the way it's being described equivalent the way it's being described as the Manhattan project perhaps. So as the Manhattan project perhaps. So as the Manhattan project perhaps. So what are the chances two-part question what are the chances two-part question what are the chances two-part question for you Sax that China already has this for you Sax that China already has this for you Sax that China already has this and is using it and do you think Daario and is using it and do you think Daario and is using it and do you think Daario is doing the right thing by regulating is doing the right thing by regulating is doing the right thing by regulating themselves? themselves? themselves? >> I think Anthropic has proven that it's >> I think Anthropic has proven that it's >> I think Anthropic has proven that it's very good at two things. One is product very good at two things. One is product very good at two things. One is product releases. The second is scaring people. releases. The second is scaring people. releases. The second is scaring people. And we've seen a pattern in their And we've seen a pattern in their And we've seen a pattern in their previous releases of at the same time previous releases of at the same time previous releases of at the same time they roll out a new model or new model they roll out a new model or new model they roll out a new model or new model card, something like that. They also card, something like that. They also card, something like that. They also roll out some study showing really the roll out some study showing really the roll out some study showing really the worst possible implication of where the worst possible implication of where the worst possible implication of where the technology could lead. We saw this last technology could lead. We saw this last technology could lead. We saw this last year about a year ago. They rolled out year about a year ago. They rolled out year about a year ago. They rolled out this blackmail study where supposedly this blackmail study where supposedly this blackmail study where supposedly the new model could blackmail users. the new model could blackmail users. the new model could blackmail users. There's been a whole bunch of these There's been a whole bunch of these There's been a whole bunch of these things. Actually, I went back to Grock things. Actually, I went back to Grock things. Actually, I went back to Grock and I just asked, "Hey, give me examples and I just asked, "Hey, give me examples and I just asked, "Hey, give me examples where Antropic has basically used scare where Antropic has basically used scare where Antropic has basically used scare tactics and it's it's a pattern." Okay, tactics and it's it's a pattern." Okay, tactics and it's it's a pattern." Okay, it's a pattern. it's a pattern. it's a pattern. >> Okay, >> Okay, >> Okay, >> these guys, I'm not saying it's not >> these guys, I'm not saying it's not >> these guys, I'm not saying it's not sincere, but they have a proven pattern sincere, but they have a proven pattern sincere, but they have a proven pattern of using fear as a way to market their of using fear as a way to market their of using fear as a way to market their new products. And if you think back to, new products. And if you think back to, new products. And if you think back to, again, my favorite example is this again, my favorite example is this again, my favorite example is this blackmail study where they prompted the blackmail study where they prompted the blackmail study where they prompted the model over 200 times to get the result model over 200 times to get the result model over 200 times to get the result they wanted. And that result was was they wanted. And that result was was they wanted. And that result was was clearly reverse engineered and it got clearly reverse engineered and it got clearly reverse engineered and it got them the headlines they wanted. And I them the headlines they wanted. And I them the headlines they wanted. And I would say the proof that it's reverse would say the proof that it's reverse would say the proof that it's reverse engineered is we're now a year later. engineered is we're now a year later. engineered is we're now a year later. There's a bunch of open- source models There's a bunch of open- source models There's a bunch of open- source models out there that have the same level of out there that have the same level of out there that have the same level of capability that that anthropic model capability that that anthropic model capability that that anthropic model had. And have you seen any examples of had. And have you seen any examples of had. And have you seen any examples of blackmail in the wild? I don't think so. blackmail in the wild? I don't think so. blackmail in the wild? I don't think so. So in other words, if that study were So in other words, if that study were So in other words, if that study were true in the sense of being a likely true in the sense of being a likely true in the sense of being a likely outcome of that model, I think you would outcome of that model, I think you would outcome of that model, I think you would see examples in the wild of that see examples in the wild of that see examples in the wild of that behavior. And we haven't seen any of behavior. And we haven't seen any of behavior. And we haven't seen any of that in the past year. Now, let's talk that in the past year. Now, let's talk that in the past year. Now, let's talk about this specific example with cyber about this specific example with cyber about this specific example with cyber hacking. hacking. hacking. >> I actually think that this one is more >> I actually think that this one is more >> I actually think that this one is more on the legitimate side. I mean, look, on the legitimate side. I mean, look, on the legitimate side. I mean, look, the reason why I bring this up is the reason why I bring this up is the reason why I bring this up is anytime Anthropic is scaring people, you anytime Anthropic is scaring people, you anytime Anthropic is scaring people, you have to ask, is this a tactic? Is this have to ask, is this a tactic? Is this have to ask, is this a tactic? Is this part of their Chicken Little routine? or part of their Chicken Little routine? or part of their Chicken Little routine? or is it real? You know, are they crying is it real? You know, are they crying is it real? You know, are they crying wolf or not? I actually would give them wolf or not? I actually would give them wolf or not? I actually would give them credit in this case and say this is more credit in this case and say this is more credit in this case and say this is more on the the real side. It just makes on the the real side. It just makes on the the real side. It just makes sense, right? So that as the coding sense, right? So that as the coding sense, right? So that as the coding models become more and more capable, models become more and more capable, models become more and more capable, they're more capable of finding bugs. they're more capable of finding bugs. they're more capable of finding bugs. That means they're more capable of That means they're more capable of That means they're more capable of finding vulnerabilities. And like one of finding vulnerabilities. And like one of finding vulnerabilities. And like one of their engineers said, that means they're their engineers said, that means they're their engineers said, that means they're more capable of stringing together more capable of stringing together more capable of stringing together multiple vulnerabilities and creating an multiple vulnerabilities and creating an multiple vulnerabilities and creating an exploit. And so I do think that over say exploit. And so I do think that over say exploit. And so I do think that over say the next 6 months we're going to have the next 6 months we're going to have the next 6 months we're going to have this call it one-time period of catching this call it one-time period of catching this call it one-time period of catching up where AIdriven cyber is going to be up where AIdriven cyber is going to be up where AIdriven cyber is going to be able to detect a whole range of of bugs able to detect a whole range of of bugs able to detect a whole range of of bugs that maybe have been dormant over the that maybe have been dormant over the that maybe have been dormant over the past 20 years across a wide range of past 20 years across a wide range of past 20 years across a wide range of systems. And so I do think that there is systems. And so I do think that there is systems. And so I do think that there is real risk here. And I do think therefore real risk here. And I do think therefore real risk here. And I do think therefore that having this pre-release period that having this pre-release period that having this pre-release period makes a lot of sense where they're makes a lot of sense where they're makes a lot of sense where they're giving the capability to all these giving the capability to all these giving the capability to all these software companies that have existing software companies that have existing software companies that have existing code bases to use the tool to detect the code bases to use the tool to detect the code bases to use the tool to detect the vulnerabilities for themselves so they vulnerabilities for themselves so they vulnerabilities for themselves so they can patch them before these capabilities can patch them before these capabilities can patch them before these capabilities are widely available. And by the way, it are widely available. And by the way, it are widely available. And by the way, it won't just be anthropic that makes these won't just be anthropic that makes these won't just be anthropic that makes these capabilities available. We know that capabilities available. We know that capabilities available. We know that like let's say the Chinese open source like let's say the Chinese open source like let's say the Chinese open source models like Kimmy K2, it's about 6 models like Kimmy K2, it's about 6 models like Kimmy K2, it's about 6 months behind. So we have a window here months behind. So we have a window here months behind. So we have a window here of maybe 6 months where we're still in of maybe 6 months where we're still in of maybe 6 months where we're still in this pre-release period where I think this pre-release period where I think this pre-release period where I think companies that have large code bases can companies that have large code bases can companies that have large code bases can get advanced access to this model and uh get advanced access to this model and uh get advanced access to this model and uh I guess open AI is going to release a I guess open AI is going to release a I guess open AI is going to release a similar thing in the next few weeks. I similar thing in the next few weeks. I similar thing in the next few weeks. I do think that every company or IT do think that every company or IT do think that every company or IT department or CISO that is managing code department or CISO that is managing code department or CISO that is managing code bases should take this seriously and use bases should take this seriously and use bases should take this seriously and use the next few months to detect any again the next few months to detect any again the next few months to detect any again like dormant bugs or vulnerabilities and like dormant bugs or vulnerabilities and like dormant bugs or vulnerabilities and and roll out patches. If everybody does and roll out patches. If everybody does and roll out patches. If everybody does their job and reacts the right way, then their job and reacts the right way, then their job and reacts the right way, then I do not think it will be the doomsday I do not think it will be the doomsday I do not think it will be the doomsday scenario that Anthropic is sort of scenario that Anthropic is sort of scenario that Anthropic is sort of portraying. But it's one of these things portraying. But it's one of these things portraying. But it's one of these things where the fear might end up being a good where the fear might end up being a good where the fear might end up being a good thing in order to drive people to in thing in order to drive people to in thing in order to drive people to in order to drive the correct behavior. So order to drive the correct behavior. So order to drive the correct behavior. So >> sure, >> sure, >> sure, >> I ultimately think this is going to work >> I ultimately think this is going to work >> I ultimately think this is going to work out fine, but you do need everyone to out fine, but you do need everyone to out fine, but you do need everyone to kind of pay attention, use the kind of pay attention, use the kind of pay attention, use the capabilities, capabilities, capabilities, >> fix the bugs, then we're going to get >> fix the bugs, then we're going to get >> fix the bugs, then we're going to get into a big arms race between AI being into a big arms race between AI being into a big arms race between AI being used for cyber offense and AI being used used for cyber offense and AI being used used for cyber offense and AI being used for cyber defense, but it'll be a more for cyber defense, but it'll be a more for cyber defense, but it'll be a more normal sort of of period. Chimath, we normal sort of of period. Chimath, we normal sort of of period. Chimath, we have uh Daario and uh you know a number have uh Daario and uh you know a number have uh Daario and uh you know a number of the participants here are taking this of the participants here are taking this of the participants here are taking this super seriously. They're making a big super seriously. They're making a big super seriously. They're making a big statement. Zach's very nuanced uh I statement. Zach's very nuanced uh I statement. Zach's very nuanced uh I think take there. What's your take on think take there. What's your take on think take there. What's your take on how do these companies have it both how do these companies have it both how do these companies have it both ways? Hey, this is shouldn't be ways? Hey, this is shouldn't be ways? Hey, this is shouldn't be regulated. This should be regulated. If regulated. This should be regulated. If regulated. This should be regulated. If this is in fact a cataclysmic, oh my this is in fact a cataclysmic, oh my this is in fact a cataclysmic, oh my god, they're going to hack everything. god, they're going to hack everything. god, they're going to hack everything. What if the Chinese have this right now? What if the Chinese have this right now? What if the Chinese have this right now? That would speak to more government That would speak to more government That would speak to more government either coordination, regulation, or some either coordination, regulation, or some either coordination, regulation, or some kind of relationship between the CIA, kind of relationship between the CIA, kind of relationship between the CIA, the FBI for domestic stuff, and these the FBI for domestic stuff, and these the FBI for domestic stuff, and these companies because there it is a non-zero companies because there it is a non-zero companies because there it is a non-zero chance that the Chinese have an equal chance that the Chinese have an equal chance that the Chinese have an equal capability here. We're assuming they're capability here. We're assuming they're capability here. We're assuming they're behind, but who knows what they're doing behind, but who knows what they're doing behind, but who knows what they're doing behind closed doors. So, what's your behind closed doors. So, what's your behind closed doors. So, what's your take on this? Is it uh The Boy Who Cried take on this? Is it uh The Boy Who Cried take on this? Is it uh The Boy Who Cried Wolf, or is this the real deal? Now, Wolf, or is this the real deal? Now, Wolf, or is this the real deal? Now, >> I think it's mostly theater. >> I think it's mostly theater. >> I think it's mostly theater. >> Okay. >> Okay. >> Okay. In February of 2019, In February of 2019, In February of 2019, when Daario was still at OpenAI, when Daario was still at OpenAI, when Daario was still at OpenAI, they did the same thing with GPT2. they did the same thing with GPT2. they did the same thing with GPT2. That was a 1.5 billion parameter model, That was a 1.5 billion parameter model, That was a 1.5 billion parameter model, which sounds like a total fart in the which sounds like a total fart in the which sounds like a total fart in the wind in 2026. But at that time, this 1.5 wind in 2026. But at that time, this 1.5 wind in 2026. But at that time, this 1.5 billion parameter model was supposed to billion parameter model was supposed to billion parameter model was supposed to be the end of days. And it was supposed be the end of days. And it was supposed be the end of days. And it was supposed to unleash this torrent of spam and to unleash this torrent of spam and to unleash this torrent of spam and misinformation. And that was the big misinformation. And that was the big misinformation. And that was the big bugaboo at the time. And so what bugaboo at the time. And so what bugaboo at the time. And so what happened? They went through this happened? They went through this happened? They went through this methodical roll out over six or nine methodical roll out over six or nine methodical roll out over six or nine months. They started releasing the months. They started releasing the months. They started releasing the smaller parameter models and then they smaller parameter models and then they smaller parameter models and then they scaled up to the big 1.5 billion scaled up to the big 1.5 billion scaled up to the big 1.5 billion parameter model. And at the end of it, parameter model. And at the end of it, parameter model. And at the end of it, it was a huge nothing burger. it was a huge nothing burger. it was a huge nothing burger. If you actually think that Mythos is If you actually think that Mythos is If you actually think that Mythos is capable of doing what it says it can do, capable of doing what it says it can do, capable of doing what it says it can do, two things are true. One is a very two things are true. One is a very two things are true. One is a very sophisticated hacker can probably do sophisticated hacker can probably do sophisticated hacker can probably do those things right now with Opus. those things right now with Opus. those things right now with Opus. And two, if these exploits And two, if these exploits And two, if these exploits are this easy to find, are this easy to find, are this easy to find, whether you use Opus or whether you use whether you use Opus or whether you use whether you use Opus or whether you use Mythos, the reality is you'd have to Mythos, the reality is you'd have to Mythos, the reality is you'd have to shut down the internet for about 5 years shut down the internet for about 5 years shut down the internet for about 5 years to patch them all. So when you see like to patch them all. So when you see like to patch them all. So when you see like a large multi- trillion dollar gang, a large multi- trillion dollar gang, a large multi- trillion dollar gang, it's a bit of theater. Why? What do you it's a bit of theater. Why? What do you it's a bit of theater. Why? What do you think they can actually accomplish in 2 think they can actually accomplish in 2 think they can actually accomplish in 2 months? Do you actually think that if months? Do you actually think that if months? Do you actually think that if there's these vulnerabilities, it's all there's these vulnerabilities, it's all there's these vulnerabilities, it's all going to get fixed? Let's give them six going to get fixed? Let's give them six going to get fixed? Let's give them six months. Let's give them nine months. But months. Let's give them nine months. But months. Let's give them nine months. But the reality is that capitalism moves the reality is that capitalism moves the reality is that capitalism moves forward, the funding needs moves forward, the funding needs moves forward, the funding needs moves forward, and the need for these guys to forward, and the need for these guys to forward, and the need for these guys to build adoption moves forward. And that's build adoption moves forward. And that's build adoption moves forward. And that's going to supersede going to supersede going to supersede what this is. So I do think that Sax is what this is. So I do think that Sax is what this is. So I do think that Sax is right that they have figured out a very right that they have figured out a very right that they have figured out a very clever go-to market muscle here and a go clever go-to market muscle here and a go clever go-to market muscle here and a go to market motion that activates to market motion that activates to market motion that activates hyper attention and hyper usage and so I hyper attention and hyper usage and so I hyper attention and hyper usage and so I give them tremendous credit and I'll give them tremendous credit and I'll give them tremendous credit and I'll maintain what I've maintained before. maintain what I've maintained before. maintain what I've maintained before. Anthropic is shooting the lights out Anthropic is shooting the lights out Anthropic is shooting the lights out right now. This is like Steph Curry right now. This is like Steph Curry right now. This is like Steph Curry going bananas from every everywhere on going bananas from every everywhere on going bananas from every everywhere on the court. These guys are hunking the court. These guys are hunking the court. These guys are hunking threes. threes. threes. >> It's all in that. Okay. So huge kudos to >> It's all in that. Okay. So huge kudos to >> It's all in that. Okay. So huge kudos to Anthropic, Anthropic, Anthropic, but we've seen it before. We saw it when but we've seen it before. We saw it when but we've seen it before. We saw it when these folks were the principal these folks were the principal these folks were the principal architects at OpenAI who are now seeing architects at OpenAI who are now seeing architects at OpenAI who are now seeing the same playbook here. I think we'll the same playbook here. I think we'll the same playbook here. I think we'll look back and I think what we'll say are look back and I think what we'll say are look back and I think what we'll say are these two things. One is if we're really these two things. One is if we're really these two things. One is if we're really going to patch all these security holes, going to patch all these security holes, going to patch all these security holes, we need to shut down the internet we need to shut down the internet we need to shut down the internet for some number of years, honestly, for some number of years, honestly, for some number of years, honestly, literally years. And the second is an literally years. And the second is an literally years. And the second is an advanced hacker can probably do this advanced hacker can probably do this advanced hacker can probably do this today with Opus if they really wanted today with Opus if they really wanted today with Opus if they really wanted to. to. to. >> Okay. Hey Brad, I gota I'll get you in >> Okay. Hey Brad, I gota I'll get you in >> Okay. Hey Brad, I gota I'll get you in here for the for the last word. I I'm here for the for the last word. I I'm here for the for the last word. I I'm going to go with Yeah, maybe they did uh going to go with Yeah, maybe they did uh going to go with Yeah, maybe they did uh Crywolf before, but based on what I see Crywolf before, but based on what I see Crywolf before, but based on what I see with these models advancing and using with these models advancing and using with these models advancing and using them and I'm using a lot of the open them and I'm using a lot of the open them and I'm using a lot of the open source ones right now from China. I source ones right now from China. I source ones right now from China. I think that this is like code red kind of think that this is like code red kind of think that this is like code red kind of moment. This is Defcon. like we should moment. This is Defcon. like we should moment. This is Defcon. like we should be taking this deadly seriously and I be taking this deadly seriously and I be taking this deadly seriously and I think these companies got to coordinate think these companies got to coordinate think these companies got to coordinate with the CIA and this is uh equally a with the CIA and this is uh equally a with the CIA and this is uh equally a defensive as offensive opportunity. Do defensive as offensive opportunity. Do defensive as offensive opportunity. Do you think this you think this you think this >> you're asking for the nationalization of >> you're asking for the nationalization of >> you're asking for the nationalization of AI now? AI now? AI now? >> No, I actually I I I don't think it >> No, I actually I I I don't think it >> No, I actually I I I don't think it should be nationalized. Um although I should be nationalized. Um although I should be nationalized. Um although I did see people sort of insinuating that. did see people sort of insinuating that. did see people sort of insinuating that. I think these companies need to build a I think these companies need to build a I think these companies need to build a group Brad that work and coordinate with group Brad that work and coordinate with group Brad that work and coordinate with the CIA. I assume that they're already the CIA. I assume that they're already the CIA. I assume that they're already doing this. I'm assuming you Emil doing this. I'm assuming you Emil doing this. I'm assuming you Emil Michael and uh you know Trump and Michael and uh you know Trump and Michael and uh you know Trump and everybody have these people in a room everybody have these people in a room everybody have these people in a room and that they've given the defcon and and that they've given the defcon and and that they've given the defcon and said hey how can our government use this said hey how can our government use this said hey how can our government use this to stop bad actors and this is already to stop bad actors and this is already to stop bad actors and this is already being coordinated with the CIA and the being coordinated with the CIA and the being coordinated with the CIA and the FBI. I am 100% certain of that that FBI. I am 100% certain of that that FBI. I am 100% certain of that that Dario went to them and said look what we Dario went to them and said look what we Dario went to them and said look what we found. This is the real deal. I'll give found. This is the real deal. I'll give found. This is the real deal. I'll give you the last word on this Brad since you the last word on this Brad since you the last word on this Brad since you're an investor in both companies and you're an investor in both companies and you're an investor in both companies and you know them quite well. the frontier you know them quite well. the frontier you know them quite well. the frontier model forum which was which was put model forum which was which was put model forum which was which was put together in 23 um is cooperating on together in 23 um is cooperating on together in 23 um is cooperating on anti- and adversarial distillation stuff anti- and adversarial distillation stuff anti- and adversarial distillation stuff as we speak right they don't want to as we speak right they don't want to as we speak right they don't want to make it easy on you know so Google and make it easy on you know so Google and make it easy on you know so Google and and open AAI and and anthropic they're and open AAI and and anthropic they're and open AAI and and anthropic they're coordinating on this stuff you know coordinating on this stuff you know coordinating on this stuff you know there are times where I've pushed back there are times where I've pushed back there are times where I've pushed back on anthropic because I thought it was on anthropic because I thought it was on anthropic because I thought it was you know perhaps regulatory capture or you know perhaps regulatory capture or you know perhaps regulatory capture or something else this is very different in something else this is very different in something else this is very different in my mind right he could have easily Dario my mind right he could have easily Dario my mind right he could have easily Dario could have easily come out and said oh could have easily come out and said oh could have easily come out and said oh my god we passed a threshold we need to my god we passed a threshold we need to my god we passed a threshold we need to have a government moratorum. Remember, have a government moratorum. Remember, have a government moratorum. Remember, even our friend Elon called for a even our friend Elon called for a even our friend Elon called for a six-month moratorium in 2023 because of six-month moratorium in 2023 because of six-month moratorium in 2023 because of civilization risk. This guy didn't do civilization risk. This guy didn't do civilization risk. This guy didn't do that. Instead, he said, "Okay, what what that. Instead, he said, "Okay, what what that. Instead, he said, "Okay, what what should we do? I'm going to get 40 of the should we do? I'm going to get 40 of the should we do? I'm going to get 40 of the leading companies together. We're going leading companies together. We're going leading companies together. We're going to spend a 100 days sandboxing, to spend a 100 days sandboxing, to spend a 100 days sandboxing, hardening the systems, and then we're hardening the systems, and then we're hardening the systems, and then we're we're we're going to keep pushing we're we're going to keep pushing we're we're going to keep pushing forward." forward." forward." >> What do you honestly think is going to >> What do you honestly think is going to >> What do you honestly think is going to get accomplished in a 100 days? How many get accomplished in a 100 days? How many get accomplished in a 100 days? How many PRs you think are going to get pushed to PRs you think are going to get pushed to PRs you think are going to get pushed to the core structural internet in 100 the core structural internet in 100 the core structural internet in 100 days? What's the overunder number? Cuz days? What's the overunder number? Cuz days? What's the overunder number? Cuz I'll give you a number. You're gonna say I'll give you a number. You're gonna say I'll give you a number. You're gonna say zero. My my answer to that is zero. My my answer to that is zero. My my answer to that is >> I'll say like 10,000, but it's going to >> I'll say like 10,000, but it's going to >> I'll say like 10,000, but it's going to be immediate. be immediate. be immediate. >> But if it prevents your browser history >> But if it prevents your browser history >> But if it prevents your browser history from being released to everybody in the from being released to everybody in the from being released to everybody in the world, Chimat, that may be something world, Chimat, that may be something world, Chimat, that may be something that you're willing to, you know, let a that you're willing to, you know, let a that you're willing to, you know, let a 100 days pass on. 100 days pass on. 100 days pass on. >> I think you got Chimat's attention when >> I think you got Chimat's attention when >> I think you got Chimat's attention when you said browser history. you said browser history. you said browser history. >> What about the dickpicks? >> As Chimat is, he's going to release them >> As Chimat is, he's going to release them himself right now. CHIMAT'S LIKE, "HEY, himself right now. CHIMAT'S LIKE, "HEY, himself right now. CHIMAT'S LIKE, "HEY, CHINESE HACKERS, HERE ARE MY DICKPICKS. CHINESE HACKERS, HERE ARE MY DICKPICKS. CHINESE HACKERS, HERE ARE MY DICKPICKS. Please put them out." Please put them out." Please put them out." >> Oh my god. we have to be out there >> Oh my god. we have to be out there >> Oh my god. we have to be out there complimenting when they're doing the complimenting when they're doing the complimenting when they're doing the right things or relying on the market right things or relying on the market right things or relying on the market rather than running to the nanny state rather than running to the nanny state rather than running to the nanny state and saying do more of this. So this to and saying do more of this. So this to and saying do more of this. So this to me was just an example of of a of a good me was just an example of of a of a good me was just an example of of a of a good balance. I'm sure we're going to have balance. I'm sure we're going to have balance. I'm sure we're going to have plenty of debates about this in the plenty of debates about this in the plenty of debates about this in the future. But you know this is one I would future. But you know this is one I would future. But you know this is one I would like to see more of. like to see more of. like to see more of. >> This is why to use your word Jake I >> This is why to use your word Jake I >> This is why to use your word Jake I tried to have a more nuanced take is tried to have a more nuanced take is tried to have a more nuanced take is because we have no choice but to take because we have no choice but to take because we have no choice but to take this seriously. Whether it's total this seriously. Whether it's total this seriously. Whether it's total theater, whether it's fear-mongering, theater, whether it's fear-mongering, theater, whether it's fear-mongering, and they do have a pattern around this, and they do have a pattern around this, and they do have a pattern around this, we can't take the risk, right? And it we can't take the risk, right? And it we can't take the risk, right? And it does logically make sense that as these does logically make sense that as these does logically make sense that as these models become more and more capable at models become more and more capable at models become more and more capable at coding, they're going to get better at coding, they're going to get better at coding, they're going to get better at cyber. And there's going to be that one cyber. And there's going to be that one cyber. And there's going to be that one time period where you're moving from time period where you're moving from time period where you're moving from preAI to post AAI, and you need a patch preAI to post AAI, and you need a patch preAI to post AAI, and you need a patch for that. So, my guess is we're going to for that. So, my guess is we're going to for that. So, my guess is we're going to see a lot of patches over the next few see a lot of patches over the next few see a lot of patches over the next few months. I think that that will resolve months. I think that that will resolve months. I think that that will resolve the problem. the problem. the problem. I think this is a case where I'm going I think this is a case where I'm going I think this is a case where I'm going to give them the benefit of the doubt. I to give them the benefit of the doubt. I to give them the benefit of the doubt. I I think that, you know, I've criticized I think that, you know, I've criticized I think that, you know, I've criticized him in the past. I think that blackmail him in the past. I think that blackmail him in the past. I think that blackmail study was embarrassing to the level of study was embarrassing to the level of study was embarrassing to the level of being a hoax, but I think in this case, being a hoax, but I think in this case, being a hoax, but I think in this case, I'm going to give him credit and say I'm going to give him credit and say I'm going to give him credit and say that I think that it's legit. that I think that it's legit. that I think that it's legit. >> So, it's not the anthropic hoax. This >> So, it's not the anthropic hoax. This >> So, it's not the anthropic hoax. This could be legit. I, you know, looking at could be legit. I, you know, looking at could be legit. I, you know, looking at >> we have no choice but to treat it that >> we have no choice but to treat it that >> we have no choice but to treat it that way. way. way. >> Of course. Yeah. I mean, even if two >> Of course. Yeah. I mean, even if two >> Of course. Yeah. I mean, even if two things could be true at the same time, things could be true at the same time, things could be true at the same time, Saxs, they could have used this tactic Saxs, they could have used this tactic Saxs, they could have used this tactic before. It could be performative, like before. It could be performative, like before. It could be performative, like the video with the dramatic music in the the video with the dramatic music in the the video with the dramatic music in the background. It does have a little bit of background. It does have a little bit of background. It does have a little bit of drama to it, and the way they presented drama to it, and the way they presented drama to it, and the way they presented it is very dramatic, but it does make it is very dramatic, but it does make it is very dramatic, but it does make logical sense that the one company that logical sense that the one company that logical sense that the one company that made the bet on code bigger than anybody made the bet on code bigger than anybody made the bet on code bigger than anybody else would be the one who would discover else would be the one who would discover else would be the one who would discover this quickest. And you know in a 100 this quickest. And you know in a 100 this quickest. And you know in a 100 days that's a pretty good um that's a days that's a pretty good um that's a days that's a pretty good um that's a pretty big advantage versus the hackers. pretty big advantage versus the hackers. pretty big advantage versus the hackers. But let me think one more point there But let me think one more point there But let me think one more point there Jimat Jimat Jimat >> the most important thing that people >> the most important thing that people >> the most important thing that people haven't talked about here is the amount haven't talked about here is the amount haven't talked about here is the amount of code being pushed right now because of code being pushed right now because of code being pushed right now because of these tools is 10x 100x in most of these tools is 10x 100x in most of these tools is 10x 100x in most organizations. So we need to have this organizations. So we need to have this organizations. So we need to have this type of security embedded in these new type of security embedded in these new type of security embedded in these new coding tools to do it in real time. coding tools to do it in real time. coding tools to do it in real time. That's the opportunity. There should be That's the opportunity. There should be That's the opportunity. There should be real time correcting of this. If this real time correcting of this. If this real time correcting of this. If this was real, they picked the wrong was real, they picked the wrong was real, they picked the wrong companies. Meaning, there are energy companies. Meaning, there are energy companies. Meaning, there are energy companies, folks that control nuclear companies, folks that control nuclear companies, folks that control nuclear reactors. There are airplane companies reactors. There are airplane companies reactors. There are airplane companies that are flying hundreds of thousands of that are flying hundreds of thousands of that are flying hundreds of thousands of people in essentially manufactured people in essentially manufactured people in essentially manufactured missiles of like streaming gas going at missiles of like streaming gas going at missiles of like streaming gas going at 500 miles an hour. None of those 500 miles an hour. None of those 500 miles an hour. None of those companies were the ones that were companies were the ones that were companies were the ones that were included in this. And so I think if you included in this. And so I think if you included in this. And so I think if you really thought that this was end of really thought that this was end of really thought that this was end of days, days, days, at a minimum we can agree maybe we at a minimum we can agree maybe we at a minimum we can agree maybe we should have expanded the circle a touch. should have expanded the circle a touch. should have expanded the circle a touch. Well, maybe those are customers of the Well, maybe those are customers of the Well, maybe those are customers of the ones they're including here. Anyway, uh ones they're including here. Anyway, uh ones they're including here. Anyway, uh this is a really important story. We'll this is a really important story. We'll this is a really important story. We'll obviously track it in the coming weeks obviously track it in the coming weeks obviously track it in the coming weeks to see what turns out to be reality. And to see what turns out to be reality. And to see what turns out to be reality. And uh Daario, do come on the program at uh Daario, do come on the program at uh Daario, do come on the program at some point. Hey uh Brad, will you get some point. Hey uh Brad, will you get some point. Hey uh Brad, will you get Dario to come on the program? I've Dario to come on the program? I've Dario to come on the program? I've invited him like three times. I got his invited him like three times. I got his invited him like three times. I got his phone number. He's ghosted me. I don't phone number. He's ghosted me. I don't phone number. He's ghosted me. I don't know why. know why. know why. >> Wait, he he's ignored you? I get >> Wait, he he's ignored you? I get >> Wait, he he's ignored you? I get >> I literally got an introduction from the >> I literally got an introduction from the >> I literally got an introduction from the number like one of the number one number like one of the number one number like one of the number one venture capitalists in the world. He's venture capitalists in the world. He's venture capitalists in the world. He's on the cap table very early. He just on the cap table very early. He just on the cap table very early. He just won't respond. I don't know why. won't respond. I don't know why. won't respond. I don't know why. >> I would tell you Daario's podcast with >> I would tell you Daario's podcast with >> I would tell you Daario's podcast with Dwarkish who I think is an excellent Dwarkish who I think is an excellent Dwarkish who I think is an excellent podcaster. I've listened to that three podcaster. I've listened to that three podcaster. I've listened to that three or four times taken notes every time. It or four times taken notes every time. It or four times taken notes every time. It is a really exceptional piece really is a really exceptional piece really is a really exceptional piece really exceptional piece of work by by by them. exceptional piece of work by by by them. exceptional piece of work by by by them. >> All right, let's keep moving. We got a >> All right, let's keep moving. We got a >> All right, let's keep moving. We got a lot on the job. lot on the job. lot on the job. >> You may once again be tarred with your >> You may once again be tarred with your >> You may once again be tarred with your affiliation with us. affiliation with us. affiliation with us. >> Poor you. I mean, I don't care. >> Poor you. I mean, I don't care. >> Poor you. I mean, I don't care. Literally, I I've got friends on both Literally, I I've got friends on both Literally, I I've got friends on both sides of the aisle. I have friends sides of the aisle. I have friends sides of the aisle. I have friends >> of course you do. >> of course you do. >> of course you do. >> Even JCAL. >> Even JCAL. >> Even JCAL. >> Even JCAL has friends everywhere. >> Even JCAL has friends everywhere. >> Even JCAL has friends everywhere. >> Let me ask Brad a question here just >> Let me ask Brad a question here just >> Let me ask Brad a question here just while we're on the topic of anthropic. while we're on the topic of anthropic. while we're on the topic of anthropic. There was a really interesting story or There was a really interesting story or There was a really interesting story or tweet I guess you could say by the tweet I guess you could say by the tweet I guess you could say by the founder of OpenClaw founder of OpenClaw founder of OpenClaw that that that >> Peter. >> Peter. >> Peter. >> Peter. Yeah. What's his name? Peter >> Peter. Yeah. What's his name? Peter >> Peter. Yeah. What's his name? Peter Steinber. Steinber. Steinber. >> Steinberger. Steinberger. >> Steinberger. Steinberger. >> Steinberger. Steinberger. >> Steinberger. Yeah. >> Steinberger. Yeah. >> Steinberger. Yeah. renowned coder created openclaw which is renowned coder created openclaw which is renowned coder created openclaw which is kind of the thing that launched this kind of the thing that launched this kind of the thing that launched this whole agent era now you I guess you whole agent era now you I guess you whole agent era now you I guess you could say any event he said that could say any event he said that could say any event he said that anthropic was cutting off his access to anthropic was cutting off his access to anthropic was cutting off his access to was it was to claw is that the next was it was to claw is that the next was it was to claw is that the next topic topic topic >> this is on the docket it's a little bit >> this is on the docket it's a little bit >> this is on the docket it's a little bit nuanced nuanced nuanced everybody using openclaw would take everybody using openclaw would take everybody using openclaw would take their $200 a month subscription to their $200 a month subscription to their $200 a month subscription to anthropic which was essentially like a anthropic which was essentially like a anthropic which was essentially like a people were using more tokens and it's people were using more tokens and it's people were using more tokens and it's an average the people from openclaw it an average the people from openclaw it an average the people from openclaw it is very verbose and those people are is very verbose and those people are is very verbose and those people are 100x the usage of the average 100x the usage of the average 100x the usage of the average subscriber. So he said you can't use subscriber. So he said you can't use subscriber. So he said you can't use your 200, you have to use the API. You your 200, you have to use the API. You your 200, you have to use the API. You move from the $200 plan to the API, add move from the $200 plan to the API, add move from the $200 plan to the API, add a zero to your token use. So or more. a zero to your token use. So or more. a zero to your token use. So or more. And so they essentially anchored And so they essentially anchored And so they essentially anchored Open Claw and then 10 days later or less Open Claw and then 10 days later or less Open Claw and then 10 days later or less they released or announced their new they released or announced their new they released or announced their new agent technology which is according to agent technology which is according to agent technology which is according to them a safer better version of OpenClaw. them a safer better version of OpenClaw. them a safer better version of OpenClaw. So, hey, all fair in love and war and So, hey, all fair in love and war and So, hey, all fair in love and war and they have basically shot a huge cannon they have basically shot a huge cannon they have basically shot a huge cannon across the bow of openclaw. across the bow of openclaw. across the bow of openclaw. >> Wait, can you just explain that exactly? >> Wait, can you just explain that exactly? >> Wait, can you just explain that exactly? So, so I think you're right that they So, so I think you're right that they So, so I think you're right that they systematically copied feature by feature systematically copied feature by feature systematically copied feature by feature >> of open claw, incorporated that into >> of open claw, incorporated that into >> of open claw, incorporated that into clawed and then the coupross was clawed and then the coupross was clawed and then the coupross was basically cutting off open basically cutting off open basically cutting off open >> oxygen. Can you just explain exactly >> oxygen. Can you just explain exactly >> oxygen. Can you just explain exactly what they did? Okay, very simply, when what they did? Okay, very simply, when what they did? Okay, very simply, when you buy a subscription to these you buy a subscription to these you buy a subscription to these services, they have blended your usage services, they have blended your usage services, they have blended your usage across many users. So there's, you know, across many users. So there's, you know, across many users. So there's, you know, nine out of 10 users use less than the nine out of 10 users use less than the nine out of 10 users use less than the tokens they're paying for and the top tokens they're paying for and the top tokens they're paying for and the top 10% use much more. When OpenClaw became 10% use much more. When OpenClaw became 10% use much more. When OpenClaw became a phenomenon, the number one open source a phenomenon, the number one open source a phenomenon, the number one open source project in history on GitHub with all of project in history on GitHub with all of project in history on GitHub with all of this usage, people went crazy. And you this usage, people went crazy. And you this usage, people went crazy. And you heard me talking about how crazy I went heard me talking about how crazy I went heard me talking about how crazy I went for it. those people with the $200 for it. those people with the $200 for it. those people with the $200 subscriptions were using $2,000 $20,000 subscriptions were using $2,000 $20,000 subscriptions were using $2,000 $20,000 worth of tokens. So they said you can no worth of tokens. So they said you can no worth of tokens. So they said you can no longer use your subscription to, you longer use your subscription to, you longer use your subscription to, you know, either your professional or know, either your professional or know, either your professional or enterprise subscription at $200 enterprise subscription at $200 enterprise subscription at $200 >> and plug that into your open claw. You >> and plug that into your open claw. You >> and plug that into your open claw. You now have to go to the API and pay per now have to go to the API and pay per now have to go to the API and pay per usage. So no more like usage. So no more like usage. So no more like >> unlimited. If you use Anthropic's own >> unlimited. If you use Anthropic's own >> unlimited. If you use Anthropic's own agent harness, are you part of the agent harness, are you part of the agent harness, are you part of the bundled flat rate? You can assume that bundled flat rate? You can assume that bundled flat rate? You can assume that that's what they'll do, which if you that's what they'll do, which if you that's what they'll do, which if you were thinking on an antirust level might were thinking on an antirust level might were thinking on an antirust level might be token dumping or price dumping. I'm be token dumping or price dumping. I'm be token dumping or price dumping. I'm not saying like I'm ratting them. not saying like I'm ratting them. not saying like I'm ratting them. >> No, it's like bundling, isn't it? >> No, it's like bundling, isn't it? >> No, it's like bundling, isn't it? >> Well, price dumping or bundling. When >> Well, price dumping or bundling. When >> Well, price dumping or bundling. When you price something under the market you price something under the market you price something under the market price in antitrust, that would be price price in antitrust, that would be price price in antitrust, that would be price dumping, right? And if you were to dumping, right? And if you were to dumping, right? And if you were to bundle, it would be like the bundling bundle, it would be like the bundling bundle, it would be like the bundling issue. issue. issue. >> Critically important. You can use >> Critically important. You can use >> Critically important. You can use openclaw via claw API and every company openclaw via claw API and every company openclaw via claw API and every company has a right to set the price for its has a right to set the price for its has a right to set the price for its products. It's just saying that you were products. It's just saying that you were products. It's just saying that you were for under their current regime, they for under their current regime, they for under their current regime, they were selling dollars for 10 cents via were selling dollars for 10 cents via were selling dollars for 10 cents via OpenClaw because these were such power OpenClaw because these were such power OpenClaw because these were such power users and now they're just saying we users and now they're just saying we users and now they're just saying we have to price this rationally, but we're have to price this rationally, but we're have to price this rationally, but we're happy to have you guys use the API. So, happy to have you guys use the API. So, happy to have you guys use the API. So, >> okay. Okay. But Brad, when you use the >> okay. Okay. But Brad, when you use the >> okay. Okay. But Brad, when you use the OpenClaw competitor that Anthropic now OpenClaw competitor that Anthropic now OpenClaw competitor that Anthropic now offers, offers, offers, >> correct? >> correct? >> correct? >> Are they subsidizing that? Are you >> Are they subsidizing that? Are you >> Are they subsidizing that? Are you paying? paying? paying? >> We don't know yet because it's in closed >> We don't know yet because it's in closed >> We don't know yet because it's in closed beta. So in other words, what I'm saying beta. So in other words, what I'm saying beta. So in other words, what I'm saying is if they charge for API usage, right, is if they charge for API usage, right, is if they charge for API usage, right, their own first party agent harness or their own first party agent harness or their own first party agent harness or system, then that would be apples to system, then that would be apples to system, then that would be apples to apples. But if apples. But if apples. But if >> if they end up charging the bundled flat >> if they end up charging the bundled flat >> if they end up charging the bundled flat rate, let's say, for their stuff, but rate, let's say, for their stuff, but rate, let's say, for their stuff, but then charge the metered rate for third then charge the metered rate for third then charge the metered rate for third party stuff, you could make a bundling party stuff, you could make a bundling party stuff, you could make a bundling argument. argument. argument. >> Sure. Sure. And you could say it's >> Sure. Sure. And you could say it's >> Sure. Sure. And you could say it's anti-competitive assuming that Anthropic anti-competitive assuming that Anthropic anti-competitive assuming that Anthropic has dominant market share in coding, has dominant market share in coding, has dominant market share in coding, which I think most people would say they which I think most people would say they which I think most people would say they do at this point. do at this point. do at this point. >> And assuming that it's the same product, >> And assuming that it's the same product, >> And assuming that it's the same product, I mean, the reason most enterprises will I mean, the reason most enterprises will I mean, the reason most enterprises will probably use the Anthropic uh version of probably use the Anthropic uh version of probably use the Anthropic uh version of this agentic product is because it meets this agentic product is because it meets this agentic product is because it meets all of your security parameters, right? all of your security parameters, right? all of your security parameters, right? So, Altimter runs, you know, a lot of So, Altimter runs, you know, a lot of So, Altimter runs, you know, a lot of stuff on Enthropic. They're already stuff on Enthropic. They're already stuff on Enthropic. They're already integrated within our our data integrated within our our data integrated within our our data warehouse, our data lake, things of that warehouse, our data lake, things of that warehouse, our data lake, things of that nature. So just letting openclaw loose nature. So just letting openclaw loose nature. So just letting openclaw loose on the uh altimeter you know data set on the uh altimeter you know data set on the uh altimeter you know data set would not be wise and so it's a would not be wise and so it's a would not be wise and so it's a different fundamental product. different fundamental product. different fundamental product. >> No I get that and I think that anthropic >> No I get that and I think that anthropic >> No I get that and I think that anthropic has a huge advantage let's say cloning has a huge advantage let's say cloning has a huge advantage let's say cloning open claw and just building it into open claw and just building it into open claw and just building it into claude. I'm not denying that to me that claude. I'm not denying that to me that claude. I'm not denying that to me that would be the reason why they don't need would be the reason why they don't need would be the reason why they don't need to do price discrimination is because to do price discrimination is because to do price discrimination is because there's already a very good reason there's already a very good reason there's already a very good reason >> to use the let's call it the bundled >> to use the let's call it the bundled >> to use the let's call it the bundled offering on a featured basis. But the offering on a featured basis. But the offering on a featured basis. But the question I'm specifically asking is question I'm specifically asking is question I'm specifically asking is whether they're giving themselves a whether they're giving themselves a whether they're giving themselves a price advantage because price advantage because price advantage because >> I think Brad is giving the the most >> I think Brad is giving the the most >> I think Brad is giving the the most generous interpretation. You're taking a generous interpretation. You're taking a generous interpretation. You're taking a more cynical one. I'm with you, Saxs. more cynical one. I'm with you, Saxs. more cynical one. I'm with you, Saxs. I'm 100% on the cynical side. Open Claw I'm 100% on the cynical side. Open Claw I'm 100% on the cynical side. Open Claw is so powerful. It's got so much is so powerful. It's got so much is so powerful. It's got so much momentum that not only is anthropic momentum that not only is anthropic momentum that not only is anthropic trying to ankle it. I believe when Sam trying to ankle it. I believe when Sam trying to ankle it. I believe when Sam Waltman bought it, it was uh and he Waltman bought it, it was uh and he Waltman bought it, it was uh and he didn't buy OpenClaw itself, he hired didn't buy OpenClaw itself, he hired didn't buy OpenClaw itself, he hired Aqua hired Peter. I believe it was to Aqua hired Peter. I believe it was to Aqua hired Peter. I believe it was to subvert the open- source project to get subvert the open- source project to get subvert the open- source project to get Peter's next set of genius ideas inside Peter's next set of genius ideas inside Peter's next set of genius ideas inside of OpenAI as opposed to letting them go of OpenAI as opposed to letting them go of OpenAI as opposed to letting them go there. People are going to say I'm a there. People are going to say I'm a there. People are going to say I'm a conspiracy theorist, but this is the conspiracy theorist, but this is the conspiracy theorist, but this is the number one focus and let me just give number one focus and let me just give number one focus and let me just give you a list of who is trying to kill you a list of who is trying to kill you a list of who is trying to kill OpenClaw/compete with them. Obviously, OpenClaw/compete with them. Obviously, OpenClaw/compete with them. Obviously, you have Anthropic, but also Perplexity you have Anthropic, but also Perplexity you have Anthropic, but also Perplexity Computer launched. It's awesome. I've Computer launched. It's awesome. I've Computer launched. It's awesome. I've been using it. Anthropic has this clawed been using it. Anthropic has this clawed been using it. Anthropic has this clawed managed agents. They dropped that on managed agents. They dropped that on managed agents. They dropped that on Wednesday, April 8th. uh yesterday uh Wednesday, April 8th. uh yesterday uh Wednesday, April 8th. uh yesterday uh today's Thursday when we tape you you today's Thursday when we tape you you today's Thursday when we tape you you guys listen on Fridays and then you have guys listen on Fridays and then you have guys listen on Fridays and then you have Hermes agent that was released on Hermes agent that was released on Hermes agent that was released on February 25th that's also open source February 25th that's also open source February 25th that's also open source and very good so that's in the open and very good so that's in the open and very good so that's in the open source camp Alibab is coming out with source camp Alibab is coming out with source camp Alibab is coming out with one that's going to be based on their one that's going to be based on their one that's going to be based on their Quinn model then you have Elon who said Quinn model then you have Elon who said Quinn model then you have Elon who said he's got something called rock computer he's got something called rock computer he's got something called rock computer coming out of macro hard which is a play coming out of macro hard which is a play coming out of macro hard which is a play on words for Microsoft in addition to on words for Microsoft in addition to on words for Microsoft in addition to that Amazon and Apple are preparing uh that Amazon and Apple are preparing uh that Amazon and Apple are preparing uh new releases of their uh maxing new releases of their uh maxing new releases of their uh maxing assistants Alexa and Siri that will be assistants Alexa and Siri that will be assistants Alexa and Siri that will be less in this new version and less in this new version and less in this new version and then nothing out of uh SAT and Microsoft then nothing out of uh SAT and Microsoft then nothing out of uh SAT and Microsoft yet. So the number one goal I believe in yet. So the number one goal I believe in yet. So the number one goal I believe in the large language model frontier model the large language model frontier model the large language model frontier model space is to kill this open source space is to kill this open source space is to kill this open source product. product. product. >> No, I mean come on like why they're >> No, I mean come on like why they're >> No, I mean come on like why they're building multi-functioning agents that building multi-functioning agents that building multi-functioning agents that can move from answering questions to can move from answering questions to can move from answering questions to actually doing something for you. like actually doing something for you. like actually doing something for you. like you got to do that because that's what you got to do that because that's what you got to do that because that's what consumers and enterprises wants. It consumers and enterprises wants. It consumers and enterprises wants. It doesn't mean that it's about killing doesn't mean that it's about killing doesn't mean that it's about killing OpenClaw. just this is an obvious thing OpenClaw. just this is an obvious thing OpenClaw. just this is an obvious thing right to do it right to do it right to do it >> but this is a giant movement to stop it >> but this is a giant movement to stop it >> but this is a giant movement to stop it because this is the equivalent of having because this is the equivalent of having because this is the equivalent of having an open-source Android like player in an open-source Android like player in an open-source Android like player in the market and that could be incredibly the market and that could be incredibly the market and that could be incredibly disruptive these I believe open source disruptive these I believe open source disruptive these I believe open source is going to win the day on the large is going to win the day on the large is going to win the day on the large language models and take 90% of the language models and take 90% of the language models and take 90% of the token usage and I think the entire token usage and I think the entire token usage and I think the entire frontier model space could be undercut frontier model space could be undercut frontier model space could be undercut by open source and I think they realize by open source and I think they realize by open source and I think they realize that SLMs the the smaller language that SLMs the the smaller language that SLMs the the smaller language models that are verticalized now that models that are verticalized now that models that are verticalized now that will run on you know, desktops and will run on you know, desktops and will run on you know, desktops and laptops and is even starting to run on laptops and is even starting to run on laptops and is even starting to run on the top ones. That is their biggest the top ones. That is their biggest the top ones. That is their biggest competitive threat and I hope it competitive threat and I hope it competitive threat and I hope it happens. All due respect to your happens. All due respect to your happens. All due respect to your investments, Brad, I think this investments, Brad, I think this investments, Brad, I think this technology and the interface is uh you technology and the interface is uh you technology and the interface is uh you know, he placed bets, but I I think it's know, he placed bets, but I I think it's know, he placed bets, but I I think it's imperative that the agent level, which imperative that the agent level, which imperative that the agent level, which is essentially your entire life, you is essentially your entire life, you is essentially your entire life, you don't give that to Anthropic. You don't don't give that to Anthropic. You don't don't give that to Anthropic. You don't give that to OpenAI. That's your entire give that to OpenAI. That's your entire give that to OpenAI. That's your entire business, your entire life. It is business, your entire life. It is business, your entire life. It is foolish for you, Brad, to give your foolish for you, Brad, to give your foolish for you, Brad, to give your entire business and all the knowledge entire business and all the knowledge entire business and all the knowledge you have to anthropic through that. you have to anthropic through that. you have to anthropic through that. unless you're just doing it to boost unless you're just doing it to boost unless you're just doing it to boost your um your your investment in those your um your your investment in those your um your your investment in those companies. But I would be very concerned companies. But I would be very concerned companies. But I would be very concerned if I was you with putting all of your if I was you with putting all of your if I was you with putting all of your knowledge that you've earned over a knowledge that you've earned over a knowledge that you've earned over a lifetime into any of these large lifetime into any of these large lifetime into any of these large language models. language models. language models. >> All right, Jake, let me ask you. Can I >> All right, Jake, let me ask you. Can I >> All right, Jake, let me ask you. Can I ask a question? Thank you for that ask a question? Thank you for that ask a question? Thank you for that impassioned monologue. Um actually, I impassioned monologue. Um actually, I impassioned monologue. Um actually, I want to ask my TED talk. want to ask my TED talk. want to ask my TED talk. >> I Yes, thank you for that TED talk. Um I >> I Yes, thank you for that TED talk. Um I >> I Yes, thank you for that TED talk. Um I have a yes no question for each of you. have a yes no question for each of you. have a yes no question for each of you. >> Do you believe that anthropic has >> Do you believe that anthropic has >> Do you believe that anthropic has dominant market share in coding? right dominant market share in coding? right dominant market share in coding? right now? Yes. No, now? Yes. No, now? Yes. No, >> no. >> no. >> no. >> In in coding, >> In in coding, >> In in coding, >> yes, >> yes, >> yes, >> they had the lead, but not that they had >> they had the lead, but not that they had >> they had the lead, but not that they had the lead, but not dominating. the lead, but not dominating. the lead, but not dominating. >> I think it's a trillion dollar market, >> I think it's a trillion dollar market, >> I think it's a trillion dollar market, and these guys have less than 10% of it and these guys have less than 10% of it and these guys have less than 10% of it today. So, it's hard to make a case that today. So, it's hard to make a case that today. So, it's hard to make a case that >> What percent of coding tokens do you >> What percent of coding tokens do you >> What percent of coding tokens do you think that anthropic is providing the think that anthropic is providing the think that anthropic is providing the market right now? market right now? market right now? >> Greater than 50%. >> Greater than 50%. >> Greater than 50%. >> Yeah, that's true. >> Yeah, that's true. >> Yeah, that's true. >> Okay, that's called dominant market >> Okay, that's called dominant market >> Okay, that's called dominant market share. share. share. >> Uh, I don't know about that. >> Uh, I don't know about that. >> Uh, I don't know about that. >> More than 50% of the market. >> More than 50% of the market. >> More than 50% of the market. >> You got to look at what you got to look >> You got to look at what you got to look >> You got to look at what you got to look at what the TAM is. at what the TAM is. at what the TAM is. with the Tan, with the Tan, with the Tan, >> right? There are a lot of people who >> right? There are a lot of people who >> right? There are a lot of people who provide, you know, that that are in this provide, you know, that that are in this provide, you know, that that are in this tiebreaker before we move on to the tiebreaker before we move on to the tiebreaker before we move on to the next. next. next. >> I'm not saying it's a permanent >> I'm not saying it's a permanent >> I'm not saying it's a permanent condition, condition, condition, >> but if you're telling me that today >> but if you're telling me that today >> but if you're telling me that today >> Anthropic is delivering over half of the >> Anthropic is delivering over half of the >> Anthropic is delivering over half of the coding tokens, that's clearly a dominant coding tokens, that's clearly a dominant coding tokens, that's clearly a dominant position in the market for coding. It's position in the market for coding. It's position in the market for coding. It's an early market. It could change, but an early market. It could change, but an early market. It could change, but >> if I were representing them, David, I >> if I were representing them, David, I >> if I were representing them, David, I would say nine months ago, everybody t would say nine months ago, everybody t would say nine months ago, everybody t called us uh, you know, out of the game. called us uh, you know, out of the game. called us uh, you know, out of the game. We were being destroyed by open AI in We were being destroyed by open AI in We were being destroyed by open AI in three months. Now people are saying we three months. Now people are saying we three months. Now people are saying we have dominant market position. This is have dominant market position. This is have dominant market position. This is the fastest changing most competitive the fastest changing most competitive the fastest changing most competitive market in the world. I think it would be market in the world. I think it would be market in the world. I think it would be very hardressed to walk into, you know, very hardressed to walk into, you know, very hardressed to walk into, you know, some district court make the case that some district court make the case that some district court make the case that these guys have somehow already formed a these guys have somehow already formed a these guys have somehow already formed a monopoly against Amazon, Google, monopoly against Amazon, Google, monopoly against Amazon, Google, Microsoft, Open AI, etc. Microsoft, Open AI, etc. Microsoft, Open AI, etc. >> Well, I'm not saying it's a it's already >> Well, I'm not saying it's a it's already >> Well, I'm not saying it's a it's already a permanent monopoly, but I am just a permanent monopoly, but I am just a permanent monopoly, but I am just asking about market share. And I do asking about market share. And I do asking about market share. And I do think you guys all agree that think you guys all agree that think you guys all agree that >> Shimov, go ahead. >> Shimov, go ahead. >> Shimov, go ahead. >> They probably have 50 to 60% market >> They probably have 50 to 60% market >> They probably have 50 to 60% market share because I think codeex is actually share because I think codeex is actually share because I think codeex is actually quite broadly used as well. quite broadly used as well. quite broadly used as well. >> But that belies the more important point >> But that belies the more important point >> But that belies the more important point which is AI enabled coding I think is which is AI enabled coding I think is which is AI enabled coding I think is still 5% of the broad market. So it's still 5% of the broad market. So it's still 5% of the broad market. So it's kind of a nothing burger. Yes, they're kind of a nothing burger. Yes, they're kind of a nothing burger. Yes, they're leading but they're leading in something leading but they're leading in something leading but they're leading in something that isn't that big yet. Now you would that isn't that big yet. Now you would that isn't that big yet. Now you would say how could it not be big? And what I say how could it not be big? And what I say how could it not be big? And what I would say is because most of the stuff would say is because most of the stuff would say is because most of the stuff that's being written is still white that's being written is still white that's being written is still white sheet denovo code. And I think the ugly sheet denovo code. And I think the ugly sheet denovo code. And I think the ugly truth is I don't care what model you truth is I don't care what model you truth is I don't care what model you have, but the long horizon ability for have, but the long horizon ability for have, but the long horizon ability for any of these models to actually build any of these models to actually build any of these models to actually build enterprisegrade software is still enterprisegrade software is still enterprisegrade software is still shiit And that's the actual lived shiit And that's the actual lived shiit And that's the actual lived experience. Not for me, but when I call experience. Not for me, but when I call experience. Not for me, but when I call on our customers, half a trillion dollar on our customers, half a trillion dollar on our customers, half a trillion dollar banks, hundred billion dollar insurance banks, hundred billion dollar insurance banks, hundred billion dollar insurance companies, none of these guys are like, companies, none of these guys are like, companies, none of these guys are like, "Wow, it just works out of the box." It "Wow, it just works out of the box." It "Wow, it just works out of the box." It doesn't work. So, most of it is still doesn't work. So, most of it is still doesn't work. So, most of it is still handtuned. So, until I can honestly tell handtuned. So, until I can honestly tell handtuned. So, until I can honestly tell you that we can point a model at this you that we can point a model at this you that we can point a model at this with the right guard rails, which I with the right guard rails, which I with the right guard rails, which I can't today, what I would say is it's a can't today, what I would say is it's a can't today, what I would say is it's a small market that will become large as small market that will become large as small market that will become large as these models become better. these models become better. these models become better. But we are in the world where we have 50 But we are in the world where we have 50 But we are in the world where we have 50 years of accumulated tech debt as a years of accumulated tech debt as a years of accumulated tech debt as a world. And I suspect when you enumerate world. And I suspect when you enumerate world. And I suspect when you enumerate the number of lines that that the number of lines that that the number of lines that that represents, it's hundreds of trillions represents, it's hundreds of trillions represents, it's hundreds of trillions of lines of just pretty marginal of lines of just pretty marginal of lines of just pretty marginal mediocre code to bad code. On top of mediocre code to bad code. On top of mediocre code to bad code. On top of that, we have all these legacy that, we have all these legacy that, we have all these legacy languages. I'll tell you one of our languages. I'll tell you one of our languages. I'll tell you one of our customers, they have to go and get customers, they have to go and get customers, they have to go and get 60year-old pensioners to come into the 60year-old pensioners to come into the 60year-old pensioners to come into the office to interpret cope. No, I'm not office to interpret cope. No, I'm not office to interpret cope. No, I'm not joking. This is a joking. This is a joking. This is a >> snowball for trend. >> snowball for trend. >> snowball for trend. >> This is a hundred billion dollar a year >> This is a hundred billion dollar a year >> This is a hundred billion dollar a year revenue company and that's how they revenue company and that's how they revenue company and that's how they solve these problems. It's not opus just solve these problems. It's not opus just solve these problems. It's not opus just solves it. So I I would just keep in solves it. So I I would just keep in solves it. So I I would just keep in mind that most of the tech debt in the mind that most of the tech debt in the mind that most of the tech debt in the world that exists 99% of it is still world that exists 99% of it is still world that exists 99% of it is still poorly addressed by these models. We are poorly addressed by these models. We are poorly addressed by these models. We are untying this Gordian knot. It's going to untying this Gordian knot. It's going to untying this Gordian knot. It's going to take decades to do it right. So all the take decades to do it right. So all the take decades to do it right. So all the breathlessness about all this other breathlessness about all this other breathlessness about all this other stuff, I really think it's not where the stuff, I really think it's not where the stuff, I really think it's not where the money is. It's not the big time stuff. money is. It's not the big time stuff. money is. It's not the big time stuff. And you can tell me, "Oh yeah, it's And you can tell me, "Oh yeah, it's And you can tell me, "Oh yeah, it's going to be the future." And I would going to be the future." And I would going to be the future." And I would say, "Tell this business that's a say, "Tell this business that's a say, "Tell this business that's a hundred billion dollars a year of hundred billion dollars a year of hundred billion dollars a year of revenue and 50 million billing revenue and 50 million billing revenue and 50 million billing relationships that all of a sudden relationships that all of a sudden relationships that all of a sudden you're going to open claw your way to a you're going to open claw your way to a you're going to open claw your way to a solution." It's Not to say solution." It's Not to say solution." It's Not to say that you can't have a great chief of that you can't have a great chief of that you can't have a great chief of staff, and not to say you can't do some staff, and not to say you can't do some staff, and not to say you can't do some useful stuff and trickery and, you know, useful stuff and trickery and, you know, useful stuff and trickery and, you know, have a good knowledge base. I'd like have a good knowledge base. I'd like have a good knowledge base. I'd like that, too. But the core things that your that, too. But the core things that your that, too. But the core things that your lived experience sits on today is a mess lived experience sits on today is a mess lived experience sits on today is a mess of tech debt that will get very slowly of tech debt that will get very slowly of tech debt that will get very slowly replaced. And that's just the reality of replaced. And that's just the reality of replaced. And that's just the reality of life. life. life. >> And there are competitors that are >> And there are competitors that are >> And there are competitors that are extremely disruptive. I'll tell you extremely disruptive. I'll tell you extremely disruptive. I'll tell you about one. We talked about Bit Tensor about one. We talked about Bit Tensor about one. We talked about Bit Tensor Tao on this program a couple weeks ago Tao on this program a couple weeks ago Tao on this program a couple weeks ago when we had the um Jensen interview. You when we had the um Jensen interview. You when we had the um Jensen interview. You brought it up actually Chimath. There's brought it up actually Chimath. There's brought it up actually Chimath. There's a there's a project that's subnet 62. a there's a project that's subnet 62. a there's a project that's subnet 62. It's called Ridges AI. And what they're It's called Ridges AI. And what they're It's called Ridges AI. And what they're doing is a competitor that is not only doing is a competitor that is not only doing is a competitor that is not only open- source but anybody can contribute open- source but anybody can contribute open- source but anybody can contribute to it. They spent about a million to it. They spent about a million to it. They spent about a million dollars in tow like rewards and in 45 dollars in tow like rewards and in 45 dollars in tow like rewards and in 45 days they hit 80% of what Claude 4 is days they hit 80% of what Claude 4 is days they hit 80% of what Claude 4 is and they did that in under 45 days. The and they did that in under 45 days. The and they did that in under 45 days. The way that works is they give rewards for way that works is they give rewards for way that works is they give rewards for people who and they can do this people who and they can do this people who and they can do this anonymously make that coding product anonymously make that coding product anonymously make that coding product which is like codeex or claude code which is like codeex or claude code which is like codeex or claude code better. that flywheel is racing right better. that flywheel is racing right better. that flywheel is racing right now with participation in the same way now with participation in the same way now with participation in the same way Bitcoin is. So you're going to see a lot Bitcoin is. So you're going to see a lot Bitcoin is. So you're going to see a lot of open- source and these crypto of open- source and these crypto of open- source and these crypto open-source combinations and uh anybody open-source combinations and uh anybody open-source combinations and uh anybody who's not investigated this, I highly who's not investigated this, I highly who's not investigated this, I highly recommend you investigate this. recommend you investigate this. recommend you investigate this. >> I do think you're right about one >> I do think you're right about one >> I do think you're right about one specific thing. I would put zero, specific thing. I would put zero, specific thing. I would put zero, literally the probability zero of any literally the probability zero of any literally the probability zero of any important company worth anything more important company worth anything more important company worth anything more than a dollar having and outsourcing than a dollar having and outsourcing than a dollar having and outsourcing their production code to an open source their production code to an open source their production code to an open source project. That'll never happen. However, project. That'll never happen. However, project. That'll never happen. However, what will happen though is when you look what will happen though is when you look what will happen though is when you look at the cost of training this 10 trillion at the cost of training this 10 trillion at the cost of training this 10 trillion parameter model on Blackwell and when parameter model on Blackwell and when parameter model on Blackwell and when you look in the future let's just say in you look in the future let's just say in you look in the future let's just say in six or nine months that a 15 or 20 six or nine months that a 15 or 20 six or nine months that a 15 or 20 trillion perm model is going to get trillion perm model is going to get trillion perm model is going to get trained on Vera Rubin I think Jason trained on Vera Rubin I think Jason trained on Vera Rubin I think Jason where you are right I have zero and just where you are right I have zero and just where you are right I have zero and just to be clear I have no investments in to be clear I have no investments in to be clear I have no investments in this at all I'm this at all I'm this at all I'm >> to be so super clear >> to be so super clear >> to be so super clear >> I'm just observing because another >> I'm just observing because another >> I'm just observing because another project other than Bit Tensor that project other than Bit Tensor that project other than Bit Tensor that someone brought up to me is Venice. The someone brought up to me is Venice. The someone brought up to me is Venice. The concept of opensource training and concept of opensource training and concept of opensource training and orchestration orchestration orchestration is a hugely disruptive idea which is the is a hugely disruptive idea which is the is a hugely disruptive idea which is the complete orthogonal attack vector to complete orthogonal attack vector to complete orthogonal attack vector to this idea that you have to raise tens this idea that you have to raise tens this idea that you have to raise tens and tens of billions of dollars to train and tens of billions of dollars to train and tens of billions of dollars to train your models because if the capital your models because if the capital your models because if the capital markets run out of 10 and 20 billion markets run out of 10 and 20 billion markets run out of 10 and 20 billion dollar checks to give people the only dollar checks to give people the only dollar checks to give people the only solution is to be totally distributed. I solution is to be totally distributed. I solution is to be totally distributed. I tend to agree with you Jason that there tend to agree with you Jason that there tend to agree with you Jason that there is going to be at some point a very is going to be at some point a very is going to be at some point a very successful open source project for successful open source project for successful open source project for pre-training. pre-training. pre-training. Absolutely. Will there never ever be an Absolutely. Will there never ever be an Absolutely. Will there never ever be an open- source way where a real company open- source way where a real company open- source way where a real company that has any skin in the game says here that has any skin in the game says here that has any skin in the game says here guys re-engineer my codebase as an open guys re-engineer my codebase as an open guys re-engineer my codebase as an open source project. Never going to happen. source project. Never going to happen. source project. Never going to happen. >> Yeah, I I think the coding tools will. >> Yeah, I I think the coding tools will. >> Yeah, I I think the coding tools will. And if you look at the history of open And if you look at the history of open And if you look at the history of open source, Brad, you actually I think had a source, Brad, you actually I think had a source, Brad, you actually I think had a lot of bets in this space. Linux, lot of bets in this space. Linux, lot of bets in this space. Linux, Kubernetes, Apache, Postgress, like Kubernetes, Apache, Postgress, like Kubernetes, Apache, Postgress, like Terraform, like these open source Terraform, like these open source Terraform, like these open source projects are deep inside of enterprises. projects are deep inside of enterprises. projects are deep inside of enterprises. Deep. And we're sitting here 15, 20 Deep. And we're sitting here 15, 20 Deep. And we're sitting here 15, 20 years ago, the same argument was made. years ago, the same argument was made. years ago, the same argument was made. Nobody will ever adopt these inside the Nobody will ever adopt these inside the Nobody will ever adopt these inside the enterprise. You got to go with Oracle, enterprise. You got to go with Oracle, enterprise. You got to go with Oracle, whatever. And fair enough, many people whatever. And fair enough, many people whatever. And fair enough, many people do. But I think this is this $29 ridges do. But I think this is this $29 ridges do. But I think this is this $29 ridges um subscription to do this versus 200. um subscription to do this versus 200. um subscription to do this versus 200. It's starting to take hold inside of It's starting to take hold inside of It's starting to take hold inside of startups. And that's where I always look startups. And that's where I always look startups. And that's where I always look at the tip of the spear. Startups love at the tip of the spear. Startups love at the tip of the spear. Startups love to, you know, use open source products. to, you know, use open source products. to, you know, use open source products. I think this could be the next big I think this could be the next big I think this could be the next big thing. But listen, I I I invest in thing. But listen, I I I invest in thing. But listen, I I I invest in things that have a 90% chance of going things that have a 90% chance of going things that have a 90% chance of going to zero. So do your own research. No to zero. So do your own research. No to zero. So do your own research. No crying in the casino. crying in the casino. crying in the casino. >> Can I just make a a final few points? So >> Can I just make a a final few points? So >> Can I just make a a final few points? So just just quickly so number one is with just just quickly so number one is with just just quickly so number one is with respect to this market for code or code respect to this market for code or code respect to this market for code or code tokens whatever you want to call it tokens whatever you want to call it tokens whatever you want to call it >> it might be 5% today meaning 5% of the >> it might be 5% today meaning 5% of the >> it might be 5% today meaning 5% of the codes AI generated versus human codes AI generated versus human codes AI generated versus human generated I think it's going to 95% I generated I think it's going to 95% I generated I think it's going to 95% I mean I bet any amount of money on that mean I bet any amount of money on that mean I bet any amount of money on that the only question is when probably over the only question is when probably over the only question is when probably over the next few years so that's point the next few years so that's point the next few years so that's point number one point number two is it's number one point number two is it's number one point number two is it's possible that if you're the early leader possible that if you're the early leader possible that if you're the early leader in coding as a AI model company let's in coding as a AI model company let's in coding as a AI model company let's say you have 50 to 60% of market share. say you have 50 to 60% of market share. say you have 50 to 60% of market share. You have the most developers using it. You have the most developers using it. You have the most developers using it. Therefore, you have the most access to Therefore, you have the most access to Therefore, you have the most access to code bases. You might get the most code bases. You might get the most code bases. You might get the most training tokens. There is a potential training tokens. There is a potential training tokens. There is a potential flywheel there where you can see the flywheel there where you can see the flywheel there where you can see the early market leader consolidating its early market leader consolidating its early market leader consolidating its lead because it's generating the most lead because it's generating the most lead because it's generating the most code tokens and it's getting access to code tokens and it's getting access to code tokens and it's getting access to the most existing code. Now, I'm not the most existing code. Now, I'm not the most existing code. Now, I'm not saying for sure that's going to happen. saying for sure that's going to happen. saying for sure that's going to happen. is possible that the other guys catch is possible that the other guys catch is possible that the other guys catch up, but I think there is a possibility up, but I think there is a possibility up, but I think there is a possibility of a flywheel there and strong, I guess of a flywheel there and strong, I guess of a flywheel there and strong, I guess you'd call it data scale effects, things you'd call it data scale effects, things you'd call it data scale effects, things like that. So, I do believe that the like that. So, I do believe that the like that. So, I do believe that the market for coding tokens could be market for coding tokens could be market for coding tokens could be monopolized. Third, Anthropic's revenue monopolized. Third, Anthropic's revenue monopolized. Third, Anthropic's revenue run rate, as based on what I can tell run rate, as based on what I can tell run rate, as based on what I can tell and what's been publicly released, is and what's been publicly released, is and what's been publicly released, is the fastest growing revenue run rate at the fastest growing revenue run rate at the fastest growing revenue run rate at scale that I think we've ever seen. Uh, scale that I think we've ever seen. Uh, scale that I think we've ever seen. Uh, we we we >> perfect segue. It's the next story. >> perfect segue. It's the next story. >> perfect segue. It's the next story. Okay, maybe Okay, maybe Okay, maybe >> pull up the the tweets. But this thing >> pull up the the tweets. But this thing >> pull up the the tweets. But this thing is ramping at a rate we've never seen is ramping at a rate we've never seen is ramping at a rate we've never seen before. before. before. >> We can get into that in a second. But >> We can get into that in a second. But >> We can get into that in a second. But just one last final point just one last final point just one last final point >> is I think it's pretty clear that where >> is I think it's pretty clear that where >> is I think it's pretty clear that where we go from here is agents and coding we go from here is agents and coding we go from here is agents and coding gives you a huge step up on agents gives you a huge step up on agents gives you a huge step up on agents because you know one of the main things because you know one of the main things because you know one of the main things that agents need to do is is write code that agents need to do is is write code that agents need to do is is write code to be able to enable them to complete to be able to enable them to complete to be able to enable them to complete tasks. tasks. tasks. >> Correct. And so if it is the case that >> Correct. And so if it is the case that >> Correct. And so if it is the case that coding is this huge market that's going coding is this huge market that's going coding is this huge market that's going to be dominated by one or two companies to be dominated by one or two companies to be dominated by one or two companies and then that leads to another huge and then that leads to another huge and then that leads to another huge market which is agents. My point is just market which is agents. My point is just market which is agents. My point is just I think all these companies need to I think all these companies need to I think all these companies need to behave in a very clean way behave in a very clean way behave in a very clean way >> and not engage in tactics that later the >> and not engage in tactics that later the >> and not engage in tactics that later the government might say you know what that government might say you know what that government might say you know what that was anti-competitive. Everyone should was anti-competitive. Everyone should was anti-competitive. Everyone should just I think play fair. Do not engage in just I think play fair. Do not engage in just I think play fair. Do not engage in discrimination against other people's discrimination against other people's discrimination against other people's products. engage in fair pricing. I'm products. engage in fair pricing. I'm products. engage in fair pricing. I'm not accusing anyone of breaking any of not accusing anyone of breaking any of not accusing anyone of breaking any of the rules, but what I'm saying is that the rules, but what I'm saying is that the rules, but what I'm saying is that eventually the government's going to eventually the government's going to eventually the government's going to look at this market with the benefit of look at this market with the benefit of look at this market with the benefit of 2020 hindsight and I think everyone 2020 hindsight and I think everyone 2020 hindsight and I think everyone should just basically, you know, keep it should just basically, you know, keep it should just basically, you know, keep it >> keep your nose clean. >> keep your nose clean. >> keep your nose clean. >> Keep it tight. Keep it tight. >> Keep it tight. Keep it tight. >> Keep it tight. Keep it tight. >> Keep it tight. Tight is right. I think >> Keep it tight. Tight is right. I think >> Keep it tight. Tight is right. I think is an excellent point. Let's talk about is an excellent point. Let's talk about is an excellent point. Let's talk about the revenue ramp of Anthropic. This is the revenue ramp of Anthropic. This is the revenue ramp of Anthropic. This is just unprecedented. Anthropic's revenue just unprecedented. Anthropic's revenue just unprecedented. Anthropic's revenue run rate has topped 30 billion with a B. run rate has topped 30 billion with a B. run rate has topped 30 billion with a B. Early 2023, they turned on revenue. They Early 2023, they turned on revenue. They Early 2023, they turned on revenue. They started charging for API access. End of started charging for API access. End of started charging for API access. End of 2024, they're at a billion dollar run 2024, they're at a billion dollar run 2024, they're at a billion dollar run rate. February 25, they launched Claw rate. February 25, they launched Claw rate. February 25, they launched Claw Code. That was the starter pistol. Mid Code. That was the starter pistol. Mid Code. That was the starter pistol. Mid 2025, $4 billion run rate. End of 2025, 2025, $4 billion run rate. End of 2025, 2025, $4 billion run rate. End of 2025, $9 billion run rate. Just a couple of $9 billion run rate. Just a couple of $9 billion run rate. Just a couple of months later in April, $30 billion run months later in April, $30 billion run months later in April, $30 billion run rate. Yes, that's right. Triple. Uh and rate. Yes, that's right. Triple. Uh and rate. Yes, that's right. Triple. Uh and the way they did this is enterprise uh the way they did this is enterprise uh the way they did this is enterprise uh customers are a major part of the spend. customers are a major part of the spend. customers are a major part of the spend. Dario announced a couple of months ago Dario announced a couple of months ago Dario announced a couple of months ago that there's over a thousand enterprises that there's over a thousand enterprises that there's over a thousand enterprises paying over 1 million annually. This is paying over 1 million annually. This is paying over 1 million annually. This is truly mindboggling when you think about truly mindboggling when you think about truly mindboggling when you think about it because those are the most coveted it because those are the most coveted it because those are the most coveted customers in the world. These are the customers in the world. These are the customers in the world. These are the big fish that you just uh when people big fish that you just uh when people big fish that you just uh when people are running enterprise software, they are running enterprise software, they are running enterprise software, they they dream Slack dreamed of getting they dream Slack dreamed of getting they dream Slack dreamed of getting these million-dollar customers. Uh these million-dollar customers. Uh these million-dollar customers. Uh Salesforce dreams of getting these Salesforce dreams of getting these Salesforce dreams of getting these million-dollar customers. Brad, you're million-dollar customers. Brad, you're million-dollar customers. Brad, you're an investor. I guess uh Sam famously on an investor. I guess uh Sam famously on an investor. I guess uh Sam famously on BG2 asked you to sell your uh OpenAI BG2 asked you to sell your uh OpenAI BG2 asked you to sell your uh OpenAI stock back to him. You didn't. You stock back to him. You didn't. You stock back to him. You didn't. You demired, but you're an investor in both. demired, but you're an investor in both. demired, but you're an investor in both. How shocking is it to you to place both How shocking is it to you to place both How shocking is it to you to place both of those bets and then see one of them of those bets and then see one of them of those bets and then see one of them come from so far behind? You know, Chat come from so far behind? You know, Chat come from so far behind? You know, Chat GPT has 900 million users. I don't know GPT has 900 million users. I don't know GPT has 900 million users. I don't know if they've they've passed a billion if they've they've passed a billion if they've they've passed a billion officially yet, but they are the Verb, officially yet, but they are the Verb, officially yet, but they are the Verb, right? They're the Uber. They're the right? They're the Uber. They're the right? They're the Uber. They're the Xerox. They're the Polaroid of AI, but Xerox. They're the Polaroid of AI, but Xerox. They're the Polaroid of AI, but they didn't go after the enterprise. they didn't go after the enterprise. they didn't go after the enterprise. Daario made that and Daario worked. He Daario made that and Daario worked. He Daario made that and Daario worked. He was the co-founder of OpenAI. He left was the co-founder of OpenAI. He left was the co-founder of OpenAI. He left and according to the New Yorker story and according to the New Yorker story and according to the New Yorker story that came out from Ronan Farrell this that came out from Ronan Farrell this that came out from Ronan Farrell this week, he was basically left because of week, he was basically left because of week, he was basically left because of his disgust in working with Sam Alman. his disgust in working with Sam Alman. his disgust in working with Sam Alman. Your thoughts? Your thoughts? Your thoughts? >> Well, you know, before we go down the >> Well, you know, before we go down the >> Well, you know, before we go down the OpenAI rabbit hole, let's just really OpenAI rabbit hole, let's just really OpenAI rabbit hole, let's just really contextualize like what's going on here. contextualize like what's going on here. contextualize like what's going on here. You know, check I I I have this You know, check I I I have this You know, check I I I have this additional chart. you showed one, you additional chart. you showed one, you additional chart. you showed one, you know, they added 4 billion of revenue in know, they added 4 billion of revenue in know, they added 4 billion of revenue in January, 7 billion in February, 11 January, 7 billion in February, 11 January, 7 billion in February, 11 billion of annualized run rates, um, or billion of annualized run rates, um, or billion of annualized run rates, um, or 10 or 11 billion in March, just to put 10 or 11 billion in March, just to put 10 or 11 billion in March, just to put in perspective, that's data bricks plus in perspective, that's data bricks plus in perspective, that's data bricks plus Palanteer combined that they added in a Palanteer combined that they added in a Palanteer combined that they added in a single month, right? So we started with single month, right? So we started with single month, right? So we started with everybody at the start of the year everybody at the start of the year everybody at the start of the year ringing their hands including you know ringing their hands including you know ringing their hands including you know Gurley and others saying we're in a big Gurley and others saying we're in a big Gurley and others saying we're in a big bubble asking whether the AI revenues bubble asking whether the AI revenues bubble asking whether the AI revenues would show up to justify all of this would show up to justify all of this would show up to justify all of this investment and bam you have the largest investment and bam you have the largest investment and bam you have the largest revenue explosion in the history of revenue explosion in the history of revenue explosion in the history of technology. So the company's plans were technology. So the company's plans were technology. So the company's plans were to end the year at about a $30 billion to end the year at about a $30 billion to end the year at about a $30 billion ex exit run rate. They got there by the ex exit run rate. They got there by the ex exit run rate. They got there by the end of March right and I suspect that end of March right and I suspect that end of March right and I suspect that it's continuing in April. So you have to it's continuing in April. So you have to it's continuing in April. So you have to ask what's going on and what's the big ask what's going on and what's the big ask what's going on and what's the big so what the first thing for me is that so what the first thing for me is that so what the first thing for me is that model and product capability just hit model and product capability just hit model and product capability just hit this threshold we talked about earlier this threshold we talked about earlier this threshold we talked about earlier near AGI whatever the hell you want to near AGI whatever the hell you want to near AGI whatever the hell you want to call it and everybody like alimter said call it and everybody like alimter said call it and everybody like alimter said damn this is so good I have to have it damn this is so good I have to have it damn this is so good I have to have it this is no longer about my IT budget this is no longer about my IT budget this is no longer about my IT budget this is about labor augmentation and this is about labor augmentation and this is about labor augmentation and labor replacement and by the way co-work labor replacement and by the way co-work labor replacement and by the way co-work is growing even faster than Claude go at is growing even faster than Claude go at is growing even faster than Claude go at the same stage of development the same stage of development the same stage of development So what it showed is we have a near So what it showed is we have a near So what it showed is we have a near infinite TAM. It turns out that the TAM infinite TAM. It turns out that the TAM infinite TAM. It turns out that the TAM for intelligence is radically different for intelligence is radically different for intelligence is radically different than anything that we've seen before. than anything that we've seen before. than anything that we've seen before. And I think the best example of this, And I think the best example of this, And I think the best example of this, right? This is millions of right? This is millions of right? This is millions of self-interested parties, consumers, self-interested parties, consumers, self-interested parties, consumers, enterprises, a thousand now over a enterprises, a thousand now over a enterprises, a thousand now over a million dollars. Right? It's not that million dollars. Right? It's not that million dollars. Right? It's not that there was some great go to market and there was some great go to market and there was some great go to market and anthropic that all of a sudden, you anthropic that all of a sudden, you anthropic that all of a sudden, you know, they snuck up and blew everybody know, they snuck up and blew everybody know, they snuck up and blew everybody away. No, it was companies demanding the away. No, it was companies demanding the away. No, it was companies demanding the product. They're getting throttled on product. They're getting throttled on product. They're getting throttled on the product. Why? Because it's so good. the product. Why? Because it's so good. the product. Why? Because it's so good. It makes them better at their business. It makes them better at their business. It makes them better at their business. We are all self-interested actors. And We are all self-interested actors. And We are all self-interested actors. And when millions of those people are all when millions of those people are all when millions of those people are all making the same decision, there's a huge making the same decision, there's a huge making the same decision, there's a huge tell. And the tell here is that the TAM tell. And the tell here is that the TAM tell. And the tell here is that the TAM is as big as Daario and Sam and others is as big as Daario and Sam and others is as big as Daario and Sam and others have been saying. We knew intelligence have been saying. We knew intelligence have been saying. We knew intelligence was going to scale on the exponential. was going to scale on the exponential. was going to scale on the exponential. The question was whether revenue will The question was whether revenue will The question was whether revenue will scale on the exponential, and that's scale on the exponential, and that's scale on the exponential, and that's what we're seeing. And remember, they're what we're seeing. And remember, they're what we're seeing. And remember, they're doing this with only 1 1/2 to 2 gawatt doing this with only 1 1/2 to 2 gawatt doing this with only 1 1/2 to 2 gawatt of compute, right? These guys are of compute, right? These guys are of compute, right? These guys are massively compute constrained. They're massively compute constrained. They're massively compute constrained. They're each going to be adding 3 GW of compute each going to be adding 3 GW of compute each going to be adding 3 GW of compute this year. And so that will unlock they this year. And so that will unlock they this year. And so that will unlock they would be growing even faster. But for would be growing even faster. But for would be growing even faster. But for that, and then Jason, to your point that, and then Jason, to your point that, and then Jason, to your point about the open source models that we all about the open source models that we all about the open source models that we all want to be a part of this solution, I've want to be a part of this solution, I've want to be a part of this solution, I've talked to a lot of big companies, 65 to talked to a lot of big companies, 65 to talked to a lot of big companies, 65 to 70% of their token consumption is 70% of their token consumption is 70% of their token consumption is open-source model, right? are these open-source model, right? are these open-source model, right? are these cheap Chinese and other tokens. So these cheap Chinese and other tokens. So these cheap Chinese and other tokens. So these revenue ramps are happening while the revenue ramps are happening while the revenue ramps are happening while the world is already using open source. This world is already using open source. This world is already using open source. This is not frontier only. This is Frontier is not frontier only. This is Frontier is not frontier only. This is Frontier plus open source. We're going to see plus open source. We're going to see plus open source. We're going to see massive token optimization over the massive token optimization over the massive token optimization over the course of the year. But what happens on course of the year. But what happens on course of the year. But what happens on this Jebans paradox is the co the unit this Jebans paradox is the co the unit this Jebans paradox is the co the unit costs right of intelligence is costs right of intelligence is costs right of intelligence is plummeting. Not the cost of tokens. The plummeting. Not the cost of tokens. The plummeting. Not the cost of tokens. The unit cost of intelligence is plummeting unit cost of intelligence is plummeting unit cost of intelligence is plummeting because the capabilities of these models because the capabilities of these models because the capabilities of these models is so much better. I look at what it is so much better. I look at what it is so much better. I look at what it does for Altimeter day in and day out. I does for Altimeter day in and day out. I does for Altimeter day in and day out. I talked to a major uh company yesterday. talked to a major uh company yesterday. talked to a major uh company yesterday. They're on a run rate to do a hundred They're on a run rate to do a hundred They're on a run rate to do a hundred million of token consumption this year million of token consumption this year million of token consumption this year on about $5 billion in opex. They think on about $5 billion in opex. They think on about $5 billion in opex. They think that we're now nearing peak employment that we're now nearing peak employment that we're now nearing peak employment in their company, but that their token in their company, but that their token in their company, but that their token their intelligence consumption, okay, their intelligence consumption, okay, their intelligence consumption, okay, let's not call it token consumption, let's not call it token consumption, let's not call it token consumption, right? because tokens may go up a lot, right? because tokens may go up a lot, right? because tokens may go up a lot, but their intelligence consumption is but their intelligence consumption is but their intelligence consumption is going to go up, you know, a lot. So, I going to go up, you know, a lot. So, I going to go up, you know, a lot. So, I would leave you with this. We're early would leave you with this. We're early would leave you with this. We're early to Chimas's point. We have low to Chimas's point. We have low to Chimas's point. We have low penetration of the global 2000. We have penetration of the global 2000. We have penetration of the global 2000. We have low penetration of the use cases. We low penetration of the use cases. We low penetration of the use cases. We have low penetration of of within the have low penetration of of within the have low penetration of of within the use cases that they're already using. use cases that they're already using. use cases that they're already using. And the models are only getting better. And the models are only getting better. And the models are only getting better. So I think when you look out toward the So I think when you look out toward the So I think when you look out toward the end of the year, I would not be shocked end of the year, I would not be shocked end of the year, I would not be shocked if you see Anthropic exiting this year if you see Anthropic exiting this year if you see Anthropic exiting this year at 80 to 100 billion in revenue. And by at 80 to 100 billion in revenue. And by at 80 to 100 billion in revenue. And by the way, doing it at the same time that the way, doing it at the same time that the way, doing it at the same time that OpenAI, who is also on the wave, they'll OpenAI, who is also on the wave, they'll OpenAI, who is also on the wave, they'll be releasing an incredible model in the be releasing an incredible model in the be releasing an incredible model in the next imminently. They're going to be on next imminently. They're going to be on next imminently. They're going to be on that wave and you're going to see an that wave and you're going to see an that wave and you're going to see an inflection in their revenues as well. inflection in their revenues as well. inflection in their revenues as well. >> Okay, Chimath, question one has been >> Okay, Chimath, question one has been >> Okay, Chimath, question one has been answered. The question of hey, does this answered. The question of hey, does this answered. The question of hey, does this stuff actually have utility? that went stuff actually have utility? that went stuff actually have utility? that went from a question mark to an exclamation from a question mark to an exclamation from a question mark to an exclamation point. Of course, it's got utility. point. Of course, it's got utility. point. Of course, it's got utility. People are getting value from it. And it People are getting value from it. And it People are getting value from it. And it might be variable. Some people get more might be variable. Some people get more might be variable. Some people get more value than others. Number two, the value than others. Number two, the value than others. Number two, the revenue ramp was a big question. Now, revenue ramp was a big question. Now, revenue ramp was a big question. Now, that's turned into an exclamation point. that's turned into an exclamation point. that's turned into an exclamation point. The final piece of the puzzle that The final piece of the puzzle that The final piece of the puzzle that you've brought up many times is can this you've brought up many times is can this you've brought up many times is can this be profitable? And these companies are be profitable? And these companies are be profitable? And these companies are burning through a large amount of cash. burning through a large amount of cash. burning through a large amount of cash. So, what is your take on when these So, what is your take on when these So, what is your take on when these companies can get out of the J curve? We companies can get out of the J curve? We companies can get out of the J curve? We talked about this, I think, three talked about this, I think, three talked about this, I think, three episodes ago. I estimated like we're episodes ago. I estimated like we're episodes ago. I estimated like we're going to be looking at $4500 billion in going to be looking at $4500 billion in going to be looking at $4500 billion in investment into these data centers at a investment into these data centers at a investment into these data centers at a minimum and then they have to climb out minimum and then they have to climb out minimum and then they have to climb out of that to get to profitability. So what of that to get to profitability. So what of that to get to profitability. So what are your thoughts on these becoming are your thoughts on these becoming are your thoughts on these becoming profitable companies? Do you remember profitable companies? Do you remember profitable companies? Do you remember the the the investor that published this list Jason investor that published this list Jason investor that published this list Jason where he put all of the terms you talk where he put all of the terms you talk where he put all of the terms you talk about when one of the terms you can't about when one of the terms you can't about when one of the terms you can't talk about is profit. It's a list where talk about is profit. It's a list where talk about is profit. It's a list where it's like if you can't talk about free it's like if you can't talk about free it's like if you can't talk about free cash flow, you talk about IBIDA. When cash flow, you talk about IBIDA. When cash flow, you talk about IBIDA. When you can't talk about IBIDA, you talk you can't talk about IBIDA, you talk you can't talk about IBIDA, you talk about about about >> margina. >> margina. >> margina. When you can't talk about that, you talk When you can't talk about that, you talk When you can't talk about that, you talk about revenue. And then when you can't about revenue. And then when you can't about revenue. And then when you can't talk about revenue, you talk about gross talk about revenue, you talk about gross talk about revenue, you talk about gross revenue revenue revenue >> bookings. >> bookings. >> bookings. >> So you can kind of figure out, >> So you can kind of figure out, >> So you can kind of figure out, I think, where we are in any part of any I think, where we are in any part of any I think, where we are in any part of any cycle by just indexing into what does cycle by just indexing into what does cycle by just indexing into what does everybody talk about. I think where we everybody talk about. I think where we everybody talk about. I think where we are is we are between gross revenue and are is we are between gross revenue and are is we are between gross revenue and net revenue. That's where the discussion net revenue. That's where the discussion net revenue. That's where the discussion is. is. is. >> Okay. >> Okay. >> Okay. >> There was another article I think today >> There was another article I think today >> There was another article I think today in I think maybe it was the information in I think maybe it was the information in I think maybe it was the information that tried to categorize and distinguish that tried to categorize and distinguish that tried to categorize and distinguish that anthropic presents gross, open AI that anthropic presents gross, open AI that anthropic presents gross, open AI presents net. They're different. We presents net. They're different. We presents net. They're different. We don't know what the various take rates don't know what the various take rates don't know what the various take rates are. So they're saying that there's a are. So they're saying that there's a are. So they're saying that there's a difference. If it's not true, there's difference. If it's not true, there's difference. If it's not true, there's been no clarity provided by these been no clarity provided by these been no clarity provided by these companies. So, at a minimum, you have companies. So, at a minimum, you have companies. So, at a minimum, you have this confusion where there's the this confusion where there's the this confusion where there's the breathless talk. Then there's people breathless talk. Then there's people breathless talk. Then there's people that don't even know the difference that don't even know the difference that don't even know the difference between actual recognized revenue and between actual recognized revenue and between actual recognized revenue and run rate revenue and how to multi. I run rate revenue and how to multi. I run rate revenue and how to multi. I mean, so we're definitely there, okay? mean, so we're definitely there, okay? mean, so we're definitely there, okay? We can quibble about the details, but we We can quibble about the details, but we We can quibble about the details, but we are not at the place where people are are not at the place where people are are not at the place where people are like, "Oh, here's your steadystate, you like, "Oh, here's your steadystate, you like, "Oh, here's your steadystate, you know, free cash flow margin, and here's know, free cash flow margin, and here's know, free cash flow margin, and here's what your EBA does." We're never we're what your EBA does." We're never we're what your EBA does." We're never we're we're years from that. They're gonna we're years from that. They're gonna we're years from that. They're gonna have token maxing IBA like IB at the have token maxing IBA like IB at the have token maxing IBA like IB at the Wii. Wii. Wii. >> The thing that we need to understand is >> The thing that we need to understand is >> The thing that we need to understand is how gross margin negative is this how gross margin negative is this how gross margin negative is this revenue growth. revenue growth. revenue growth. >> We don't know that and at least we don't >> We don't know that and at least we don't >> We don't know that and at least we don't as outsiders. as outsiders. as outsiders. >> Brad might know. >> Brad might know. >> Brad might know. >> Brad may know. I I I I will tell you >> Brad may know. I I I I will tell you >> Brad may know. I I I I will tell you think about this. What are their big think about this. What are their big think about this. What are their big cost inputs? The number one cost input cost inputs? The number one cost input cost inputs? The number one cost input is the cost of compute. Cost of compute. is the cost of compute. Cost of compute. is the cost of compute. Cost of compute. >> Right? I just told you they only have a >> Right? I just told you they only have a >> Right? I just told you they only have a gigawatt and a half of compute. and they gigawatt and a half of compute. and they gigawatt and a half of compute. and they have that gigawatt and a half of compute have that gigawatt and a half of compute have that gigawatt and a half of compute whether they have a billion in revenue whether they have a billion in revenue whether they have a billion in revenue or whether they have 80 billion in or whether they have 80 billion in or whether they have 80 billion in revenue. So you might actually expect to revenue. So you might actually expect to revenue. So you might actually expect to see these companies their gross margins see these companies their gross margins see these companies their gross margins are exploding higher like the fastest are exploding higher like the fastest are exploding higher like the fastest increase in gross margins I've probably increase in gross margins I've probably increase in gross margins I've probably seen out of any technology company. So seen out of any technology company. So seen out of any technology company. So this is not gross margin negative you're this is not gross margin negative you're this is not gross margin negative you're saying? saying? saying? >> No definitely not gross margin negative. >> No definitely not gross margin negative. >> No definitely not gross margin negative. And what I would tell you And what I would tell you And what I would tell you >> so that they must be hugely profitable >> so that they must be hugely profitable >> so that they must be hugely profitable then then then >> well you may see accidental why I call >> well you may see accidental why I call >> well you may see accidental why I call it accidental profitability. They may it accidental profitability. They may it accidental profitability. They may not be able to spend this revenue fast not be able to spend this revenue fast not be able to spend this revenue fast enough chamath on compute. And remember enough chamath on compute. And remember enough chamath on compute. And remember it's only 2500 people. Google crossed it's only 2500 people. Google crossed it's only 2500 people. Google crossed this revenue threshold when they had this revenue threshold when they had this revenue threshold when they had 120,000 people. These guys have 2500 120,000 people. These guys have 2500 120,000 people. These guys have 2500 people. So the only thing you can really people. So the only thing you can really people. So the only thing you can really spend money on, right, is compute. And spend money on, right, is compute. And spend money on, right, is compute. And they can't stand up the compute fast they can't stand up the compute fast they can't stand up the compute fast enough. enough. enough. >> But none of this foots to me then to be >> But none of this foots to me then to be >> But none of this foots to me then to be honest because if you were on a honest because if you were on a honest because if you were on a threshold of 90% plus gross margin, threshold of 90% plus gross margin, threshold of 90% plus gross margin, >> I'm not saying it's there. I'm not >> I'm not saying it's there. I'm not >> I'm not saying it's there. I'm not saying it's 90% plus. I'm just saying saying it's 90% plus. I'm just saying saying it's 90% plus. I'm just saying it's gone from meaningfully negative 18 it's gone from meaningfully negative 18 it's gone from meaningfully negative 18 months ago to, you know, very very months ago to, you know, very very months ago to, you know, very very positive. I've seen rumored out there positive. I've seen rumored out there positive. I've seen rumored out there 50% is what you're saying. The trend is 50% is what you're saying. The trend is 50% is what you're saying. The trend is there. there. there. >> Let me just say this. >> Let me just say this. >> Let me just say this. I think if you're an incumbent, you want I think if you're an incumbent, you want I think if you're an incumbent, you want the cost of compute to go down. I think the cost of compute to go down. I think the cost of compute to go down. I think if you're not an incumbent, so if you're not an incumbent, so if you're not an incumbent, so specifically, who do I mean? Meta, specifically, who do I mean? Meta, specifically, who do I mean? Meta, Google, and SpaceX. Google, and SpaceX. Google, and SpaceX. I think those three people who have all I think those three people who have all I think those three people who have all three of them, well, sorry, Meta and three of them, well, sorry, Meta and three of them, well, sorry, Meta and Google have a fortress balance sheet. I Google have a fortress balance sheet. I Google have a fortress balance sheet. I think by the end of June, SpaceX will think by the end of June, SpaceX will think by the end of June, SpaceX will also have a fortress balance sheet. What also have a fortress balance sheet. What also have a fortress balance sheet. What they will want to do is they will want they will want to do is they will want they will want to do is they will want to make this a compute problem because to make this a compute problem because to make this a compute problem because they will control the the conditions on they will control the the conditions on they will control the the conditions on the field. You already see this today. the field. You already see this today. the field. You already see this today. >> Yeah. >> Yeah. >> Yeah. >> Meta's models today, what people's >> Meta's models today, what people's >> Meta's models today, what people's general reviews are it's okay, but the general reviews are it's okay, but the general reviews are it's okay, but the one thing that people say is it's one thing that people say is it's one thing that people say is it's incredibly performant. The model quality incredibly performant. The model quality incredibly performant. The model quality is okay, but the performance is great, is okay, but the performance is great, is okay, but the performance is great, which speaks to Meta's huge advantage. which speaks to Meta's huge advantage. which speaks to Meta's huge advantage. They have a massive compute They have a massive compute They have a massive compute infrastructure. So if you're if you're infrastructure. So if you're if you're infrastructure. So if you're if you're not open AI and anthropic, not open AI and anthropic, not open AI and anthropic, they'll want to make this a capital they'll want to make this a capital they'll want to make this a capital problem because then they can win it. If problem because then they can win it. If problem because then they can win it. If you're anthropic and open AI, you want you're anthropic and open AI, you want you're anthropic and open AI, you want this thing to be as efficient as this thing to be as efficient as this thing to be as efficient as possible. possible. possible. I think where we are is very much in the I think where we are is very much in the I think where we are is very much in the early innings. And we're bumbling around early innings. And we're bumbling around early innings. And we're bumbling around talking about gross margins and you know talking about gross margins and you know talking about gross margins and you know revenues. We are not at profitability. revenues. We are not at profitability. revenues. We are not at profitability. And what is true for Facebook and what And what is true for Facebook and what And what is true for Facebook and what was true for Google was irrespective of was true for Google was irrespective of was true for Google was irrespective of where they got to a billion. Who g where they got to a billion. Who g where they got to a billion. Who g cares? They were profitable by year cares? They were profitable by year cares? They were profitable by year three and they never looked back. I was three and they never looked back. I was three and they never looked back. I was there. I remember it was glorious. there. I remember it was glorious. there. I remember it was glorious. >> The the cost the cost of building uh you >> The the cost the cost of building uh you >> The the cost the cost of building uh you know AI know AI know AI totally stipulate is radically higher totally stipulate is radically higher totally stipulate is radically higher than the cost of building retrieval at than the cost of building retrieval at than the cost of building retrieval at Google, right? Like it's just a Google, right? Like it's just a Google, right? Like it's just a fundamentally more expensive problem. fundamentally more expensive problem. fundamentally more expensive problem. But I will tell you that there's a lot But I will tell you that there's a lot But I will tell you that there's a lot of FUD out there about negative gross of FUD out there about negative gross of FUD out there about negative gross margins. I mean Jason, you started the margins. I mean Jason, you started the margins. I mean Jason, you started the segment by saying they're burning segment by saying they're burning segment by saying they're burning through large amounts of cash. I think through large amounts of cash. I think through large amounts of cash. I think people are going to be shocked at the people are going to be shocked at the people are going to be shocked at the burn how low the burn levels are at burn how low the burn levels are at burn how low the burn levels are at these companies. these companies. these companies. >> Anthropic or Open AI. >> Anthropic or Open AI. >> Anthropic or Open AI. >> Yes. And and I would say at Open AI as >> Yes. And and I would say at Open AI as >> Yes. And and I would say at Open AI as well like they're if they're on you know well like they're if they're on you know well like they're if they're on you know if they do $50 billion this year again if they do $50 billion this year again if they do $50 billion this year again just look at the number of people they just look at the number of people they just look at the number of people they have revenue per people. It's pretty low have revenue per people. It's pretty low have revenue per people. It's pretty low and the inference cost is plummeting. and the inference cost is plummeting. and the inference cost is plummeting. Inference cost is down by 90% Inference cost is down by 90% Inference cost is down by 90% year-over-year. And so just finally I year-over-year. And so just finally I year-over-year. And so just finally I want to make respond to this point about want to make respond to this point about want to make respond to this point about gross versus net uh this this tweet that gross versus net uh this this tweet that gross versus net uh this this tweet that Chimath was referencing. Okay, so Chimath was referencing. Okay, so Chimath was referencing. Okay, so there's a certain percentage, a there's a certain percentage, a there's a certain percentage, a smallalish percentage of Anthropics smallalish percentage of Anthropics smallalish percentage of Anthropics revenue, right, that they distribute revenue, right, that they distribute revenue, right, that they distribute through the hyperscalers and like a lot through the hyperscalers and like a lot through the hyperscalers and like a lot of arrangements, whether it's Snowflake of arrangements, whether it's Snowflake of arrangements, whether it's Snowflake or Data Bricks or others, you pay a or Data Bricks or others, you pay a or Data Bricks or others, you pay a commission, right, uh on on that. I will commission, right, uh on on that. I will commission, right, uh on on that. I will just tell you that you're talking just tell you that you're talking just tell you that you're talking singledigit percentage of total revenue singledigit percentage of total revenue singledigit percentage of total revenue of these companies. So the gross versus of these companies. So the gross versus of these companies. So the gross versus net thing isn't what's being reported. net thing isn't what's being reported. net thing isn't what's being reported. like the apples for apples is pretty like the apples for apples is pretty like the apples for apples is pretty easy and if you want to be conservative easy and if you want to be conservative easy and if you want to be conservative on it take down Anthropic's revenue by on it take down Anthropic's revenue by on it take down Anthropic's revenue by you know five to 10% which you know you know five to 10% which you know you know five to 10% which you know again I don't I think it's better to again I don't I think it's better to again I don't I think it's better to gross up OpenAI's revenue but any way gross up OpenAI's revenue but any way gross up OpenAI's revenue but any way you do it I just think it's a you do it I just think it's a you do it I just think it's a distraction from what's really what's distraction from what's really what's distraction from what's really what's really going on here happy to really going on here happy to really going on here happy to >> s you have any thoughts on this uh >> s you have any thoughts on this uh >> s you have any thoughts on this uh massive revenue ramp massive revenue ramp massive revenue ramp >> yeah I mean I want to go back to a point >> yeah I mean I want to go back to a point >> yeah I mean I want to go back to a point that Brad made because I think it was that Brad made because I think it was that Brad made because I think it was just really important and I want to just just really important and I want to just just really important and I want to just underline it consider where we were at underline it consider where we were at underline it consider where we were at the beginning of the year and What the beginning of the year and What the beginning of the year and What everybody was saying is that AI was a everybody was saying is that AI was a everybody was saying is that AI was a big bubble and the evidence they would big bubble and the evidence they would big bubble and the evidence they would point to was the fact that hundreds of point to was the fact that hundreds of point to was the fact that hundreds of billions of dollars was going into capex billions of dollars was going into capex billions of dollars was going into capex that needed to be spent on these data that needed to be spent on these data that needed to be spent on these data centers and there was no evidence of centers and there was no evidence of centers and there was no evidence of significant revenue to justify that significant revenue to justify that significant revenue to justify that spend. Where was the ROI? By the way, as spend. Where was the ROI? By the way, as spend. Where was the ROI? By the way, as an aside, the same doomers who were an aside, the same doomers who were an aside, the same doomers who were saying that AI was in a bubble were also saying that AI was in a bubble were also saying that AI was in a bubble were also the ones who were saying that AI was so the ones who were saying that AI was so the ones who were saying that AI was so powerful it's going to put us all out of powerful it's going to put us all out of powerful it's going to put us all out of work and it's going to, you know, take work and it's going to, you know, take work and it's going to, you know, take over from humanity. I mean, in other over from humanity. I mean, in other over from humanity. I mean, in other words, they couldn't decide if AI was words, they couldn't decide if AI was words, they couldn't decide if AI was too powerful or not powerful enough. But too powerful or not powerful enough. But too powerful or not powerful enough. But putting aside that contradiction, they putting aside that contradiction, they putting aside that contradiction, they clearly were making this case that AI clearly were making this case that AI clearly were making this case that AI was this big bubble and that there'd be was this big bubble and that there'd be was this big bubble and that there'd be no payoff or justification for this no payoff or justification for this no payoff or justification for this massive capex that's being spent. And I massive capex that's being spent. And I massive capex that's being spent. And I think we're starting to see here there think we're starting to see here there think we're starting to see here there is justification for it. Uh we're seeing is justification for it. Uh we're seeing is justification for it. Uh we're seeing it just in this one vertical of AI which it just in this one vertical of AI which it just in this one vertical of AI which is coding. We're again seeing the is coding. We're again seeing the is coding. We're again seeing the fastest revenue growth in history. It's fastest revenue growth in history. It's fastest revenue growth in history. It's utterly unprecedented. And this is just utterly unprecedented. And this is just utterly unprecedented. And this is just one category or vertical of AI. We know one category or vertical of AI. We know one category or vertical of AI. We know that agents are coming next and the that agents are coming next and the that agents are coming next and the enterprise adoption of that is going to enterprise adoption of that is going to enterprise adoption of that is going to be absolutely massive. So, I guess what be absolutely massive. So, I guess what be absolutely massive. So, I guess what I'm saying is that this is early proof I'm saying is that this is early proof I'm saying is that this is early proof for I think the thing that makes Silicon for I think the thing that makes Silicon for I think the thing that makes Silicon Valley special, which is we're willing Valley special, which is we're willing Valley special, which is we're willing to basically bet on things that just to basically bet on things that just to basically bet on things that just intuitively on a gut level we know are intuitively on a gut level we know are intuitively on a gut level we know are the next big thing. We're not that the next big thing. We're not that the next big thing. We're not that spreadsheet driven. Actually, Silicon spreadsheet driven. Actually, Silicon spreadsheet driven. Actually, Silicon Valley believes that if you build it, Valley believes that if you build it, Valley believes that if you build it, they will come and is willing to finance they will come and is willing to finance they will come and is willing to finance that build out. And that's basically that build out. And that's basically that build out. And that's basically what's been happening. Again, just the what's been happening. Again, just the what's been happening. Again, just the top four hyperscalers, $350 billion of top four hyperscalers, $350 billion of top four hyperscalers, $350 billion of expected capex this year on its way, I expected capex this year on its way, I expected capex this year on its way, I think Jensen said 1 trillion by 2030. think Jensen said 1 trillion by 2030. think Jensen said 1 trillion by 2030. So, Silicon Valley, whether it's big So, Silicon Valley, whether it's big So, Silicon Valley, whether it's big companies, whether it's founders, companies, whether it's founders, companies, whether it's founders, they're always willing to bet on this they're always willing to bet on this they're always willing to bet on this next big thing. They're not like Wall next big thing. They're not like Wall next big thing. They're not like Wall Street. They don't need, you know, Street. They don't need, you know, Street. They don't need, you know, specialist to tell them where to go. specialist to tell them where to go. specialist to tell them where to go. They know where the technology is going They know where the technology is going They know where the technology is going and they make their bets based on that. and they make their bets based on that. and they make their bets based on that. And I think that there is going to be a And I think that there is going to be a And I think that there is going to be a big payoff for this. And I think it's big payoff for this. And I think it's big payoff for this. And I think it's the thing that's going to make our the thing that's going to make our the thing that's going to make our economy and the United States in general economy and the United States in general economy and the United States in general remain extremely dynamic and in the lead remain extremely dynamic and in the lead remain extremely dynamic and in the lead on this thing is that we are willing to on this thing is that we are willing to on this thing is that we are willing to make those kinds of bets. And I think make those kinds of bets. And I think make those kinds of bets. And I think it's going to pay off big time. it's going to pay off big time. it's going to pay off big time. >> Yeah, clearly. Hey, um Brad, you didn't >> Yeah, clearly. Hey, um Brad, you didn't >> Yeah, clearly. Hey, um Brad, you didn't answer my question about the vibes over answer my question about the vibes over answer my question about the vibes over at OpenAI versus Quad. Open AI is um I at OpenAI versus Quad. Open AI is um I at OpenAI versus Quad. Open AI is um I wouldn't say reeling but there's a lot wouldn't say reeling but there's a lot wouldn't say reeling but there's a lot of hand ringing going on a lot of of hand ringing going on a lot of of hand ringing going on a lot of employees leaving a lot of people who employees leaving a lot of people who employees leaving a lot of people who are wondering like is our strategy the are wondering like is our strategy the are wondering like is our strategy the winning strategy of like consumer first winning strategy of like consumer first winning strategy of like consumer first they shut down Sora you know unwinding they shut down Sora you know unwinding they shut down Sora you know unwinding the Disney deal and really trying to get the Disney deal and really trying to get the Disney deal and really trying to get the company focused and it's kind of the company focused and it's kind of the company focused and it's kind of like I mean listen the New Yorker story like I mean listen the New Yorker story like I mean listen the New Yorker story was a bit of a rehash so I don't think was a bit of a rehash so I don't think was a bit of a rehash so I don't think we have to go into the blowby-blow we have to go into the blowby-blow we have to go into the blowby-blow because we covered here three years ago because we covered here three years ago because we covered here three years ago but the truth is a lot of the great but the truth is a lot of the great but the truth is a lot of the great founders, co-founders of OpenAI and a founders, co-founders of OpenAI and a founders, co-founders of OpenAI and a lot of the great contributors are now at lot of the great contributors are now at lot of the great contributors are now at Anthropic and other large language Anthropic and other large language Anthropic and other large language models. And in the secondary market, models. And in the secondary market, models. And in the secondary market, OpenAI is trading lower than the last OpenAI is trading lower than the last OpenAI is trading lower than the last valuation. And Anthropic is trading valuation. And Anthropic is trading valuation. And Anthropic is trading significantly above the $380 billion. So significantly above the $380 billion. So significantly above the $380 billion. So maybe talk a little bit about this maybe talk a little bit about this maybe talk a little bit about this competition, this Microsoft versus competition, this Microsoft versus competition, this Microsoft versus Apple, this Google versus Facebook. Apple, this Google versus Facebook. Apple, this Google versus Facebook. Well, let's let's start with immense Well, let's let's start with immense Well, let's let's start with immense credit where credit is due. Anthropic credit where credit is due. Anthropic credit where credit is due. Anthropic was literally counted out of the game was literally counted out of the game was literally counted out of the game last year. Y, last year. Y, last year. Y, >> right? And here they come over the last >> right? And here they come over the last >> right? And here they come over the last 12 months and and and they've kicked 12 months and and and they've kicked 12 months and and and they've kicked OpenAI's ass over the last 90 days, OpenAI's ass over the last 90 days, OpenAI's ass over the last 90 days, right? And what did Anthropic do? right? And what did Anthropic do? right? And what did Anthropic do? Anthropic made choices. No multimodal, Anthropic made choices. No multimodal, Anthropic made choices. No multimodal, no video, no hardware, no chips, no no video, no hardware, no chips, no no video, no hardware, no chips, no building data centers. They said, "We're building data centers. They said, "We're building data centers. They said, "We're just going to focus on coding and just going to focus on coding and just going to focus on coding and co-work. We think that is the path to co-work. We think that is the path to co-work. We think that is the path to AGI and and and and ASI." They executed AGI and and and and ASI." They executed AGI and and and and ASI." They executed their butts off. They took the lead. their butts off. They took the lead. their butts off. They took the lead. 2500 people tight pulling on the ore in 2500 people tight pulling on the ore in 2500 people tight pulling on the ore in the same direction. But I think you the same direction. But I think you the same direction. But I think you would be seriously foolish to count out would be seriously foolish to count out would be seriously foolish to count out open AI, right? And I think we're we're open AI, right? And I think we're we're open AI, right? And I think we're we're we're at peak open AI FUD. And I'll tell we're at peak open AI FUD. And I'll tell we're at peak open AI FUD. And I'll tell you, it starts with great researchers you, it starts with great researchers you, it starts with great researchers and great models. And I think when you and great models. And I think when you and great models. And I think when you see the Spud model, they're about ready see the Spud model, they're about ready see the Spud model, they're about ready to release. I think it's going to be an to release. I think it's going to be an to release. I think it's going to be an excellent model. Shows that they're excellent model. Shows that they're excellent model. Shows that they're firmly on the wave. Um, if you look at firmly on the wave. Um, if you look at firmly on the wave. Um, if you look at what's going on with Codeex, incredible what's going on with Codeex, incredible what's going on with Codeex, incredible ramp on Codeex, fastest ramping model ramp on Codeex, fastest ramping model ramp on Codeex, fastest ramping model with 5.4, I think 5.5 or Spud, whatever with 5.4, I think 5.5 or Spud, whatever with 5.4, I think 5.5 or Spud, whatever we're going to call, it's going to be an we're going to call, it's going to be an we're going to call, it's going to be an even faster ramp. even faster ramp. even faster ramp. >> Have you seen Spud? Have you used it? >> Have you seen Spud? Have you used it? >> Have you seen Spud? Have you used it? Have you gotten a preview? Have you gotten a preview? Have you gotten a preview? >> People are using Spud, right? So, it it >> People are using Spud, right? So, it it >> People are using Spud, right? So, it it is being previewed and so is being previewed and so is being previewed and so >> So, you're talking to people who've used >> So, you're talking to people who've used >> So, you're talking to people who've used it and what are they telling you? it and what are they telling you? it and what are they telling you? >> They're telling us that it's an >> They're telling us that it's an >> They're telling us that it's an incredible model on par with Mythos, incredible model on par with Mythos, incredible model on par with Mythos, right? and that it's a a very usable right? and that it's a a very usable right? and that it's a a very usable model in terms of um how it's packaged. model in terms of um how it's packaged. model in terms of um how it's packaged. I will say that back to David's point I will say that back to David's point I will say that back to David's point now this is the most important point I now this is the most important point I now this is the most important point I think anybody can take away here. think anybody can take away here. think anybody can take away here. This is not zero sum. The TAM of This is not zero sum. The TAM of This is not zero sum. The TAM of intelligence is dramatically larger than intelligence is dramatically larger than intelligence is dramatically larger than any TAM we've ever seen in our investing any TAM we've ever seen in our investing any TAM we've ever seen in our investing careers over the last two decades. careers over the last two decades. careers over the last two decades. Right? And if you're on the wave, which Right? And if you're on the wave, which Right? And if you're on the wave, which Open AAI is, you are going to be selling Open AAI is, you are going to be selling Open AAI is, you are going to be selling into the world's biggest TAM, they are into the world's biggest TAM, they are into the world's biggest TAM, they are going to build a very big company. I'm a going to build a very big company. I'm a going to build a very big company. I'm a buyer of the shares today. buyer of the shares today. buyer of the shares today. Notwithstanding all of the vibes that Notwithstanding all of the vibes that Notwithstanding all of the vibes that you describe, I think these companies you describe, I think these companies you describe, I think these companies are firmly on the wave. They are jarred. are firmly on the wave. They are jarred. are firmly on the wave. They are jarred. They are sitting there saying, "What did They are sitting there saying, "What did They are sitting there saying, "What did we do wrong? And how do we get our mojo we do wrong? And how do we get our mojo we do wrong? And how do we get our mojo back?" They want to compete. It is back?" They want to compete. It is back?" They want to compete. It is embarrassing to people on the research embarrassing to people on the research embarrassing to people on the research team and the product team over there. team and the product team over there. team and the product team over there. So, I'm not saying there's not a real So, I'm not saying there's not a real So, I'm not saying there's not a real awakening occurring there, but I think awakening occurring there, but I think awakening occurring there, but I think that's what the case is. And by the way, that's what the case is. And by the way, that's what the case is. And by the way, to Chamas's point, do not count out to Chamas's point, do not count out to Chamas's point, do not count out Meta, right? I think Meta is absolutely Meta, right? I think Meta is absolutely Meta, right? I think Meta is absolutely in this game. Google is absolutely in in this game. Google is absolutely in in this game. Google is absolutely in this game. Elon is absolutely in this this game. Elon is absolutely in this this game. Elon is absolutely in this game. And if you're game. And if you're game. And if you're >> got some stuff dropping shortly that's >> got some stuff dropping shortly that's >> got some stuff dropping shortly that's going to be very impressive. going to be very impressive. going to be very impressive. >> If you're on team America, the fact that >> If you're on team America, the fact that >> If you're on team America, the fact that we have five frontier models competing we have five frontier models competing we have five frontier models competing against each other and David made sure against each other and David made sure against each other and David made sure they weren't throttled by excessive they weren't throttled by excessive they weren't throttled by excessive government regulation. We have mythos government regulation. We have mythos government regulation. We have mythos come out. It's a self-imposed safe come out. It's a self-imposed safe come out. It's a self-imposed safe harbor, you know, to harden our system. harbor, you know, to harden our system. harbor, you know, to harden our system. It wasn't a call for moratoriums or It wasn't a call for moratoriums or It wasn't a call for moratoriums or getting the government involved. We have getting the government involved. We have getting the government involved. We have the type of competition that's causing the type of competition that's causing the type of competition that's causing us to accelerate our lead against the us to accelerate our lead against the us to accelerate our lead against the rest of the world. We can't take our eye rest of the world. We can't take our eye rest of the world. We can't take our eye off the prize. We got to stop off the prize. We got to stop off the prize. We got to stop adversarial distillation and we need to adversarial distillation and we need to adversarial distillation and we need to make sure that we're distributing our make sure that we're distributing our make sure that we're distributing our products around the world. But I view products around the world. But I view products around the world. But I view this as really good for team America. this as really good for team America. this as really good for team America. >> Well said. And here is your poly market >> Well said. And here is your poly market >> Well said. And here is your poly market IPOs before 2027. Obviously SpaceX at IPOs before 2027. Obviously SpaceX at IPOs before 2027. Obviously SpaceX at 95% uh Cerebrus at 94% and uh hey number 95% uh Cerebrus at 94% and uh hey number 95% uh Cerebrus at 94% and uh hey number five on this list 51% chance that five on this list 51% chance that five on this list 51% chance that Anthropic goes out before the end of the Anthropic goes out before the end of the Anthropic goes out before the end of the year. 44% chance that OpenAI comes out year. 44% chance that OpenAI comes out year. 44% chance that OpenAI comes out before then. All right here is the before then. All right here is the before then. All right here is the closing market cap for Anthropic on Poly closing market cap for Anthropic on Poly closing market cap for Anthropic on Poly Market only $158,000 in volume. So, Market only $158,000 in volume. So, Market only $158,000 in volume. So, Chimath, when you put in 400K, you're Chimath, when you put in 400K, you're Chimath, when you put in 400K, you're going to really tilt this market. going to really tilt this market. going to really tilt this market. 78% chance that it's above 600 billion, 78% chance that it's above 600 billion, 78% chance that it's above 600 billion, 19% chance that it doesn't go out. So, 19% chance that it doesn't go out. So, 19% chance that it doesn't go out. So, it's looking like this will be a decent it's looking like this will be a decent it's looking like this will be a decent investment for you. Brad, what valuation investment for you. Brad, what valuation investment for you. Brad, what valuation did you get into Anthropic at? did you get into Anthropic at? did you get into Anthropic at? >> We first invested in I believe it was >> We first invested in I believe it was >> We first invested in I believe it was the the the uh 30 or $150 billion round. uh 30 or $150 billion round. uh 30 or $150 billion round. >> So, this will be a 7x 5x for Altimeter >> So, this will be a 7x 5x for Altimeter >> So, this will be a 7x 5x for Altimeter L, please. Congratulations. I mean, no, L, please. Congratulations. I mean, no, L, please. Congratulations. I mean, no, listen. I I I again, there are lots of listen. I I I again, there are lots of listen. I I I again, there are lots of people who were there before us and who people who were there before us and who people who were there before us and who are on the board and who are going to do are on the board and who are going to do are on the board and who are going to do much better than that. What' you put in? much better than that. What' you put in? much better than that. What' you put in? 50. 50. 50. >> What' you put in? >> What' you put in? >> What' you put in? >> No, we've got billions in both >> No, we've got billions in both >> No, we've got billions in both companies. Uh companies. Uh companies. Uh >> billions in both companies. Oh my lord. >> billions in both companies. Oh my lord. >> billions in both companies. Oh my lord. >> I think there's this existential thing >> I think there's this existential thing >> I think there's this existential thing going on in venture today. David could going on in venture today. David could going on in venture today. David could talk about it as well. I mean people talk about it as well. I mean people talk about it as well. I mean people can't they're extraordinarily nervous can't they're extraordinarily nervous can't they're extraordinarily nervous about you look at the IGV stock index about you look at the IGV stock index about you look at the IGV stock index down 30% year to date down 5% today all down 30% year to date down 5% today all down 30% year to date down 5% today all software stocks plummeting right venture software stocks plummeting right venture software stocks plummeting right venture capitalists are terrified to invest capitalists are terrified to invest capitalists are terrified to invest money in anything other than these money in anything other than these money in anything other than these frontier models and things like SpaceX frontier models and things like SpaceX frontier models and things like SpaceX or military modernization finding or military modernization finding or military modernization finding something that's out of harm's way of AI something that's out of harm's way of AI something that's out of harm's way of AI right where you can count on the right where you can count on the right where you can count on the terminal value to Chamas insights over terminal value to Chamas insights over terminal value to Chamas insights over the last few weeks is very difficult to the last few weeks is very difficult to the last few weeks is very difficult to do. That's why you see this crowding. do. That's why you see this crowding. do. That's why you see this crowding. So, we've taken a barbell approach, So, we've taken a barbell approach, So, we've taken a barbell approach, right? We've got a lot in what we think right? We've got a lot in what we think right? We've got a lot in what we think are the most important companies that are the most important companies that are the most important companies that are on the frontier and then we're are on the frontier and then we're are on the frontier and then we're betting with on really small teams that betting with on really small teams that betting with on really small teams that we think have very defensible businesses we think have very defensible businesses we think have very defensible businesses in a world of uh you know, AGI. But it's in a world of uh you know, AGI. But it's in a world of uh you know, AGI. But it's >> what happens to all these enterprise >> what happens to all these enterprise >> what happens to all these enterprise software companies? Do they become PE software companies? Do they become PE software companies? Do they become PE takeouts? Do they get consolidated? um takeouts? Do they get consolidated? um takeouts? Do they get consolidated? um or do they just have to adopt these AI or do they just have to adopt these AI or do they just have to adopt these AI technologies and and and solve this technologies and and and solve this technologies and and and solve this problem of hey the frontier model is problem of hey the frontier model is problem of hey the frontier model is just going to solve for whatever these just going to solve for whatever these just going to solve for whatever these niche software companies do. niche software companies do. niche software companies do. >> I think the market's probably being a >> I think the market's probably being a >> I think the market's probably being a little too pessimistic with respect to little too pessimistic with respect to little too pessimistic with respect to at least some of these software at least some of these software at least some of these software companies. I mean, obviously, there's companies. I mean, obviously, there's companies. I mean, obviously, there's going to be big differences in the going to be big differences in the going to be big differences in the quality of the modes of these companies. quality of the modes of these companies. quality of the modes of these companies. And so, look, software is going to be a And so, look, software is going to be a And so, look, software is going to be a lot cheaper and easier to generate, but lot cheaper and easier to generate, but lot cheaper and easier to generate, but I'm not sure that was the competitive I'm not sure that was the competitive I'm not sure that was the competitive advantage of a lot of these companies. advantage of a lot of these companies. advantage of a lot of these companies. So, there's probably a little bit of the So, there's probably a little bit of the So, there's probably a little bit of the baby being thrown out with the bathwater baby being thrown out with the bathwater baby being thrown out with the bathwater right now, and there probably are some right now, and there probably are some right now, and there probably are some value buys in enterprise software. I value buys in enterprise software. I value buys in enterprise software. I think the interesting question here and think the interesting question here and think the interesting question here and we've been talking about this for a we've been talking about this for a we've been talking about this for a couple of years in the pod is just where couple of years in the pod is just where couple of years in the pod is just where you see the AI value capture being in you see the AI value capture being in you see the AI value capture being in terms of layer of the stack. Remember terms of layer of the stack. Remember terms of layer of the stack. Remember where we started it was really just the where we started it was really just the where we started it was really just the chip layer of the stack was where all chip layer of the stack was where all chip layer of the stack was where all the value capture was. It was basically the value capture was. It was basically the value capture was. It was basically Nvidia was the first company to be worth Nvidia was the first company to be worth Nvidia was the first company to be worth multiple trillions of dollars because of multiple trillions of dollars because of multiple trillions of dollars because of AI. And for a while it looked like AI. And for a while it looked like AI. And for a while it looked like that's where all the value capture was that's where all the value capture was that's where all the value capture was going to be because OpenAI for example going to be because OpenAI for example going to be because OpenAI for example was losing so much money and Anthropic was losing so much money and Anthropic was losing so much money and Anthropic wasn't on the radar as much. Now we're wasn't on the radar as much. Now we're wasn't on the radar as much. Now we're seeing wait a second um you know it's seeing wait a second um you know it's seeing wait a second um you know it's not just the chip companies it's also not just the chip companies it's also not just the chip companies it's also the hyperscalers are now benefiting and the hyperscalers are now benefiting and the hyperscalers are now benefiting and now we're seeing at the model layer it now we're seeing at the model layer it now we're seeing at the model layer it looks like Enthropic and Open AI they're looks like Enthropic and Open AI they're looks like Enthropic and Open AI they're all going to be huge beneficiaries. I all going to be huge beneficiaries. I all going to be huge beneficiaries. I think the next question is at the think the next question is at the think the next question is at the application layer of the stack. Okay. application layer of the stack. Okay. application layer of the stack. Okay. Well, now does all that value capture Well, now does all that value capture Well, now does all that value capture just get eaten by the model companies or just get eaten by the model companies or just get eaten by the model companies or are there applications that get are there applications that get are there applications that get turbocharged? I guess you could say that turbocharged? I guess you could say that turbocharged? I guess you could say that Palunteer is already one of them, right? Palunteer is already one of them, right? Palunteer is already one of them, right? It's an application company that's been It's an application company that's been It's an application company that's been turbocharged by these model turbocharged by these model turbocharged by these model capabilities. Who else will be a big capabilities. Who else will be a big capabilities. Who else will be a big beneficiary? Is it again, is it all beneficiary? Is it again, is it all beneficiary? Is it again, is it all going to be at the model layer or will going to be at the model layer or will going to be at the model layer or will you see an explosion of value at the you see an explosion of value at the you see an explosion of value at the application layer? I'm hoping obviously application layer? I'm hoping obviously application layer? I'm hoping obviously that it'll be at all layers of the that it'll be at all layers of the that it'll be at all layers of the stack. PC beneficiaries. But to me, stack. PC beneficiaries. But to me, stack. PC beneficiaries. But to me, that's a really interesting question that's a really interesting question that's a really interesting question right now. right now. right now. >> Yeah. What happens to Salesforce, >> Yeah. What happens to Salesforce, >> Yeah. What happens to Salesforce, HubSpot, you know, Oracle, right down HubSpot, you know, Oracle, right down HubSpot, you know, Oracle, right down the line? David, uh, Chimati, your the line? David, uh, Chimati, your the line? David, uh, Chimati, your thoughts here, uh, on the the layers thoughts here, uh, on the the layers thoughts here, uh, on the the layers here and where the value is captured. here and where the value is captured. here and where the value is captured. >> It's too early to tell. >> It's too early to tell. >> It's too early to tell. >> Too early to tell, right? And energy we >> Too early to tell, right? And energy we >> Too early to tell, right? And energy we kind of put into sort of data center as kind of put into sort of data center as kind of put into sort of data center as well, but that's obviously been a clear well, but that's obviously been a clear well, but that's obviously been a clear winner. Little housekeeping here. winner. Little housekeeping here. winner. Little housekeeping here. Liquidity, put a little Tiffany in here. Liquidity, put a little Tiffany in here. Liquidity, put a little Tiffany in here. uh producer Nick D is sold out. There's uh producer Nick D is sold out. There's uh producer Nick D is sold out. There's a wait list of hundreds of people, but a wait list of hundreds of people, but a wait list of hundreds of people, but it is what it is, folks. If you snooze, it is what it is, folks. If you snooze, it is what it is, folks. If you snooze, you lose and top tier speakers are you lose and top tier speakers are you lose and top tier speakers are coming. Uh it's going to be great. We'll coming. Uh it's going to be great. We'll coming. Uh it's going to be great. We'll get a an update from But I think Brad, get a an update from But I think Brad, get a an update from But I think Brad, you're going to be joining us again. you're going to be joining us again. you're going to be joining us again. Yes. For liquidity. Yes. For liquidity. Yes. For liquidity. >> I have an update. >> I have an update. >> I have an update. >> That's probably not your headliner, >> That's probably not your headliner, >> That's probably not your headliner, though. I'm probably not your headliner. though. I'm probably not your headliner. though. I'm probably not your headliner. >> No, but you always score so high. Every >> No, but you always score so high. Every >> No, but you always score so high. Every event you've spoken at, you've been event you've spoken at, you've been event you've spoken at, you've been either number one, two, I don't think either number one, two, I don't think either number one, two, I don't think you've ever dropped to three. Go ahead, you've ever dropped to three. Go ahead, you've ever dropped to three. Go ahead, Sham. Make your announcement here. Sham. Make your announcement here. Sham. Make your announcement here. >> Nat sent me an article from Wikipedia >> Nat sent me an article from Wikipedia >> Nat sent me an article from Wikipedia about penile links when you guys are about penile links when you guys are about penile links when you guys are talking about talking about talking about >> breaking news. >> breaking news. >> breaking news. >> Showing me showing me that I'm in the >> Showing me showing me that I'm in the >> Showing me showing me that I'm in the large category. Top 5%. She highlighted large category. Top 5%. She highlighted large category. Top 5%. She highlighted it. it. it. >> Top 5%. Okay. And that's with Is that >> Top 5%. Okay. And that's with Is that >> Top 5%. Okay. And that's with Is that with Nano Banana or without? Is that with Nano Banana or without? Is that with Nano Banana or without? Is that >> She just texted dummy. It's clogged. My >> She just texted dummy. It's clogged. My >> She just texted dummy. It's clogged. My apologies. Clogged. apologies. Clogged. apologies. Clogged. >> Oh. >> Oh. >> Oh. >> All right. This is why Jamath isn't >> All right. This is why Jamath isn't >> All right. This is why Jamath isn't afraid of the cyber is because nothing's afraid of the cyber is because nothing's afraid of the cyber is because nothing's going to come out that's more going to come out that's more going to come out that's more embarrassing than what he says himself embarrassing than what he says himself embarrassing than what he says himself on the box. on the box. on the box. >> He's like Bezos. When Bezos got hacked, >> He's like Bezos. When Bezos got hacked, >> He's like Bezos. When Bezos got hacked, HE'S LIKE, "GUYS, I GOT HACKED." HE'S LIKE, "GUYS, I GOT HACKED." HE'S LIKE, "GUYS, I GOT HACKED." >> SO, I saw the agenda for this thing. >> SO, I saw the agenda for this thing. >> SO, I saw the agenda for this thing. It's incredible. Congrats to you guys. I It's incredible. Congrats to you guys. I It's incredible. Congrats to you guys. I mean, like the uh like just the fun of mean, like the uh like just the fun of mean, like the uh like just the fun of being in Napa, all the poker, all the being in Napa, all the poker, all the being in Napa, all the poker, all the the dining experience. This is five star the dining experience. This is five star the dining experience. This is five star all the It looks really all the It looks really all the It looks really >> six-star. It's a man level because >> six-star. It's a man level because >> six-star. It's a man level because Chimath Chimath Chimath >> was, I dare I say, belligerent in his >> was, I dare I say, belligerent in his >> was, I dare I say, belligerent in his demands. He said, "This has to be demands. He said, "This has to be demands. He said, "This has to be six-star or I will not show up." Jake six-star or I will not show up." Jake six-star or I will not show up." Jake Al. I said, "Okay, boss, get to work." Al. I said, "Okay, boss, get to work." Al. I said, "Okay, boss, get to work." And uh, Chimath, what do you got any? No And uh, Chimath, what do you got any? No And uh, Chimath, what do you got any? No mids. This is all elite. And for the mids. This is all elite. And for the mids. This is all elite. And for the hundreds of people who are on the wait hundreds of people who are on the wait hundreds of people who are on the wait list, I am sorry, but we have a capacity list, I am sorry, but we have a capacity list, I am sorry, but we have a capacity issue. We'll try to get you in for next issue. We'll try to get you in for next issue. We'll try to get you in for next year. But Chim, give us some updates year. But Chim, give us some updates year. But Chim, give us some updates here. You have any updates that you want here. You have any updates that you want here. You have any updates that you want to share? because you are running to share? because you are running to share? because you are running programming for liquidity 2026 up in programming for liquidity 2026 up in programming for liquidity 2026 up in Yon. Yon. Yon. >> Look, it's going really well. >> Look, it's going really well. >> Look, it's going really well. Really excited to hear all of these Really excited to hear all of these Really excited to hear all of these great folks speak. I think the next two great folks speak. I think the next two great folks speak. I think the next two will release today. Brad Gersonner and will release today. Brad Gersonner and will release today. Brad Gersonner and Thomas Leaf of COTU Thomas Leaf of COTU Thomas Leaf of COTU >> of CO2. That's a great get. >> of CO2. That's a great get. >> of CO2. That's a great get. >> We also have I think three people >> We also have I think three people >> We also have I think three people confirmed for their best ideas pitch. confirmed for their best ideas pitch. confirmed for their best ideas pitch. Really interesting folks. They each run Really interesting folks. They each run Really interesting folks. They each run between one and six or seven billion between one and six or seven billion between one and six or seven billion >> awesome >> awesome >> awesome >> superstar compounders early in their >> superstar compounders early in their >> superstar compounders early in their career. career. career. >> This is a new zone chamat. >> This is a new zone chamat. >> This is a new zone chamat. >> It's great. So right now we have Bill >> It's great. So right now we have Bill >> It's great. So right now we have Bill Aman, we have Andre Carpathy, we have Aman, we have Andre Carpathy, we have Aman, we have Andre Carpathy, we have Dan Loe, we have Thomas Lefont, we have Dan Loe, we have Thomas Lefont, we have Dan Loe, we have Thomas Lefont, we have Brad Gersner, we have Sarah Frier and Brad Gersner, we have Sarah Frier and Brad Gersner, we have Sarah Frier and more to come. We will announce more. more to come. We will announce more. more to come. We will announce more. >> There might be one or two surprises. Jay >> There might be one or two surprises. Jay >> There might be one or two surprises. Jay Cal Cal Cal >> and a couple and a couple of surprises. >> and a couple and a couple of surprises. >> and a couple and a couple of surprises. >> Yeah, we we don't announce all the >> Yeah, we we don't announce all the >> Yeah, we we don't announce all the speakers. Jay Cal's got a couple of speakers. Jay Cal's got a couple of speakers. Jay Cal's got a couple of surprises coming. And if you didn't get surprises coming. And if you didn't get surprises coming. And if you didn't get in to liquidity, apologies. You're on in to liquidity, apologies. You're on in to liquidity, apologies. You're on the wait list. We are going to be the wait list. We are going to be the wait list. We are going to be hosting the fifth hosting the fifth hosting the fifth annual all-in summit in Los Angeles annual all-in summit in Los Angeles annual all-in summit in Los Angeles September 13th to the 15th of Sax. You September 13th to the 15th of Sax. You September 13th to the 15th of Sax. You going to come to that? going to come to that? going to come to that? >> Allin.com/events. >> Allin.com/events. >> Allin.com/events. >> Sax, you should come to that. >> Sax, you should come to that. >> Sax, you should come to that. >> I've been advised that I can attend >> I've been advised that I can attend >> I've been advised that I can attend business. I can be in the state for business. I can be in the state for business. I can be in the state for business reasons. business reasons. business reasons. >> Okay, there you go. Then we'll see you >> Okay, there you go. Then we'll see you >> Okay, there you go. Then we'll see you at liquidity and the summit. Correct. at liquidity and the summit. Correct. at liquidity and the summit. Correct. That's that's big news. Now we just got That's that's big news. Now we just got That's that's big news. Now we just got a bunch of Sachs stands who are racing. a bunch of Sachs stands who are racing. a bunch of Sachs stands who are racing. Uh and now we're going to get Sachs at Uh and now we're going to get Sachs at Uh and now we're going to get Sachs at This is what happens every year behind This is what happens every year behind This is what happens every year behind the scenes. the scenes. the scenes. >> Sachs at the last minute says, "Oh, I >> Sachs at the last minute says, "Oh, I >> Sachs at the last minute says, "Oh, I have four speakers and I have 72 people have four speakers and I have 72 people have four speakers and I have 72 people who need tickets and then the whole team who need tickets and then the whole team who need tickets and then the whole team has to like do a fire drill 48 hours has to like do a fire drill 48 hours has to like do a fire drill 48 hours before the event." Okay, here we go, before the event." Okay, here we go, before the event." Okay, here we go, guys. We're going to go to the third guys. We're going to go to the third guys. We're going to go to the third rail here. We got to catch up on the rail here. We got to catch up on the rail here. We got to catch up on the Iran war. Here's the latest. Two weeks Iran war. Here's the latest. Two weeks Iran war. Here's the latest. Two weeks into a ceasefire have started just two into a ceasefire have started just two into a ceasefire have started just two days ago at the taping of this VP JD days ago at the taping of this VP JD days ago at the taping of this VP JD Vance, friend of the pod is a and some Vance, friend of the pod is a and some Vance, friend of the pod is a and some special consultants Wikoff and friend of special consultants Wikoff and friend of special consultants Wikoff and friend of the pod Jared Kushner are headed to the pod Jared Kushner are headed to the pod Jared Kushner are headed to Islamabad, the capital of Pakistan for Islamabad, the capital of Pakistan for Islamabad, the capital of Pakistan for talks this very weekend. So while you're talks this very weekend. So while you're talks this very weekend. So while you're listening to this event, they are going listening to this event, they are going listening to this event, they are going to be working on the peace deal. Easter to be working on the peace deal. Easter to be working on the peace deal. Easter Sunday, Trump posted a truth stating, Sunday, Trump posted a truth stating, Sunday, Trump posted a truth stating, "Open the straight, you crazy "Open the straight, you crazy "Open the straight, you crazy bastards, or you're going to be living bastards, or you're going to be living bastards, or you're going to be living in hell. Just watch." Praise be to in hell. Just watch." Praise be to in hell. Just watch." Praise be to Allah. On Tuesday morning, Trump posted Allah. On Tuesday morning, Trump posted Allah. On Tuesday morning, Trump posted uh a another threat on social media. A uh a another threat on social media. A uh a another threat on social media. A whole civilization will die tonight. whole civilization will die tonight. whole civilization will die tonight. Never to be brought back again. I don't Never to be brought back again. I don't Never to be brought back again. I don't want that to happen, but it probably want that to happen, but it probably want that to happen, but it probably will. Tweets were obviously discussed uh will. Tweets were obviously discussed uh will. Tweets were obviously discussed uh a lot over the last week. He gave him an a lot over the last week. He gave him an a lot over the last week. He gave him an 8:00 p.m. deadline. 8:00 p.m. deadline. 8:00 p.m. deadline. At 6:30 p.m. POTUS announced on Truth At 6:30 p.m. POTUS announced on Truth At 6:30 p.m. POTUS announced on Truth Social that he had agreed. President Social that he had agreed. President Social that he had agreed. President Trump had agreed to a two-week ceasefire Trump had agreed to a two-week ceasefire Trump had agreed to a two-week ceasefire if Iran opens the straight. He also if Iran opens the straight. He also if Iran opens the straight. He also said, "Hey, listen. We got the straight. said, "Hey, listen. We got the straight. said, "Hey, listen. We got the straight. Maybe there'll be a toll booth, but Maybe there'll be a toll booth, but Maybe there'll be a toll booth, but we'll take the majority of the toll and we'll take the majority of the toll and we'll take the majority of the toll and we'll split it with Iran." Here's the we'll split it with Iran." Here's the we'll split it with Iran." Here's the quote. We received a 10-point proposal quote. We received a 10-point proposal quote. We received a 10-point proposal from Iran, and we believe it's a from Iran, and we believe it's a from Iran, and we believe it's a workable it is a workable basis on which workable it is a workable basis on which workable it is a workable basis on which to negotiate. And apparently Netanyahu to negotiate. And apparently Netanyahu to negotiate. And apparently Netanyahu took the ceasefire to mean level Lebanon took the ceasefire to mean level Lebanon took the ceasefire to mean level Lebanon dropping 160 bombs in 10 minutes dropping 160 bombs in 10 minutes dropping 160 bombs in 10 minutes yesterday. Saxs, uh, you were out last yesterday. Saxs, uh, you were out last yesterday. Saxs, uh, you were out last week. Everybody wants to know your week. Everybody wants to know your week. Everybody wants to know your position on the war. I'll hand it off to position on the war. I'll hand it off to position on the war. I'll hand it off to you. What are your thoughts on how on you. What are your thoughts on how on you. What are your thoughts on how on the two ceasefire and everything that's the two ceasefire and everything that's the two ceasefire and everything that's occurred up until this point? occurred up until this point? occurred up until this point? >> Well, look, I have to preface what I'm >> Well, look, I have to preface what I'm >> Well, look, I have to preface what I'm about to say, which is I'm not part of about to say, which is I'm not part of about to say, which is I'm not part of the foreign policy team at the White the foreign policy team at the White the foreign policy team at the White House. And the last time I commented on House. And the last time I commented on House. And the last time I commented on the war on this show, it somehow made the war on this show, it somehow made the war on this show, it somehow made international headlines that Trump international headlines that Trump international headlines that Trump advisor says XYZ. advisor says XYZ. advisor says XYZ. And I'm not a Trump adviser on this And I'm not a Trump adviser on this And I'm not a Trump adviser on this issue. I think that'd be a fair headline issue. I think that'd be a fair headline issue. I think that'd be a fair headline to write if it was a technology issue, to write if it was a technology issue, to write if it was a technology issue, but this is not. So whatever I say is but this is not. So whatever I say is but this is not. So whatever I say is just my personal opinion, but then the just my personal opinion, but then the just my personal opinion, but then the media is going to somehow portray it or media is going to somehow portray it or media is going to somehow portray it or attribute it attribute it attribute it >> to the White House or try and create an >> to the White House or try and create an >> to the White House or try and create an issue out of it. So, I feel like I'm issue out of it. So, I feel like I'm issue out of it. So, I feel like I'm limited in what I can say except that to limited in what I can say except that to limited in what I can say except that to say that I think it's terrific that we say that I think it's terrific that we say that I think it's terrific that we have the ceasefire. I think it's great have the ceasefire. I think it's great have the ceasefire. I think it's great that there's going to be this meeting in that there's going to be this meeting in that there's going to be this meeting in Islamabad to hammer it out. And I think Islamabad to hammer it out. And I think Islamabad to hammer it out. And I think what the president's accomplished so far what the president's accomplished so far what the president's accomplished so far with the ceasefire is it's a great thing with the ceasefire is it's a great thing with the ceasefire is it's a great thing because what happens with these wars is because what happens with these wars is because what happens with these wars is they take on a life of their own, they take on a life of their own, they take on a life of their own, meaning they tend to go up the meaning they tend to go up the meaning they tend to go up the escalation ladder, right? And there's a escalation ladder, right? And there's a escalation ladder, right? And there's a lot of podcasts that are discussing the lot of podcasts that are discussing the lot of podcasts that are discussing the so-called escalation trap and supposedly so-called escalation trap and supposedly so-called escalation trap and supposedly there are stages to this based on there are stages to this based on there are stages to this based on historical patterns. And so I think it's historical patterns. And so I think it's historical patterns. And so I think it's actually very hard to pull out of these actually very hard to pull out of these actually very hard to pull out of these things and I give the president things and I give the president things and I give the president tremendous credit for negotiating the tremendous credit for negotiating the tremendous credit for negotiating the ceasefire that we've achieved so far and ceasefire that we've achieved so far and ceasefire that we've achieved so far and then sending the team to hopefully work then sending the team to hopefully work then sending the team to hopefully work this out. this out. this out. >> Brad, actually my first trip to the >> Brad, actually my first trip to the >> Brad, actually my first trip to the Middle East was when you and I uh maybe Middle East was when you and I uh maybe Middle East was when you and I uh maybe four years ago when Thank you for taking four years ago when Thank you for taking four years ago when Thank you for taking me. What is your take on where we're at me. What is your take on where we're at me. What is your take on where we're at here? I think we're just wrapped up week here? I think we're just wrapped up week here? I think we're just wrapped up week six of this and we're going into week six of this and we're going into week six of this and we're going into week seven. seven. seven. >> First, on March 4th, I tweeted the Trump >> First, on March 4th, I tweeted the Trump >> First, on March 4th, I tweeted the Trump doctrine in Iran. Massively destroy all doctrine in Iran. Massively destroy all doctrine in Iran. Massively destroy all military capa capabilities. Kill the military capa capabilities. Kill the military capa capabilities. Kill the people building lethal weapons to use people building lethal weapons to use people building lethal weapons to use against us and get out. Reserve the against us and get out. Reserve the against us and get out. Reserve the right to do it again if needed. Zero right to do it again if needed. Zero right to do it again if needed. Zero efforts to build Misonian democracy. efforts to build Misonian democracy. efforts to build Misonian democracy. Iran's going to have to build what comes Iran's going to have to build what comes Iran's going to have to build what comes next. And I think what the market has next. And I think what the market has next. And I think what the market has said right if you look back at last year said right if you look back at last year said right if you look back at last year on tariffs Jason the top tobottom draw on tariffs Jason the top tobottom draw on tariffs Jason the top tobottom draw down was about 15% on the NASDAQ down was about 15% on the NASDAQ down was about 15% on the NASDAQ intraday is down 22%. intraday is down 22%. intraday is down 22%. Okay, the draw down in this period over Okay, the draw down in this period over Okay, the draw down in this period over Iran was only down about 5 to 7% on S&P Iran was only down about 5 to 7% on S&P Iran was only down about 5 to 7% on S&P and NASDAQ, right? So, the market has and NASDAQ, right? So, the market has and NASDAQ, right? So, the market has said, listen, re trust Trump at his said, listen, re trust Trump at his said, listen, re trust Trump at his words. He said he's not going to get words. He said he's not going to get words. He said he's not going to get into an entangled war here. I think he into an entangled war here. I think he into an entangled war here. I think he terrifies the hell out of people with terrifies the hell out of people with terrifies the hell out of people with his tweets about, you know, destroying his tweets about, you know, destroying his tweets about, you know, destroying civilization and all this other stuff. civilization and all this other stuff. civilization and all this other stuff. But I think people, even though they But I think people, even though they But I think people, even though they don't like to hear it, they've resolved don't like to hear it, they've resolved don't like to hear it, they've resolved for themselves that when he says he's for themselves that when he says he's for themselves that when he says he's going to get out, he will in fact get going to get out, he will in fact get going to get out, he will in fact get out. Of course, there was a lot of hand out. Of course, there was a lot of hand out. Of course, there was a lot of hand ringing, but if you look at the markets ringing, but if you look at the markets ringing, but if you look at the markets today, we basically bounced all the way today, we basically bounced all the way today, we basically bounced all the way back from where we were pre-Iran on both back from where we were pre-Iran on both back from where we were pre-Iran on both the S&P and the NASDAQ. If in fact we the S&P and the NASDAQ. If in fact we the S&P and the NASDAQ. If in fact we land the plane, if JD lands the plane, land the plane, if JD lands the plane, land the plane, if JD lands the plane, and by the way, on Lebanon, yes, they and by the way, on Lebanon, yes, they and by the way, on Lebanon, yes, they were bombing yesterday, but Netanyahu were bombing yesterday, but Netanyahu were bombing yesterday, but Netanyahu has now said that you're going to have has now said that you're going to have has now said that you're going to have direct government talks between Israel direct government talks between Israel direct government talks between Israel and Lebanon. So, if the if we land the and Lebanon. So, if the if we land the and Lebanon. So, if the if we land the plane on these two things, I think it's plane on these two things, I think it's plane on these two things, I think it's off to the races in the market. By the off to the races in the market. By the off to the races in the market. By the way, while everybody's focused on Iran, way, while everybody's focused on Iran, way, while everybody's focused on Iran, stay tuned. I think we're getting close stay tuned. I think we're getting close stay tuned. I think we're getting close to a deal on Ukraine, Russia, right? to a deal on Ukraine, Russia, right? to a deal on Ukraine, Russia, right? Venezuela is, you know, kind of going Venezuela is, you know, kind of going Venezuela is, you know, kind of going seemingly very well. I think there's seemingly very well. I think there's seemingly very well. I think there's also going to be news on Cuba. You could also going to be news on Cuba. You could also going to be news on Cuba. You could envision a world there's risk to the envision a world there's risk to the envision a world there's risk to the downside. Certainly, I will stipulate, downside. Certainly, I will stipulate, downside. Certainly, I will stipulate, but you also have to pay attention to but you also have to pay attention to but you also have to pay attention to the risk to the upside. If you land the the risk to the upside. If you land the the risk to the upside. If you land the plane on those things heading into plane on those things heading into plane on those things heading into America 250 July 4th, the market could America 250 July 4th, the market could America 250 July 4th, the market could really take off. really take off. really take off. >> All right. Well, let's uh maybe uplevel >> All right. Well, let's uh maybe uplevel >> All right. Well, let's uh maybe uplevel this a little bit and talk about why this a little bit and talk about why this a little bit and talk about why we're in this war to begin with. And we're in this war to begin with. And we're in this war to begin with. And that's the big discussion amongst both that's the big discussion amongst both that's the big discussion amongst both sides of the aisle. On Tuesday, the New sides of the aisle. On Tuesday, the New sides of the aisle. On Tuesday, the New York Times dropped an inside the room York Times dropped an inside the room York Times dropped an inside the room piece on how President Trump made the piece on how President Trump made the piece on how President Trump made the decision decision decision according to this report, if it's true. according to this report, if it's true. according to this report, if it's true. I know some people don't uh subscribe to I know some people don't uh subscribe to I know some people don't uh subscribe to the New York Times anymore or think it's the New York Times anymore or think it's the New York Times anymore or think it's fake news, but how Trump decided to fake news, but how Trump decided to fake news, but how Trump decided to basically follow Netanyahu into this basically follow Netanyahu into this basically follow Netanyahu into this war. On February 11th, Netanyahu met war. On February 11th, Netanyahu met war. On February 11th, Netanyahu met with Trump at the White House where he with Trump at the White House where he with Trump at the White House where he gave him a four-part pitch on attacking gave him a four-part pitch on attacking gave him a four-part pitch on attacking Iran. JD Vance, according to the story, Iran. JD Vance, according to the story, Iran. JD Vance, according to the story, if it's true, disclaimer, disclaimer, if it's true, disclaimer, disclaimer, if it's true, disclaimer, disclaimer, warned Trump that the war could cause warned Trump that the war could cause warned Trump that the war could cause regional chaos and break apart Trump's regional chaos and break apart Trump's regional chaos and break apart Trump's MAGA 2.0, the Trump 2.0 coalition we MAGA 2.0, the Trump 2.0 coalition we MAGA 2.0, the Trump 2.0 coalition we talked about here, the big tent. And talked about here, the big tent. And talked about here, the big tent. And that's turned out actually to be true. that's turned out actually to be true. that's turned out actually to be true. There's been a bunch of hand ringing There's been a bunch of hand ringing There's been a bunch of hand ringing from Megan, Kelly, Tucker, Carlson, from Megan, Kelly, Tucker, Carlson, from Megan, Kelly, Tucker, Carlson, right on down the line. Rubio was right on down the line. Rubio was right on down the line. Rubio was anti-regime change, but he was largely anti-regime change, but he was largely anti-regime change, but he was largely ambivalent, according to this story ambivalent, according to this story ambivalent, according to this story about the bombing campaign. Susie Wilds, about the bombing campaign. Susie Wilds, about the bombing campaign. Susie Wilds, chief of staff, said she had concerns chief of staff, said she had concerns chief of staff, said she had concerns about gas prices before the midterms. about gas prices before the midterms. about gas prices before the midterms. Pretty good uh advice there. And General Pretty good uh advice there. And General Pretty good uh advice there. And General Dan Kaine, chairman of the Joint Chiefs Dan Kaine, chairman of the Joint Chiefs Dan Kaine, chairman of the Joint Chiefs of Staff, said this of Netanyahu's of Staff, said this of Netanyahu's of Staff, said this of Netanyahu's pitch. Quote, "Sir, this is, in my pitch. Quote, "Sir, this is, in my pitch. Quote, "Sir, this is, in my experience, standard operating procedure experience, standard operating procedure experience, standard operating procedure for the Israelis. They oversell and for the Israelis. They oversell and for the Israelis. They oversell and their plans are not always their plans are not always their plans are not always well-developed. They know they need us well-developed. They know they need us well-developed. They know they need us and that's why they're hard selling. If and that's why they're hard selling. If and that's why they're hard selling. If you put this together with Rubio's you put this together with Rubio's you put this together with Rubio's walked back comments at the start of the walked back comments at the start of the walked back comments at the start of the war, we knew, this is quote from Rubio, war, we knew, this is quote from Rubio, war, we knew, this is quote from Rubio, we knew there was going to be an Israeli we knew there was going to be an Israeli we knew there was going to be an Israeli action. We knew that would precipitate action. We knew that would precipitate action. We knew that would precipitate an attack against American forces and an attack against American forces and an attack against American forces and that's why we did it. I had Josh Shapiro that's why we did it. I had Josh Shapiro that's why we did it. I had Josh Shapiro on the All-In interview show and um uh on the All-In interview show and um uh on the All-In interview show and um uh he talked a lot about this. There is a he talked a lot about this. There is a he talked a lot about this. There is a big underpinning here, Chimath, that the big underpinning here, Chimath, that the big underpinning here, Chimath, that the United States foreign policy is being United States foreign policy is being United States foreign policy is being driven by Netanyahu. Every Jewish driven by Netanyahu. Every Jewish driven by Netanyahu. Every Jewish American person I've talked to feels American person I've talked to feels American person I've talked to feels Netanyahu is not doing Jewish American Netanyahu is not doing Jewish American Netanyahu is not doing Jewish American and Jewish the Jewish diaspora any and Jewish the Jewish diaspora any and Jewish the Jewish diaspora any favors here by his approach to these favors here by his approach to these favors here by his approach to these wars. What are your thoughts on why we wars. What are your thoughts on why we wars. What are your thoughts on why we got into this and how we get out of it? got into this and how we get out of it? got into this and how we get out of it? >> I mean, the person that decides is the >> I mean, the person that decides is the >> I mean, the person that decides is the president of the United States. some president of the United States. some president of the United States. some foreign leader isn't foreign leader isn't foreign leader isn't getting to call the shots in the United getting to call the shots in the United getting to call the shots in the United States. I think very practically States. I think very practically States. I think very practically speaking, speaking, speaking, the markets are effectively the markets are effectively the markets are effectively pricing in that this was a small blip pricing in that this was a small blip pricing in that this was a small blip for whatever people think. That's just for whatever people think. That's just for whatever people think. That's just what the best prediction market that we what the best prediction market that we what the best prediction market that we have is telling us. I think that's have is telling us. I think that's have is telling us. I think that's important to acknowledge that we're important to acknowledge that we're important to acknowledge that we're probably in the endgame here. And the probably in the endgame here. And the probably in the endgame here. And the second thing to acknowledge is if I was second thing to acknowledge is if I was second thing to acknowledge is if I was Israel, I would really be concerned Israel, I would really be concerned Israel, I would really be concerned that unless I help find an offramp that unless I help find an offramp that unless I help find an offramp quickly, the risk that Israel loses quickly, the risk that Israel loses quickly, the risk that Israel loses America as a predictably steadfast ally America as a predictably steadfast ally America as a predictably steadfast ally could go down. And I think that that's could go down. And I think that that's could go down. And I think that that's problematic for Israel problematic for Israel problematic for Israel >> far more than is problematic for the >> far more than is problematic for the >> far more than is problematic for the United States. United States. United States. >> So all of that kind of tells me that we >> So all of that kind of tells me that we >> So all of that kind of tells me that we will find an offramp. A because I think will find an offramp. A because I think will find an offramp. A because I think economically it makes sense and then B economically it makes sense and then B economically it makes sense and then B geopolitically I think Israel will want geopolitically I think Israel will want geopolitically I think Israel will want to make sure that this doesn't burn to make sure that this doesn't burn to make sure that this doesn't burn a long-standing relationship. a long-standing relationship. a long-standing relationship. >> Yeah, that that seems to me to be the >> Yeah, that that seems to me to be the >> Yeah, that that seems to me to be the major issue here is Americans basically major issue here is Americans basically major issue here is Americans basically do not want to be in this war. Americans do not want to be in this war. Americans do not want to be in this war. Americans do not want a forest policy being do not want a forest policy being do not want a forest policy being influenced to the extent they believe. influenced to the extent they believe. influenced to the extent they believe. I'm not putting my belief in here. I'm not putting my belief in here. I'm not putting my belief in here. Americans believe we are being dragged Americans believe we are being dragged Americans believe we are being dragged into this by Israel and that Israel has into this by Israel and that Israel has into this by Israel and that Israel has too much or Netanyahu specifically has too much or Netanyahu specifically has too much or Netanyahu specifically has far too much influence. And then people far too much influence. And then people far too much influence. And then people believe the anti-semitism that's believe the anti-semitism that's believe the anti-semitism that's occurring here. Josh Shapiro gave me a occurring here. Josh Shapiro gave me a occurring here. Josh Shapiro gave me a lot of push back on this. Uh but all the lot of push back on this. Uh but all the lot of push back on this. Uh but all the Jewish Americans I talked to say Jewish Americans I talked to say Jewish Americans I talked to say Netanyahu is causing with his actions in Netanyahu is causing with his actions in Netanyahu is causing with his actions in Gaza, Lebanon, Iran. Uh he's gone too Gaza, Lebanon, Iran. Uh he's gone too Gaza, Lebanon, Iran. Uh he's gone too far and it's causing the anti-semitism far and it's causing the anti-semitism far and it's causing the anti-semitism we're experiencing uh today. So you can we're experiencing uh today. So you can we're experiencing uh today. So you can make your own decisions about that. Any make your own decisions about that. Any make your own decisions about that. Any final thoughts here, Brad, on final thoughts here, Brad, on final thoughts here, Brad, on the American foreign policy being the American foreign policy being the American foreign policy being influenced too much by Israel? influenced too much by Israel? influenced too much by Israel? >> No, it's the discussion. I >> No, it's the discussion. I >> No, it's the discussion. I >> I mean, listen, um kind of like Sax said >> I mean, listen, um kind of like Sax said >> I mean, listen, um kind of like Sax said earlier, um I think that we will earlier, um I think that we will earlier, um I think that we will ultimately be judged by the outcomes, ultimately be judged by the outcomes, ultimately be judged by the outcomes, right? And that everybody is an armchair right? And that everybody is an armchair right? And that everybody is an armchair pundit today on, you know, uh the the pundit today on, you know, uh the the pundit today on, you know, uh the the the approach that we're taking in these the approach that we're taking in these the approach that we're taking in these two different places. I think we could two different places. I think we could two different places. I think we could be on the verge of a massive be on the verge of a massive be on the verge of a massive transformation of the Gulf States. You transformation of the Gulf States. You transformation of the Gulf States. You went there with me, Jason. Saudi, went there with me, Jason. Saudi, went there with me, Jason. Saudi, Qataris, Kuwaitis, Emiratis. I've talked Qataris, Kuwaitis, Emiratis. I've talked Qataris, Kuwaitis, Emiratis. I've talked to a lot of them this week. I think to a lot of them this week. I think to a lot of them this week. I think they're very hopeful and optimistic. I they're very hopeful and optimistic. I they're very hopeful and optimistic. I think you could bring Iran into the think you could bring Iran into the think you could bring Iran into the fold. But listen, I'm an optimist on all fold. But listen, I'm an optimist on all fold. But listen, I'm an optimist on all of this stuff. I I just want to remind of this stuff. I I just want to remind of this stuff. I I just want to remind people, doing nothing in Iran had people, doing nothing in Iran had people, doing nothing in Iran had tremendous risks. Doing nothing in tremendous risks. Doing nothing in tremendous risks. Doing nothing in Venezuela had tremendous risks. So, it's Venezuela had tremendous risks. So, it's Venezuela had tremendous risks. So, it's not as though this was uh, you know, not as though this was uh, you know, not as though this was uh, you know, something that I I I I think wasn't well something that I I I I think wasn't well something that I I I I think wasn't well calculated, but I think we have to let calculated, but I think we have to let calculated, but I think we have to let the cards be played and and and then let the cards be played and and and then let the cards be played and and and then let history be the judge. But I think history be the judge. But I think history be the judge. But I think there's uh a risk in both directions, there's uh a risk in both directions, there's uh a risk in both directions, but I'm going to remain optimistic. but I'm going to remain optimistic. but I'm going to remain optimistic. >> All right. You uh said in the Gaza >> All right. You uh said in the Gaza >> All right. You uh said in the Gaza situation, we should have a wide birth situation, we should have a wide birth situation, we should have a wide birth for criticism of Israel and Netanyahu. for criticism of Israel and Netanyahu. for criticism of Israel and Netanyahu. What are your thoughts on this belief What are your thoughts on this belief What are your thoughts on this belief here in the United States now in this here in the United States now in this here in the United States now in this discussion that Israel is having far too discussion that Israel is having far too discussion that Israel is having far too much influence over the United States much influence over the United States much influence over the United States foreign policy? foreign policy? foreign policy? Well, I noticed in my feed today that Well, I noticed in my feed today that Well, I noticed in my feed today that Naftali Bennett, who's a major Israeli Naftali Bennett, who's a major Israeli Naftali Bennett, who's a major Israeli politician who was a former prime politician who was a former prime politician who was a former prime minister, tweeted polling that showed minister, tweeted polling that showed minister, tweeted polling that showed that Israel was becoming very unpopular that Israel was becoming very unpopular that Israel was becoming very unpopular in the US and he was expressing concern in the US and he was expressing concern in the US and he was expressing concern about that and expressing about that and expressing about that and expressing the need to to basically address that or the need to to basically address that or the need to to basically address that or fix that. So, I think you're starting to fix that. So, I think you're starting to fix that. So, I think you're starting to see Israeli politicians raising that as see Israeli politicians raising that as see Israeli politicians raising that as an issue. And I think that's probably a an issue. And I think that's probably a an issue. And I think that's probably a good thing. Yeah, there it is. And it's good thing. Yeah, there it is. And it's good thing. Yeah, there it is. And it's really cool actually how X now just really cool actually how X now just really cool actually how X now just automatically translates things from automatically translates things from automatically translates things from foreign languages, in this case, Hebrew, foreign languages, in this case, Hebrew, foreign languages, in this case, Hebrew, and it puts it in your feed. So, yeah. and it puts it in your feed. So, yeah. and it puts it in your feed. So, yeah. So, here's Naftali Bennett, former prime So, here's Naftali Bennett, former prime So, here's Naftali Bennett, former prime minister, saying, "This is a serious minister, saying, "This is a serious minister, saying, "This is a serious situation. There's a lot of work ahead situation. There's a lot of work ahead situation. There's a lot of work ahead of us to fix everything." Now, of us to fix everything." Now, of us to fix everything." Now, obviously, this is not Netanyahu. this obviously, this is not Netanyahu. this obviously, this is not Netanyahu. this is one of his um political opponents. is one of his um political opponents. is one of his um political opponents. But But But yeah, I mean this is something for yeah, I mean this is something for yeah, I mean this is something for Israel to consider and think about and I Israel to consider and think about and I Israel to consider and think about and I think that they would improve their think that they would improve their think that they would improve their popularity uh if they got behind the popularity uh if they got behind the popularity uh if they got behind the ceasefire and I have no indication that ceasefire and I have no indication that ceasefire and I have no indication that they won't but that would certainly be a they won't but that would certainly be a they won't but that would certainly be a good place to start. I have to say just good place to start. I have to say just good place to start. I have to say just as an aside, this auto translate feature as an aside, this auto translate feature as an aside, this auto translate feature has done more for understanding across has done more for understanding across has done more for understanding across borders than anything I've ever seen. borders than anything I've ever seen. borders than anything I've ever seen. And it is the most impressive tech And it is the most impressive tech And it is the most impressive tech feature I I've seen released in years. feature I I've seen released in years. feature I I've seen released in years. Putting AI and large language models Putting AI and large language models Putting AI and large language models aside for people who don't know what's aside for people who don't know what's aside for people who don't know what's happening because of Grock being really happening because of Grock being really happening because of Grock being really good at doing auto translate. They've good at doing auto translate. They've good at doing auto translate. They've taken the pockets of the best of what's taken the pockets of the best of what's taken the pockets of the best of what's happening in Japan, what's happening in happening in Japan, what's happening in happening in Japan, what's happening in Israel, what's happening in France, and Israel, what's happening in France, and Israel, what's happening in France, and they're surfacing it auto translated. they're surfacing it auto translated. they're surfacing it auto translated. Then when you reply as an American to Then when you reply as an American to Then when you reply as an American to somebody in Japan, they see it autorated somebody in Japan, they see it autorated somebody in Japan, they see it autorated as well, which has led to people who as well, which has led to people who as well, which has led to people who don't speak the same language engaging don't speak the same language engaging don't speak the same language engaging on X in a very nuanced, fun, interesting on X in a very nuanced, fun, interesting on X in a very nuanced, fun, interesting way. And that for as a truth mechanism way. And that for as a truth mechanism way. And that for as a truth mechanism is just absolutely extraordinary. I is just absolutely extraordinary. I is just absolutely extraordinary. I think this is going to have such a think this is going to have such a think this is going to have such a profound effect. Maybe Elon and the X profound effect. Maybe Elon and the X profound effect. Maybe Elon and the X team should get like a Nobel Peace Prize team should get like a Nobel Peace Prize team should get like a Nobel Peace Prize award for this. I think it's going to award for this. I think it's going to award for this. I think it's going to change. I mean, I hate to be hyperbolic, change. I mean, I hate to be hyperbolic, change. I mean, I hate to be hyperbolic, but have you been using this feature, but have you been using this feature, but have you been using this feature, Chamat? Has it been coming up in your Chamat? Has it been coming up in your Chamat? Has it been coming up in your feed? And which language is up in your feed? And which language is up in your feed? And which language is up in your feed right now? feed right now? feed right now? >> English. Okay. So, you're not part of >> English. Okay. So, you're not part of >> English. Okay. So, you're not part of the translation thing. Brad, has this the translation thing. Brad, has this the translation thing. Brad, has this hit your feed yet? And and which regions hit your feed yet? And and which regions hit your feed yet? And and which regions are you? are you? are you? >> Definitely. Definitely see it in on the >> Definitely. Definitely see it in on the >> Definitely. Definitely see it in on the Middle East stuff. Um, and uh, you know, Middle East stuff. Um, and uh, you know, Middle East stuff. Um, and uh, you know, I've seen on Chinese, I've seen it on on I've seen on Chinese, I've seen it on on I've seen on Chinese, I've seen it on on the Russian Japanese the Russian Japanese the Russian Japanese >> super helpful. >> super helpful. >> super helpful. >> Let me tell you, bass Japanese is a >> Let me tell you, bass Japanese is a >> Let me tell you, bass Japanese is a whole another level of beast. whole another level of beast. whole another level of beast. >> Whoa. Man, base Japanese makes like >> Whoa. Man, base Japanese makes like >> Whoa. Man, base Japanese makes like Fentes and Alex Jones seem tame. They're Fentes and Alex Jones seem tame. They're Fentes and Alex Jones seem tame. They're like, look at this group of people. like, look at this group of people. like, look at this group of people. Insert whatever group of immigrants you Insert whatever group of immigrants you Insert whatever group of immigrants you like. And they're like, this is like. And they're like, this is like. And they're like, this is unacceptable behavior. This is not unacceptable behavior. This is not unacceptable behavior. This is not Japanese culture. These people need to Japanese culture. These people need to Japanese culture. These people need to be get the hell out of Japan. It is be get the hell out of Japan. It is be get the hell out of Japan. It is wild, folks. And if you don't have an X wild, folks. And if you don't have an X wild, folks. And if you don't have an X account, you are missing out. Go to account, you are missing out. Go to account, you are missing out. Go to X.com and sign up for this reason only X.com and sign up for this reason only X.com and sign up for this reason only because you think about the velocity. because you think about the velocity. because you think about the velocity. Like journalists are not even taking the Like journalists are not even taking the Like journalists are not even taking the time to translate and cover what's going time to translate and cover what's going time to translate and cover what's going on in those areas. And this is happening on in those areas. And this is happening on in those areas. And this is happening automatically in real time. automatically in real time. automatically in real time. >> So you start thinking about what >> So you start thinking about what >> So you start thinking about what happened in Ukraine. If you had people happened in Ukraine. If you had people happened in Ukraine. If you had people Russia and Ukraine doing this and having Russia and Ukraine doing this and having Russia and Ukraine doing this and having conversations with each other, it would conversations with each other, it would conversations with each other, it would be wild. be wild. be wild. >> You're like a such a good hype man. The >> You're like a such a good hype man. The >> You're like a such a good hype man. The problem is you hype buttered bread the problem is you hype buttered bread the problem is you hype buttered bread the same way you hype a nuclear reactor. And same way you hype a nuclear reactor. And same way you hype a nuclear reactor. And so it's hard to really tell, you know, so it's hard to really tell, you know, so it's hard to really tell, you know, what you're really hyping because your what you're really hyping because your what you're really hyping because your level of excitement, the intonation is level of excitement, the intonation is level of excitement, the intonation is exactly the same. exactly the same. exactly the same. >> Yo, man, there's nothing better than a >> Yo, man, there's nothing better than a >> Yo, man, there's nothing better than a slice of great toast. I mean, if this is slice of great toast. I mean, if this is slice of great toast. I mean, if this is very this in in a way, it is like sliced very this in in a way, it is like sliced very this in in a way, it is like sliced bread. It's very simple, but it is so bread. It's very simple, but it is so bread. It's very simple, but it is so powerful in the experience. powerful in the experience. powerful in the experience. >> This has been >> This has been >> This has been >> It is true. X is better today than it's >> It is true. X is better today than it's >> It is true. X is better today than it's ever been. And remember, they have 70% ever been. And remember, they have 70% ever been. And remember, they have 70% fewer employees than they had the day fewer employees than they had the day fewer employees than they had the day Elon walked into the building. And so if Elon walked into the building. And so if Elon walked into the building. And so if there were ever a debate there were ever a debate there were ever a debate >> about this, like, and I remember >> about this, like, and I remember >> about this, like, and I remember everybody saying, "Oh, it's going to tip everybody saying, "Oh, it's going to tip everybody saying, "Oh, it's going to tip over. Oh, it's going to be a crappy over. Oh, it's going to be a crappy over. Oh, it's going to be a crappy experience." experience." experience." >> The fact of the matter, here's we are a >> The fact of the matter, here's we are a >> The fact of the matter, here's we are a few years later, 70% fewer employees, few years later, 70% fewer employees, few years later, 70% fewer employees, and every other company in Silicon and every other company in Silicon and every other company in Silicon Valley is looking at that. I think for a Valley is looking at that. I think for a Valley is looking at that. I think for a lot of these tech companies, we've hit lot of these tech companies, we've hit lot of these tech companies, we've hit peak employment. We're going to create a peak employment. We're going to create a peak employment. We're going to create a tremendous number of new jobs, but for tremendous number of new jobs, but for tremendous number of new jobs, but for the existing jobs, these companies are the existing jobs, these companies are the existing jobs, these companies are all realizing they can do more with all realizing they can do more with all realizing they can do more with less. less. less. >> Nikita Beer just tweeted that they're >> Nikita Beer just tweeted that they're >> Nikita Beer just tweeted that they're about to go ham on these bot accounts about to go ham on these bot accounts about to go ham on these bot accounts that auto reply. that auto reply. that auto reply. >> Yes. >> Yes. >> Yes. >> Those those literally ruined my feed. >> Those those literally ruined my feed. >> Those those literally ruined my feed. >> That's why I went to subscriber mode in >> That's why I went to subscriber mode in >> That's why I went to subscriber mode in my replies and it's it's worked out my replies and it's it's worked out my replies and it's it's worked out great. great. great. >> Yeah. No, shout out to him and um to >> Yeah. No, shout out to him and um to >> Yeah. No, shout out to him and um to Chris Saka who was in tears at what Chris Saka who was in tears at what Chris Saka who was in tears at what happened to Twitter. You happened to Twitter. You happened to Twitter. You >> It's gonna be okay, Chris. Sorry. No >> It's gonna be okay, Chris. Sorry. No >> It's gonna be okay, Chris. Sorry. No more tears. more tears. more tears. You only let subscribers respond to your You only let subscribers respond to your You only let subscribers respond to your tweets. I tweets. I tweets. I >> I do 50/50. Sometimes I'll just let it >> I do 50/50. Sometimes I'll just let it >> I do 50/50. Sometimes I'll just let it rip and get chaos. And then other times rip and get chaos. And then other times rip and get chaos. And then other times I have 2,000 paid subscribers. I give I have 2,000 paid subscribers. I give I have 2,000 paid subscribers. I give all the money to charity, like 30 grand all the money to charity, like 30 grand all the money to charity, like 30 grand a year. And it's just wonderful to get a year. And it's just wonderful to get a year. And it's just wonderful to get to know the same 2,000 people out of my to know the same 2,000 people out of my to know the same 2,000 people out of my million followers. It's kind of like million followers. It's kind of like million followers. It's kind of like having this little subset. So sometimes having this little subset. So sometimes having this little subset. So sometimes I'm like, I don't have time to deal with I'm like, I don't have time to deal with I'm like, I don't have time to deal with a 100red or 200 or 300 replies. a 100red or 200 or 300 replies. a 100red or 200 or 300 replies. >> You have a million. That's incredible. I >> You have a million. That's incredible. I >> You have a million. That's incredible. I mean, it's just mean, it's just mean, it's just >> I mean, you have two million. I think >> I mean, you have two million. I think >> I mean, you have two million. I think Sax must have a million, right? You have Sax must have a million, right? You have Sax must have a million, right? You have a million, right, Sax? Only only a million, right, Sax? Only only a million, right, Sax? Only only >> Brad. How many you have now? You're >> Brad. How many you have now? You're >> Brad. How many you have now? You're getting popular. getting popular. getting popular. >> You built a couple. >> You built a couple. >> You built a couple. >> Got a couple hund. >> Got a couple hund. >> Got a couple hund. >> What's your Oh, your alt cap altca. >> What's your Oh, your alt cap altca. >> What's your Oh, your alt cap altca. >> I'm at 1.4 million. What are you at, >> I'm at 1.4 million. What are you at, >> I'm at 1.4 million. What are you at, Jacob? Have I surpassed you? Jacob? Have I surpassed you? Jacob? Have I surpassed you? >> I think you have. I'm like 1.1. >> I think you have. I'm like 1.1. >> I think you have. I'm like 1.1. >> What it cost me to get my real name, >> What it cost me to get my real name, >> What it cost me to get my real name, Jason? Jason? Jason? >> Uh, I know a guy. Find out. >> Uh, I know a guy. Find out. >> Uh, I know a guy. Find out. >> You're 1.1. Yeah, I made it to 1.4. I >> You're 1.1. Yeah, I made it to 1.4. I >> You're 1.1. Yeah, I made it to 1.4. I don't know how that happened exactly. don't know how that happened exactly. don't know how that happened exactly. >> Just having the number one podcast in >> Just having the number one podcast in >> Just having the number one podcast in the world. Uh, another amazing episode the world. Uh, another amazing episode the world. Uh, another amazing episode of the number one pop and Chimath has of the number one pop and Chimath has of the number one pop and Chimath has two million, but that's only because he two million, but that's only because he two million, but that's only because he engages he has just incredible moments engages he has just incredible moments engages he has just incredible moments of uh engaging with his haters. Oh my of uh engaging with his haters. Oh my of uh engaging with his haters. Oh my god, the the the replies that Chimath god, the the the replies that Chimath god, the the the replies that Chimath sometimes drops are so great. I love sometimes drops are so great. I love sometimes drops are so great. I love Chimoth goes Chimoth goes Chimoth goes >> I light them up. I light them up. >> I light them up. I light them up. >> I light them up. I light them up. >> He lights them up. Then you had somebody >> He lights them up. Then you had somebody >> He lights them up. Then you had somebody who was like, "Oh my god, I was in the who was like, "Oh my god, I was in the who was like, "Oh my god, I was in the casino and you told me to bet black, so casino and you told me to bet black, so casino and you told me to bet black, so you bet black, so I bet black and I lost you bet black, so I bet black and I lost you bet black, so I bet black and I lost my money." And so you're responsible and my money." And so you're responsible and my money." And so you're responsible and then you paid for the kids college. He then you paid for the kids college. He then you paid for the kids college. He has two young girls and so I I funded has two young girls and so I I funded has two young girls and so I I funded their college accounts. their college accounts. their college accounts. >> I thought that was hilarious. Just as >> I thought that was hilarious. Just as >> I thought that was hilarious. Just as >> obviously I'm very happy for him and his >> obviously I'm very happy for him and his >> obviously I'm very happy for him and his two daughters. I'm even more happy at two daughters. I'm even more happy at two daughters. I'm even more happy at how much it'll anger all these other how much it'll anger all these other how much it'll anger all these other goofball dorks living in their mom's goofball dorks living in their mom's goofball dorks living in their mom's basement. basement. basement. >> Yes. >> Yes. >> Yes. >> Who'd literally have no take they take >> Who'd literally have no take they take >> Who'd literally have no take they take no responsibility for their lives. no responsibility for their lives. no responsibility for their lives. And uh they should enjoy those Hot And uh they should enjoy those Hot And uh they should enjoy those Hot Pockets. By the way, for those folks in Pockets. By the way, for those folks in Pockets. By the way, for those folks in their mom's basement, the Hot Pockets their mom's basement, the Hot Pockets their mom's basement, the Hot Pockets and the Fish Sticks are ready and you and the Fish Sticks are ready and you and the Fish Sticks are ready and you get one more hour of Xbox from mom. get one more hour of Xbox from mom. get one more hour of Xbox from mom. >> All right, listen. We missed you, >> All right, listen. We missed you, >> All right, listen. We missed you, Freeberg, but this is the best episode Freeberg, but this is the best episode Freeberg, but this is the best episode in two years. Uh in two years. Uh in two years. Uh >> Freeird at the end of the show. >> Freeird at the end of the show. >> Freeird at the end of the show. >> And we will see you all at the liquidity >> And we will see you all at the liquidity >> And we will see you all at the liquidity summit except for the 400 people on the summit except for the 400 people on the summit except for the 400 people on the wait list who aren't going to get in. wait list who aren't going to get in. wait list who aren't going to get in. >> We got an email from the guys at Athena >> We got an email from the guys at Athena >> We got an email from the guys at Athena because we were just because we were just because we were just >> Oh my god. the they they're they're >> Oh my god. the they they're they're >> Oh my god. the they they're they're going to hire like 500 new Athena going to hire like 500 new Athena going to hire like 500 new Athena assistants. assistants. assistants. >> Yes, they had a thousand people after >> Yes, they had a thousand people after >> Yes, they had a thousand people after last week when we mentioned how much we last week when we mentioned how much we last week when we mentioned how much we love Athena. love Athena. love Athena. >> Go to Athena.com. >> Go to Athena.com. >> Go to Athena.com. >> But that's amazing. Those are like 500 >> But that's amazing. Those are like 500 >> But that's amazing. Those are like 500 hardworking men and women who are like hardworking men and women who are like hardworking men and women who are like working working working >> in the Philippines. >> in the Philippines. >> in the Philippines. >> Sax have great jobs. >> Sax have great jobs. >> Sax have great jobs. >> Sax, I'm going to get you a couple >> Sax, I'm going to get you a couple >> Sax, I'm going to get you a couple Athena assistants as a birthday present. Athena assistants as a birthday present. Athena assistants as a birthday present. That's what I'm going to get. That's what I'm going to get. That's what I'm going to get. >> You're going to love this, Sax. H Athena >> You're going to love this, Sax. H Athena >> You're going to love this, Sax. H Athena assistants are the best. Congratulations assistants are the best. Congratulations assistants are the best. Congratulations to my friends over there. All right, to my friends over there. All right, to my friends over there. All right, everybody. We'll see you next time. Love everybody. We'll see you next time. Love everybody. We'll see you next time. Love you boys on you boys on you boys on >> tonight favorite podcast. >> Let your winners ride. >> Let your winners ride. >> Rain and and >> we open source it to the fans and >> we open source it to the fans and >> we open source it to the fans and they've just gone crazy with it. they've just gone crazy with it. they've just gone crazy with it. >> Love you queen of >> Love you queen of >> Love you queen of winners. >> Besties are gone. >> Besties are gone. That is my dog taking out your That is my dog taking out your That is my dog taking out your driveways. >> Oh man, my appetiter will meet. >> Oh man, my appetiter will meet. >> We should all just get a room and just >> We should all just get a room and just >> We should all just get a room and just have one big huge orgy cuz they're all have one big huge orgy cuz they're all have one big huge orgy cuz they're all just useless. It's like this like sexual just useless. It's like this like sexual just useless. It's like this like sexual tension that we just need to release tension that we just need to release tension that we just need to release somehow. >> That's going to be good. We need to get >> That's going to be good. We need to get merch.