ChatGPT – The Super Assistant Era | BG2 Guest Interview

Chat GPT originally was entirely free Chat GPT originally was entirely free and the reason for that was that it was and the reason for that was that it was and the reason for that was that it was intended to be a demo and we were going intended to be a demo and we were going intended to be a demo and we were going to wind it down after a month. to wind it down after a month. to wind it down after a month. >> We then realized that the demo went >> We then realized that the demo went >> We then realized that the demo went viral and people loved the demo and it viral and people loved the demo and it viral and people loved the demo and it was actually a product and but we was actually a product and but we was actually a product and but we realized to be a product you can't take realized to be a product you can't take realized to be a product you can't take the product down every time you're at the product down every time you're at the product down every time you're at capacity. So we you ship subscriptions capacity. So we you ship subscriptions capacity. So we you ship subscriptions simply because it could shape the simply because it could shape the simply because it could shape the demand. It was a way of gracefully demand. It was a way of gracefully demand. It was a way of gracefully turning users away when we had to turn turning users away when we had to turn turning users away when we had to turn away someone. You know, you guys are at away someone. You know, you guys are at away someone. You know, you guys are at 900 million VT active users now, and 900 million VT active users now, and 900 million VT active users now, and that growth has been incredible. The that growth has been incredible. The that growth has been incredible. The next billion users, where they where are next billion users, where they where are next billion users, where they where are they going to come from? they going to come from? they going to come from? >> We've got about 10% of the world coming >> We've got about 10% of the world coming >> We've got about 10% of the world coming to us now. 90% left to go, right? to us now. 90% left to go, right? to us now. 90% left to go, right? There's so much more opportunity. >> Well, Nick, so excited to have you here. >> Well, Nick, so excited to have you here. >> Thank you for having me, Peru. You've >> Thank you for having me, Peru. You've >> Thank you for having me, Peru. You've had uh quite the journey from Germany to had uh quite the journey from Germany to had uh quite the journey from Germany to the US for Brown. the US for Brown. the US for Brown. >> That's true. >> That's true. >> That's true. >> Most recently at Instacart delivering uh >> Most recently at Instacart delivering uh >> Most recently at Instacart delivering uh groceries in 30 minutes to now groceries in 30 minutes to now groceries in 30 minutes to now delivering AGI to billions. I'm sure delivering AGI to billions. I'm sure delivering AGI to billions. I'm sure that was the plan all along. that was the plan all along. that was the plan all along. >> Yeah, clearly total master plan. >> Yeah, clearly total master plan. >> Yeah, clearly total master plan. >> Well, well, tell us about your journey. >> Well, well, tell us about your journey. >> Well, well, tell us about your journey. What how did you get to OpenAI? I know What how did you get to OpenAI? I know What how did you get to OpenAI? I know it's a fun fun story. And your your it's a fun fun story. And your your it's a fun fun story. And your your three and a half years or so at OpenI, three and a half years or so at OpenI, three and a half years or so at OpenI, how have they gone? The only through how have they gone? The only through how have they gone? The only through light in how any sort of employment light in how any sort of employment light in how any sort of employment decision has been entirely people based. decision has been entirely people based. decision has been entirely people based. So I don't claim any credit for for uh So I don't claim any credit for for uh So I don't claim any credit for for uh joining OpenAI um or predicting chat GPT joining OpenAI um or predicting chat GPT joining OpenAI um or predicting chat GPT or anything like it. But um I uh um hit or anything like it. But um I uh um hit or anything like it. But um I uh um hit up someone who I admire a lot who I got up someone who I admire a lot who I got up someone who I admire a lot who I got got to know at Dropbox. um Joanne who uh got to know at Dropbox. um Joanne who uh got to know at Dropbox. um Joanne who uh worked worked here at the time and she worked worked here at the time and she worked worked here at the time and she uh I asked her to get off the Dolly 2 uh I asked her to get off the Dolly 2 uh I asked her to get off the Dolly 2 wait list and she told me I had an wait list and she told me I had an wait list and she told me I had an interview if I wanted to get off the interview if I wanted to get off the interview if I wanted to get off the wait list. So um I took the bait and got wait list. So um I took the bait and got wait list. So um I took the bait and got totally nerd sniped in the process and totally nerd sniped in the process and totally nerd sniped in the process and and here I am. and here I am. and here I am. >> There you go. The Dolly 2 weight list >> There you go. The Dolly 2 weight list >> There you go. The Dolly 2 weight list will get you. will get you. will get you. >> It's a great recruiting tool. >> It's a great recruiting tool. >> It's a great recruiting tool. >> Nice, nice, nice. >> Nice, nice, nice. >> Nice, nice, nice. >> We should do more weight lists probably. >> We should do more weight lists probably. >> We should do more weight lists probably. >> Yeah. Yeah. Yeah. Well, you know, the >> Yeah. Yeah. Yeah. Well, you know, the >> Yeah. Yeah. Yeah. Well, you know, the big uh the big big uh the big big uh the big super cycle we're in is is is Chad GPT. super cycle we're in is is is Chad GPT. super cycle we're in is is is Chad GPT. Now, I assume over a billion users on Now, I assume over a billion users on Now, I assume over a billion users on the monthly side, 900 million weekly the monthly side, 900 million weekly the monthly side, 900 million weekly active users that recently reported up active users that recently reported up active users that recently reported up from zero three and a half years ago. Uh from zero three and a half years ago. Uh from zero three and a half years ago. Uh you could have, if I imagine what the you could have, if I imagine what the you could have, if I imagine what the dashboard of Nick Turley looks like, it dashboard of Nick Turley looks like, it dashboard of Nick Turley looks like, it could have users, it could have paying could have users, it could have paying could have users, it could have paying subscribers, it could have daily active subscribers, it could have daily active subscribers, it could have daily active users, it could have retention, users, it could have retention, users, it could have retention, engagement. I mean, there's like 15 engagement. I mean, there's like 15 engagement. I mean, there's like 15 things, maybe all of them. What what is things, maybe all of them. What what is things, maybe all of them. What what is your northstar? How do you how do you op your northstar? How do you how do you op your northstar? How do you how do you op what are you optimizing for? Uh what is what are you optimizing for? Uh what is what are you optimizing for? Uh what is Nick looking at in his daily dashboard? Nick looking at in his daily dashboard? Nick looking at in his daily dashboard? >> It's it's funny, right? Because it's >> It's it's funny, right? Because it's >> It's it's funny, right? Because it's such a young product. It's been to your such a young product. It's been to your such a young product. It's been to your point three and a half years. And um point three and a half years. And um point three and a half years. And um this kind of question, it kind of this kind of question, it kind of this kind of question, it kind of changes as as as you evolve and you and changes as as as you evolve and you and changes as as as you evolve and you and you grow up and you ask yourself, you you grow up and you ask yourself, you you grow up and you ask yourself, you know, what are we really building here? know, what are we really building here? know, what are we really building here? And uh to this day, right, then want to And uh to this day, right, then want to And uh to this day, right, then want to build a super assistant that can build a super assistant that can build a super assistant that can actually help people achieve their actually help people achieve their actually help people achieve their goals. goals. goals. >> And ultimately the thing we care about >> And ultimately the thing we care about >> And ultimately the thing we care about is like is our product doing that? Is it is like is our product doing that? Is it is like is our product doing that? Is it actually helping you do the thing that actually helping you do the thing that actually helping you do the thing that you're, you know, um coming to the you're, you know, um coming to the you're, you know, um coming to the product to do? And it's so different for product to do? And it's so different for product to do? And it's so different for different people, right? Some people um different people, right? Some people um different people, right? Some people um are are trying to get healthy, other are are trying to get healthy, other are are trying to get healthy, other people are trying to start a company, people are trying to start a company, people are trying to start a company, >> um um learn a new topic, um >> um um learn a new topic, um >> um um learn a new topic, um >> do their taxes. There's all these >> do their taxes. There's all these >> do their taxes. There's all these different things that you might be different things that you might be different things that you might be doing. Um, and the true measure of doing. Um, and the true measure of doing. Um, and the true measure of success is whether or not that we're success is whether or not that we're success is whether or not that we're helping you do that. And um, obviously helping you do that. And um, obviously helping you do that. And um, obviously we look at WAU in particular because, we look at WAU in particular because, we look at WAU in particular because, you know, we want to know if you're you know, we want to know if you're you know, we want to know if you're coming back to the product. We look at coming back to the product. We look at coming back to the product. We look at retention. Um, but we, you know, we we retention. Um, but we, you know, we we retention. Um, but we, you know, we we look at, um, all kinds of stuff in look at, um, all kinds of stuff in look at, um, all kinds of stuff in aggregate because really there isn't aggregate because really there isn't aggregate because really there isn't like this one single thing that you can like this one single thing that you can like this one single thing that you can optimize for. optimize for. optimize for. >> If you were to allocate a 100 units of >> If you were to allocate a 100 units of >> If you were to allocate a 100 units of points points points >> to these metrics, which metric can you >> to these metrics, which metric can you >> to these metrics, which metric can you like distribute the 100 units across like distribute the 100 units across like distribute the 100 units across these metrics in order of importance for these metrics in order of importance for these metrics in order of importance for you right this second? It's a good you right this second? It's a good you right this second? It's a good question. I I care a lot about long-term question. I I care a lot about long-term question. I I care a lot about long-term retention and I would put all my points retention and I would put all my points retention and I would put all my points there. Um because um I'm really proud of there. Um because um I'm really proud of there. Um because um I'm really proud of the retention stats we have. the retention stats we have. the retention stats we have. >> Huge, >> Huge, >> Huge, >> but ultimately the sign of durable >> but ultimately the sign of durable >> but ultimately the sign of durable values, whether or not people are coming values, whether or not people are coming values, whether or not people are coming back in three months because that means back in three months because that means back in three months because that means you're really solving their problems. you're really solving their problems. you're really solving their problems. And And And >> yeah, >> yeah, >> yeah, >> I think things like revenue, they follow >> I think things like revenue, they follow >> I think things like revenue, they follow from that. Um from that. Um from that. Um >> yeah. >> yeah. >> yeah. >> Um versus like, you know, trying to go >> Um versus like, you know, trying to go >> Um versus like, you know, trying to go on those things directly. And we've on those things directly. And we've on those things directly. And we've we've had a lot of success making very we've had a lot of success making very we've had a lot of success making very principled decisions u on this stuff. principled decisions u on this stuff. principled decisions u on this stuff. Like one good example is you GPD4 used Like one good example is you GPD4 used Like one good example is you GPD4 used to be behind a pay pay wall because we to be behind a pay pay wall because we to be behind a pay pay wall because we couldn't serve it to everyone and then couldn't serve it to everyone and then couldn't serve it to everyone and then we had GPD4 which was a total we had GPD4 which was a total we had GPD4 which was a total breakthrough breakthrough breakthrough >> in um in in our ability to inference it >> in um in in our ability to inference it >> in um in in our ability to inference it and um and um and um >> so we just gave it away for free and >> so we just gave it away for free and >> so we just gave it away for free and that ended up being totally revenue that ended up being totally revenue that ended up being totally revenue positive and retention positive because positive and retention positive because positive and retention positive because it just provided access to the tech and it just provided access to the tech and it just provided access to the tech and I think when you make your decisions I think when you make your decisions I think when you make your decisions that way and you focus on the customer that way and you focus on the customer that way and you focus on the customer >> you end up with a great product and >> you end up with a great product and >> you end up with a great product and revenue obviously follows too. revenue obviously follows too. revenue obviously follows too. >> Phenomenal. >> Phenomenal. >> Phenomenal. >> Yeah. Well, it uh it shows up in the >> Yeah. Well, it uh it shows up in the >> Yeah. Well, it uh it shows up in the numbers. You know, I I posted this chart numbers. You know, I I posted this chart numbers. You know, I I posted this chart uh yesterday on the data that we have, uh yesterday on the data that we have, uh yesterday on the data that we have, you know, from a third party. The you know, from a third party. The you know, from a third party. The retention curves for chat GPD are retention curves for chat GPD are retention curves for chat GPD are smiling. Look at that. Just like that. smiling. Look at that. Just like that. smiling. Look at that. Just like that. And that is a rare that is a very rare And that is a rare that is a very rare And that is a rare that is a very rare occurrence, you know, as as we know. And occurrence, you know, as as we know. And occurrence, you know, as as we know. And um why why do you think like if you were um why why do you think like if you were um why why do you think like if you were to give us a narrative on that smile to give us a narrative on that smile to give us a narrative on that smile curve? What is the why do these smile curve? What is the why do these smile curve? What is the why do these smile curves exist? What are you seeing in curves exist? What are you seeing in curves exist? What are you seeing in Chad GPD that has people who have who Chad GPD that has people who have who Chad GPD that has people who have who have maybe turned off for a couple of have maybe turned off for a couple of have maybe turned off for a couple of weeks or months coming back and why are weeks or months coming back and why are weeks or months coming back and why are they coming back? they coming back? they coming back? >> Look, there isn't one single thing. You >> Look, there isn't one single thing. You >> Look, there isn't one single thing. You know, the way you build a retentive know, the way you build a retentive know, the way you build a retentive product is lots and lots of little product is lots and lots of little product is lots and lots of little things and really trying to make it things and really trying to make it things and really trying to make it better systematically. I will say that better systematically. I will say that better systematically. I will say that you know with AI and in particular chat you know with AI and in particular chat you know with AI and in particular chat GBT I found that it takes people some GBT I found that it takes people some GBT I found that it takes people some time to really understand all the parts time to really understand all the parts time to really understand all the parts of their life they can delegate right of their life they can delegate right of their life they can delegate right and I think many users for that it's a and I think many users for that it's a and I think many users for that it's a multi-month process for them to multi-month process for them to multi-month process for them to understand how can this thing help me understand how can this thing help me understand how can this thing help me and what are all the different ways and what are all the different ways and what are all the different ways >> that um I could plug chatbt into my life >> that um I could plug chatbt into my life >> that um I could plug chatbt into my life >> um and um but you know when I think >> um and um but you know when I think >> um and um but you know when I think about some of the breakthroughs and about some of the breakthroughs and about some of the breakthroughs and levers we've had um things like search levers we've had um things like search levers we've had um things like search and personalization they they have and personalization they they have and personalization they they have helped solve those user problems because helped solve those user problems because helped solve those user problems because um you know search provides way more um you know search provides way more um you know search provides way more daily value to you. daily value to you. daily value to you. >> Um it used to be that chat was a pretty >> Um it used to be that chat was a pretty >> Um it used to be that chat was a pretty worky product. You know we'd see usage worky product. You know we'd see usage worky product. You know we'd see usage go down on the weekend. We usage you go down on the weekend. We usage you go down on the weekend. We usage you know go down during the summer months know go down during the summer months know go down during the summer months when a lot of people were off from work when a lot of people were off from work when a lot of people were off from work >> and um >> and um >> and um >> today you know we're we're mobile first. >> today you know we're we're mobile first. >> today you know we're we're mobile first. The vast majority is mobile and we see The vast majority is mobile and we see The vast majority is mobile and we see all these personal use cases and I think all these personal use cases and I think all these personal use cases and I think search was a big investment that got us search was a big investment that got us search was a big investment that got us there there there >> and personalization makes chat so much >> and personalization makes chat so much >> and personalization makes chat so much more relevant for you right because it more relevant for you right because it more relevant for you right because it gets to know you over time. you get to gets to know you over time. you get to gets to know you over time. you get to know it. Um and um those are two things know it. Um and um those are two things know it. Um and um those are two things that have materially moved um the way that have materially moved um the way that have materially moved um the way that you know people come back to the that you know people come back to the that you know people come back to the product. But um there's lots more to do. product. But um there's lots more to do. product. But um there's lots more to do. >> Yeah. >> Yeah. >> Yeah. >> Um and you know, as mentioned, I don't >> Um and you know, as mentioned, I don't >> Um and you know, as mentioned, I don't I'm not resting on our um retention I'm not resting on our um retention I'm not resting on our um retention stats even though, um we're obviously stats even though, um we're obviously stats even though, um we're obviously very proud. very proud. very proud. >> Nice, nice, nice. Um and you know, the >> Nice, nice, nice. Um and you know, the >> Nice, nice, nice. Um and you know, the other thing that I I got wrong about other thing that I I got wrong about other thing that I I got wrong about Chad GPT was this is two two and a half Chad GPT was this is two two and a half Chad GPT was this is two two and a half years ago. I was like, well, you know, years ago. I was like, well, you know, years ago. I was like, well, you know, let's look at who's going to win this let's look at who's going to win this let's look at who's going to win this consumer AI race. You typically these consumer AI race. You typically these consumer AI race. You typically these consumer markets are winner or take most consumer markets are winner or take most consumer markets are winner or take most winner or take all. Look at search. winner or take all. Look at search. winner or take all. Look at search. Google has near 90% plus market share. Google has near 90% plus market share. Google has near 90% plus market share. Three and a half, four trillion market Three and a half, four trillion market Three and a half, four trillion market cap. cap. cap. >> Mobile, same thing with Apple. Social, >> Mobile, same thing with Apple. Social, >> Mobile, same thing with Apple. Social, same thing with Meta. I was like, well, same thing with Meta. I was like, well, same thing with Meta. I was like, well, AI, Meta has all the distribution. AI, Meta has all the distribution. AI, Meta has all the distribution. Google's got all the distribution. Google's got all the distribution. Google's got all the distribution. They've got 34 billion users. Well, it They've got 34 billion users. Well, it They've got 34 billion users. Well, it would be a flick of a switch for them to would be a flick of a switch for them to would be a flick of a switch for them to roll out their AI. But I was wrong. roll out their AI. But I was wrong. roll out their AI. But I was wrong. That's not what happened. Chad GPT turns That's not what happened. Chad GPT turns That's not what happened. Chad GPT turns out uh you know you guys are at 900 out uh you know you guys are at 900 out uh you know you guys are at 900 million VT active users now and um that million VT active users now and um that million VT active users now and um that growth has been incredible clearly growth has been incredible clearly growth has been incredible clearly distribution was not enough right distribution was not enough right distribution was not enough right >> so the same question for distribution >> so the same question for distribution >> so the same question for distribution what are the levers for us that have what are the levers for us that have what are the levers for us that have gotten us to the scale is it model gotten us to the scale is it model gotten us to the scale is it model quality is it you know product quality quality is it you know product quality quality is it you know product quality is it you know features is it the is it you know features is it the is it you know features is it the experience or product improvements like experience or product improvements like experience or product improvements like memory and personalization or search memory and personalization or search memory and personalization or search like like like >> same question like what would you say >> same question like what would you say >> same question like what would you say drove historical drove historical drove historical >> growth and and success >> growth and and success >> growth and and success We've got about 10% of the world coming We've got about 10% of the world coming We've got about 10% of the world coming to us now. 90% left to go, right? So to us now. 90% left to go, right? So to us now. 90% left to go, right? So there's so much more opportunity to to there's so much more opportunity to to there's so much more opportunity to to to re reach more people and introduce to re reach more people and introduce to re reach more people and introduce them to the way that AI can can can them to the way that AI can can can them to the way that AI can can can >> benefit them, right? But when I when I >> benefit them, right? But when I when I >> benefit them, right? But when I when I look backwards and I only say that look backwards and I only say that look backwards and I only say that because like the next billion users because like the next billion users because like the next billion users might be very different in terms of like might be very different in terms of like might be very different in terms of like how you um engage and reach and provide how you um engage and reach and provide how you um engage and reach and provide value, value, value, >> but when I look backward, it's been >> but when I look backward, it's been >> but when I look backward, it's been roughly sort of roughly sort of roughly sort of >> oneird one third one third between >> oneird one third one third between >> oneird one third one third between sort of classic friction removal type of sort of classic friction removal type of sort of classic friction removal type of work. Like one of our biggest um work. Like one of our biggest um work. Like one of our biggest um um moments when you look at pure impact um moments when you look at pure impact um moments when you look at pure impact um was you know removing the um was you know removing the um was you know removing the authentication wall authentication wall authentication wall >> and Sam will say I told you so because I >> and Sam will say I told you so because I >> and Sam will say I told you so because I think that was his feedback from like think that was his feedback from like think that was his feedback from like day one day one day one >> u like can't you shouldn't have to log >> u like can't you shouldn't have to log >> u like can't you shouldn't have to log into the chatbt but it's like stuff like into the chatbt but it's like stuff like into the chatbt but it's like stuff like that that you do for any product and it that that you do for any product and it that that you do for any product and it does matter some things never change does matter some things never change does matter some things never change right right right >> um and but you know and then you know >> um and but you know and then you know >> um and but you know and then you know another third or so isort another third or so isort another third or so isort >> you know are what I would sort of sort >> you know are what I would sort of sort >> you know are what I would sort of sort core product investments and they're core product investments and they're core product investments and they're really typically things that we've done really typically things that we've done really typically things that we've done together between research and product. together between research and product. together between research and product. So So So >> search and personalization are really >> search and personalization are really >> search and personalization are really good examples of that where we came good examples of that where we came good examples of that where we came together and we figured out not just together and we figured out not just together and we figured out not just UIUX evolution but also how to postrain UIUX evolution but also how to postrain UIUX evolution but also how to postrain um these changes into the model and it um these changes into the model and it um these changes into the model and it was really the moments when we came was really the moments when we came was really the moments when we came together. Um um another recent example together. Um um another recent example together. Um um another recent example is like we have these writing blocks is like we have these writing blocks is like we have these writing blocks that render when you you know ask about that render when you you know ask about that render when you you know ask about queries um where you're um you know queries um where you're um you know queries um where you're um you know trying to write with the model trying to write with the model trying to write with the model >> and like putting really good craft into >> and like putting really good craft into >> and like putting really good craft into those experiences really matters and um those experiences really matters and um those experiences really matters and um um you our users love it and then um you our users love it and then um you our users love it and then >> another third of of the growth has been >> another third of of the growth has been >> another third of of the growth has been just model improvements like step both just model improvements like step both just model improvements like step both step changes like going from um GBD 3.5 step changes like going from um GBD 3.5 step changes like going from um GBD 3.5 back then to GPD4 then going from GPD4 back then to GPD4 then going from GPD4 back then to GPD4 then going from GPD4 behind a payw wall to O suddenly behind a payw wall to O suddenly behind a payw wall to O suddenly available to everyone, right? available to everyone, right? available to everyone, right? >> But a lot of it is also the iteration >> But a lot of it is also the iteration >> But a lot of it is also the iteration that isn't splashy, that doesn't warrant that isn't splashy, that doesn't warrant that isn't splashy, that doesn't warrant like, you know, a named release. You we like, you know, a named release. You we like, you know, a named release. You we um I'm really excited about the updates um I'm really excited about the updates um I'm really excited about the updates we just made um with 5.3, 5.4, etc. we just made um with 5.3, 5.4, etc. we just made um with 5.3, 5.4, etc. >> Because um that is when we like take a >> Because um that is when we like take a >> Because um that is when we like take a lot of user feedback and we you know, lot of user feedback and we you know, lot of user feedback and we you know, methodically address it and obviously methodically address it and obviously methodically address it and obviously that shows up um that shows up um that shows up um >> in our retention as well. So sort of one >> in our retention as well. So sort of one >> in our retention as well. So sort of one third one third one third between third one third one third between third one third one third between classic um friction removal um and classic um friction removal um and classic um friction removal um and access access access >> um core product investments and then >> um core product investments and then >> um core product investments and then pure model improvements. pure model improvements. pure model improvements. >> And so the question that I've really >> And so the question that I've really >> And so the question that I've really been waiting to ask you is how do we get been waiting to ask you is how do we get been waiting to ask you is how do we get the next billion the next billion the next billion >> and and you know talk about that a >> and and you know talk about that a >> and and you know talk about that a little bit. There's a lot of it it seems little bit. There's a lot of it it seems little bit. There's a lot of it it seems like at least from the outside fog of like at least from the outside fog of like at least from the outside fog of war. If I was a consumer today in the war. If I was a consumer today in the war. If I was a consumer today in the market to pick my super assistant, um market to pick my super assistant, um market to pick my super assistant, um you would have a couple of great you would have a couple of great you would have a couple of great options, you know, uh plot out there, options, you know, uh plot out there, options, you know, uh plot out there, they're having some great traction last they're having some great traction last they're having some great traction last couple of weeks. couple of weeks. couple of weeks. >> Um Gemini mega distribution, Uber >> Um Gemini mega distribution, Uber >> Um Gemini mega distribution, Uber distribution, um and us by the by the by distribution, um and us by the by the by distribution, um and us by the by the by the leading product today, at least in the leading product today, at least in the leading product today, at least in user numbers, the next billion users, user numbers, the next billion users, user numbers, the next billion users, where they where they going to come where they where they going to come where they where they going to come from? First of all, just to from? First of all, just to from? First of all, just to contextualize that goal. You we care contextualize that goal. You we care contextualize that goal. You we care about about about um two things at the end of the day. um two things at the end of the day. um two things at the end of the day. Obviously, reaching more people is Obviously, reaching more people is Obviously, reaching more people is really important. It's the direct really important. It's the direct really important. It's the direct manifestation of our mission um to the manifestation of our mission um to the manifestation of our mission um to the world where you the more people we can world where you the more people we can world where you the more people we can introduce the benefits of AI uh the introduce the benefits of AI uh the introduce the benefits of AI uh the better that is. Um but we're also really better that is. Um but we're also really better that is. Um but we're also really excited to go deeper. Um and that means excited to go deeper. Um and that means excited to go deeper. Um and that means taking the same billion users that find taking the same billion users that find taking the same billion users that find value in chat GPD today. Um and actually value in chat GPD today. Um and actually value in chat GPD today. Um and actually providing more meaningful value in their providing more meaningful value in their providing more meaningful value in their world like actually helping them achieve world like actually helping them achieve world like actually helping them achieve their goals. not just answering their goals. not just answering their goals. not just answering questions, right? questions, right? questions, right? >> Um, so I'll talk about how we get to >> Um, so I'll talk about how we get to >> Um, so I'll talk about how we get to more scale, but I think it's important more scale, but I think it's important more scale, but I think it's important to remember that, you know, the way this to remember that, you know, the way this to remember that, you know, the way this technology is evolving is, you know, technology is evolving is, you know, technology is evolving is, you know, we're going to go beyond pure chat bots we're going to go beyond pure chat bots we're going to go beyond pure chat bots um pretty fast. um pretty fast. um pretty fast. >> Exciting. Um I think on on scale you >> Exciting. Um I think on on scale you >> Exciting. Um I think on on scale you know it's shocked me how many people know it's shocked me how many people know it's shocked me how many people have found value in chatbt as it works have found value in chatbt as it works have found value in chatbt as it works today because I don't think delegation today because I don't think delegation today because I don't think delegation is a natural skill for most is a natural skill for most is a natural skill for most >> and chatbt is a pretty >> and chatbt is a pretty >> and chatbt is a pretty it's a it's it's a power tool right you it's a it's it's a power tool right you it's a it's it's a power tool right you come to it doesn't tell you what it's come to it doesn't tell you what it's come to it doesn't tell you what it's for you kind of have to discover it on for you kind of have to discover it on for you kind of have to discover it on your own and you have to use it and then your own and you have to use it and then your own and you have to use it and then you'll learn about this prompt that was you'll learn about this prompt that was you'll learn about this prompt that was really cool and then maybe you you're on really cool and then maybe you you're on really cool and then maybe you you're on Twitter and you learn about another one Twitter and you learn about another one Twitter and you learn about another one or you're on Instagram and you learn or you're on Instagram and you learn or you're on Instagram and you learn another But the product it's it's like a another But the product it's it's like a another But the product it's it's like a raw appliance. And I think to you know raw appliance. And I think to you know raw appliance. And I think to you know on one thing we really need to nail as on one thing we really need to nail as on one thing we really need to nail as we you know reach the next set of users we you know reach the next set of users we you know reach the next set of users >> is a product that has a bit more of an >> is a product that has a bit more of an >> is a product that has a bit more of an affordance. affordance. affordance. >> U because I think for most people >> U because I think for most people >> U because I think for most people they're very very busy. they're very very busy. they're very very busy. >> Um and they everyone I think in the >> Um and they everyone I think in the >> Um and they everyone I think in the world has intelligence constrained world has intelligence constrained world has intelligence constrained problems like problems that more problems like problems that more problems like problems that more intelligence could help with intelligence could help with intelligence could help with >> but you need to frame that to people. >> but you need to frame that to people. >> but you need to frame that to people. >> Yeah. Yeah. >> Yeah. Yeah. >> Yeah. Yeah. >> And I still feel like we're a little bit >> And I still feel like we're a little bit >> And I still feel like we're a little bit too much like a computer terminal and it too much like a computer terminal and it too much like a computer terminal and it needs to feel more like software like or needs to feel more like software like or needs to feel more like software like or um you know an operating system of um you know an operating system of um you know an operating system of software, software, software, >> right? >> right? >> right? >> Um so that's one thing. Um another thing >> Um so that's one thing. Um another thing >> Um so that's one thing. Um another thing um that gets at the same constraint is um that gets at the same constraint is um that gets at the same constraint is is beginning to be proactive. is beginning to be proactive. is beginning to be proactive. >> Um in a world where a lot of folks are, >> Um in a world where a lot of folks are, >> Um in a world where a lot of folks are, you know, too busy to delegate their you know, too busy to delegate their you know, too busy to delegate their problems to AI or don't quite know where problems to AI or don't quite know where problems to AI or don't quite know where to start, I think being able to help you to start, I think being able to help you to start, I think being able to help you proactively is really really important proactively is really really important proactively is really really important as well. as well. as well. Um, but you know, I think all these are Um, but you know, I think all these are Um, but you know, I think all these are are product evolutions that we could are product evolutions that we could are product evolutions that we could make on on top of the current tech. And make on on top of the current tech. And make on on top of the current tech. And the thing that gets me particularly the thing that gets me particularly the thing that gets me particularly excited is productizing our next excited is productizing our next excited is productizing our next generation tech or reasoning models generation tech or reasoning models generation tech or reasoning models because the truth is when you look at because the truth is when you look at because the truth is when you look at reasoning and chatb today. reasoning and chatb today. reasoning and chatb today. >> It's relevant to a very small group of >> It's relevant to a very small group of >> It's relevant to a very small group of people. It's relevant for the people who people. It's relevant for the people who people. It's relevant for the people who are trying to get the most out of chat are trying to get the most out of chat are trying to get the most out of chat GPT. GPT. GPT. >> But I fundamentally believe that >> But I fundamentally believe that >> But I fundamentally believe that reasoning it's transformative. And if reasoning it's transformative. And if reasoning it's transformative. And if you can figure out how to productize you can figure out how to productize you can figure out how to productize reasoning in a way that works on reasoning in a way that works on reasoning in a way that works on people's behalf without them even people's behalf without them even people's behalf without them even knowing knowing knowing >> um and that looks very much like you >> um and that looks very much like you >> um and that looks very much like you know know know >> the model doing long horizon tasks on >> the model doing long horizon tasks on >> the model doing long horizon tasks on your behalf. It doesn't mean you your behalf. It doesn't mean you your behalf. It doesn't mean you encounter the concept. It just means encounter the concept. It just means encounter the concept. It just means it's benefiting you right. it's benefiting you right. it's benefiting you right. >> Um so there's so much work to do and and >> Um so there's so much work to do and and >> Um so there's so much work to do and and you know you know you know >> the the the product certainly has to >> the the the product certainly has to >> the the the product certainly has to evolve to to be relevant for for for evolve to to be relevant for for for evolve to to be relevant for for for this kind of scale. this kind of scale. this kind of scale. >> Yeah. One of the one of the things that >> Yeah. One of the one of the things that >> Yeah. One of the one of the things that I've been hoping for a while and you I've been hoping for a while and you I've been hoping for a while and you know Brad made a bet two years ago um know Brad made a bet two years ago um know Brad made a bet two years ago um when can Chad GBD help me take actions. when can Chad GBD help me take actions. when can Chad GBD help me take actions. >> Can Chad Guby help me be more proactive >> Can Chad Guby help me be more proactive >> Can Chad Guby help me be more proactive >> and um I think his bet expired end of >> and um I think his bet expired end of >> and um I think his bet expired end of last year. So he's he's we're very last year. So he's he's we're very last year. So he's he's we're very curious. curious. curious. >> When is that coming? And I'll frame that >> When is that coming? And I'll frame that >> When is that coming? And I'll frame that for you because you know with with with for you because you know with with with for you because you know with with with with search engines in Google you know with search engines in Google you know with search engines in Google you know two decades ago you'd have gotten the 10 two decades ago you'd have gotten the 10 two decades ago you'd have gotten the 10 blue links. You could have spent an hour blue links. You could have spent an hour blue links. You could have spent an hour getting the answer. you can now get the getting the answer. you can now get the getting the answer. you can now get the answer instantly with chat GPT. answer instantly with chat GPT. answer instantly with chat GPT. >> Uh and it feels like the next step is is >> Uh and it feels like the next step is is >> Uh and it feels like the next step is is actions actions actions >> 100%. >> 100%. >> 100%. >> And it feels like the next step is you >> And it feels like the next step is you >> And it feels like the next step is you know with you know pulse is a is a great know with you know pulse is a is a great know with you know pulse is a is a great proactive product. proactive product. proactive product. >> Um that that that feels you know it's I >> Um that that that feels you know it's I >> Um that that that feels you know it's I have a pulse that runs weekly have a pulse that runs weekly have a pulse that runs weekly >> but what I would really like is like hey >> but what I would really like is like hey >> but what I would really like is like hey Nick spoke about something and just just Nick spoke about something and just just Nick spoke about something and just just find me make sure I know that Nick spoke find me make sure I know that Nick spoke find me make sure I know that Nick spoke about this or or like hey this XYZ thing about this or or like hey this XYZ thing about this or or like hey this XYZ thing happened that I cared about a lot. happened that I cared about a lot. happened that I cared about a lot. >> Um when is when is one of that going to >> Um when is when is one of that going to >> Um when is when is one of that going to get proactive? um what is the modality get proactive? um what is the modality get proactive? um what is the modality going to look like? going to look like? going to look like? >> Yeah. Yeah. So there's there's two >> Yeah. Yeah. So there's there's two >> Yeah. Yeah. So there's there's two concepts I think. Um there there's chat concepts I think. Um there there's chat concepts I think. Um there there's chat should be doing stuff rather than just should be doing stuff rather than just should be doing stuff rather than just answering answering answering >> and then there's chat should be being >> and then there's chat should be being >> and then there's chat should be being proactive and I think when you put them proactive and I think when you put them proactive and I think when you put them together you start feeling like it feels together you start feeling like it feels together you start feeling like it feels like a super assistant. Um because I like a super assistant. Um because I like a super assistant. Um because I think these things compound think these things compound think these things compound >> um >> um >> um >> on the action taking piece you strictly >> on the action taking piece you strictly >> on the action taking piece you strictly speaking in chat speaking in chat speaking in chat can do stuff today. Um the action space can do stuff today. Um the action space can do stuff today. Um the action space is just very limited, right? It can is just very limited, right? It can is just very limited, right? It can search the web, which means it can use search the web, which means it can use search the web, which means it can use you search tool or browser in the same you search tool or browser in the same you search tool or browser in the same way that a human would. way that a human would. way that a human would. >> Um it can make images. It can do all the >> Um it can make images. It can do all the >> Um it can make images. It can do all the all these things, right? But it doesn't all these things, right? But it doesn't all these things, right? But it doesn't have clearly doesn't have the same have clearly doesn't have the same have clearly doesn't have the same action space that a human with a action space that a human with a action space that a human with a computer would have. And that is what we computer would have. And that is what we computer would have. And that is what we aim to build. Um aim to build. Um aim to build. Um >> and if you timing is everything on these >> and if you timing is everything on these >> and if you timing is everything on these bets, right? And I don't pretend to be bets, right? And I don't pretend to be bets, right? And I don't pretend to be great at timing either. U you look at great at timing either. U you look at great at timing either. U you look at past attempts that we've made like the past attempts that we've made like the past attempts that we've made like the chatbt agent for example, chatbt agent for example, chatbt agent for example, >> which kind of has capabilities like >> which kind of has capabilities like >> which kind of has capabilities like this. um it was just slightly too early. this. um it was just slightly too early. this. um it was just slightly too early. The models weren't quite good enough to The models weren't quite good enough to The models weren't quite good enough to hit real escape velocity. And the hit real escape velocity. And the hit real escape velocity. And the problem is if you don't have escape problem is if you don't have escape problem is if you don't have escape velocity is that users don't learn to velocity is that users don't learn to velocity is that users don't learn to trust it. They don't even try. trust it. They don't even try. trust it. They don't even try. >> So when you look at a lot of things >> So when you look at a lot of things >> So when you look at a lot of things people were doing in the original people were doing in the original people were doing in the original version of chatb agent, it was the version of chatb agent, it was the version of chatb agent, it was the things that happened to work like things that happened to work like things that happened to work like migrating your uh uh file server into migrating your uh uh file server into migrating your uh uh file server into the cloud or something like that. Useful the cloud or something like that. Useful the cloud or something like that. Useful stuff but very niche. stuff but very niche. stuff but very niche. >> Yeah. Um and um as this stuff gets >> Yeah. Um and um as this stuff gets >> Yeah. Um and um as this stuff gets better um we just have to get it to a better um we just have to get it to a better um we just have to get it to a point where people try to use it for point where people try to use it for point where people try to use it for real meaningful problems in their life real meaningful problems in their life real meaningful problems in their life because then we can start hill climbing because then we can start hill climbing because then we can start hill climbing and this has been the magic of chatbt and this has been the magic of chatbt and this has been the magic of chatbt where chatbt upon launch was good enough where chatbt upon launch was good enough where chatbt upon launch was good enough to get real attempts at use cases even to get real attempts at use cases even to get real attempts at use cases even if they didn't initially work like chat if they didn't initially work like chat if they didn't initially work like chat was a pretty bad writer originally it was a pretty bad writer originally it was a pretty bad writer originally it was a bad software engineer but people was a bad software engineer but people was a bad software engineer but people tried and got enough value out of it tried and got enough value out of it tried and got enough value out of it that we could take those use cases and that we could take those use cases and that we could take those use cases and make them great make them great make them great >> and I do think we're about to get to >> and I do think we're about to get to >> and I do think we're about to get to that point with general purpose agents that point with general purpose agents that point with general purpose agents where where where >> it works well enough that you get at >> it works well enough that you get at >> it works well enough that you get at least partial credit least partial credit least partial credit >> and because you're getting partial >> and because you're getting partial >> and because you're getting partial credit you get really good tasks back credit you get really good tasks back credit you get really good tasks back and then the magic begins because um you and then the magic begins because um you and then the magic begins because um you know once you have know once you have know once you have >> a a set of use cases that you can um >> a a set of use cases that you can um >> a a set of use cases that you can um climb the hill on we can make them climb the hill on we can make them climb the hill on we can make them awesome. So on task I think we're close awesome. So on task I think we're close awesome. So on task I think we're close but I think even people inside of open but I think even people inside of open but I think even people inside of open would have had a hard time predicting would have had a hard time predicting would have had a hard time predicting exactly when this gets good. Um we've exactly when this gets good. Um we've exactly when this gets good. Um we've been excited about it for a while been excited about it for a while been excited about it for a while >> on um proactivity. >> on um proactivity. >> on um proactivity. >> Um Pulse was a really great first step >> Um Pulse was a really great first step >> Um Pulse was a really great first step because because because >> what we wanted to build was a form >> what we wanted to build was a form >> what we wanted to build was a form factor where you're not prompting the factor where you're not prompting the factor where you're not prompting the model like the model's prompting you. model like the model's prompting you. model like the model's prompting you. >> Um for the reasons that I described >> Um for the reasons that I described >> Um for the reasons that I described earlier, which is, you know, it's so earlier, which is, you know, it's so earlier, which is, you know, it's so hard for people to delegate and to hard for people to delegate and to hard for people to delegate and to figure out what their problems are. What figure out what their problems are. What figure out what their problems are. What if the eye understood your your goals if the eye understood your your goals if the eye understood your your goals and the things you're interested in and and the things you're interested in and and the things you're interested in and just could start being proactive on your just could start being proactive on your just could start being proactive on your behalf? behalf? behalf? um pulse is limited in the value it can um pulse is limited in the value it can um pulse is limited in the value it can provide for you because it's not provide for you because it's not provide for you because it's not connected to your life and it can't take connected to your life and it can't take connected to your life and it can't take action. So, it's producing information action. So, it's producing information action. So, it's producing information for you for you for you >> and people love that. You know, I love >> and people love that. You know, I love >> and people love that. You know, I love that. I've got mine running, too. that. I've got mine running, too. that. I've got mine running, too. >> But I think the magic begins when you >> But I think the magic begins when you >> But I think the magic begins when you have actions and proactivity because have actions and proactivity because have actions and proactivity because then it can begin speculatively then it can begin speculatively then it can begin speculatively actually, you know, um detecting, hey, actually, you know, um detecting, hey, actually, you know, um detecting, hey, you just landed where you were supposed you just landed where you were supposed you just landed where you were supposed to go. Um you know, I'm I'm I'm going to to go. Um you know, I'm I'm I'm going to to go. Um you know, I'm I'm I'm going to call a cab for you. or call a cab for you. or call a cab for you. or >> um you know if you're at work it's like >> um you know if you're at work it's like >> um you know if you're at work it's like hey I proactively ran this analysis hey I proactively ran this analysis hey I proactively ran this analysis because I saw your metrics dropped because I saw your metrics dropped because I saw your metrics dropped >> um so I think these things really >> um so I think these things really >> um so I think these things really compound and we need to nail multiple of compound and we need to nail multiple of compound and we need to nail multiple of the building blocks to really achieve the building blocks to really achieve the building blocks to really achieve the transformation um and the form the transformation um and the form the transformation um and the form factor that we hope for factor that we hope for factor that we hope for >> as you were answering those questions I >> as you were answering those questions I >> as you were answering those questions I now have uh 15 more questions for you so now have uh 15 more questions for you so now have uh 15 more questions for you so so so I hope you have 15 more minutes so so I hope you have 15 more minutes so so I hope you have 15 more minutes but um but um but um >> okay one by one we'll start with what >> okay one by one we'll start with what >> okay one by one we'll start with what you said on actions and tasks you said on actions and tasks you said on actions and tasks >> got it on timing tough to Okay. But is >> got it on timing tough to Okay. But is >> got it on timing tough to Okay. But is there a shape or ordinality of tasks and there a shape or ordinality of tasks and there a shape or ordinality of tasks and or or agents that that you think, hey, or or agents that that you think, hey, or or agents that that you think, hey, this is the kind of thing that's likely this is the kind of thing that's likely this is the kind of thing that's likely to come first whenever it does? to come first whenever it does? to come first whenever it does? >> I mean, the thing that's already come >> I mean, the thing that's already come >> I mean, the thing that's already come first is the uh domain specific agents, first is the uh domain specific agents, first is the uh domain specific agents, right? If you look at what's happening right? If you look at what's happening right? If you look at what's happening in in code, in in code, in in code, >> we're we're we're fully there. >> we're we're we're fully there. >> we're we're we're fully there. >> You know, it's it's mindbending, but >> You know, it's it's mindbending, but >> You know, it's it's mindbending, but we've got so many engineers um who who we've got so many engineers um who who we've got so many engineers um who who don't open their IDE like ever. And don't open their IDE like ever. And don't open their IDE like ever. And right right right >> for me as someone who you know used to >> for me as someone who you know used to >> for me as someone who you know used to code and then unfortunately got very code and then unfortunately got very code and then unfortunately got very very busy it's brought me back in the very busy it's brought me back in the very busy it's brought me back in the game. game. game. >> So um codeex and you know products like >> So um codeex and you know products like >> So um codeex and you know products like it is clearly a product that has escape it is clearly a product that has escape it is clearly a product that has escape velocity where people are absolutely velocity where people are absolutely velocity where people are absolutely using it for all kinds of agentic work using it for all kinds of agentic work using it for all kinds of agentic work and if you just take what people are and if you just take what people are and if you just take what people are doing doing doing >> and make it work even better >> and make it work even better >> and make it work even better >> you kind of get all the way there. Um, >> you kind of get all the way there. Um, >> you kind of get all the way there. Um, you know, I won't be surprised if you you know, I won't be surprised if you you know, I won't be surprised if you see this happen for other forms of sort see this happen for other forms of sort see this happen for other forms of sort of quantitative knowledge work just of quantitative knowledge work just of quantitative knowledge work just because it happens to have the because it happens to have the because it happens to have the properties that code has. It's testable. properties that code has. It's testable. properties that code has. It's testable. You know, if it worked or not, You know, if it worked or not, You know, if it worked or not, >> um, it's, you know, very RL friendly. >> um, it's, you know, very RL friendly. >> um, it's, you know, very RL friendly. >> Um, >> Um, >> Um, >> but um, uh, the the domain specific ones >> but um, uh, the the domain specific ones >> but um, uh, the the domain specific ones already work. I think the thing already work. I think the thing already work. I think the thing everyone's working for is, you know, everyone's working for is, you know, everyone's working for is, you know, general purpose agents that just general purpose agents that just general purpose agents that just >> kind of work for anything. >> kind of work for anything. >> kind of work for anything. >> Yeah. And I you know that's why I think >> Yeah. And I you know that's why I think >> Yeah. And I you know that's why I think you need to to win a consumer because you need to to win a consumer because you need to to win a consumer because it's very hard to train people into like it's very hard to train people into like it's very hard to train people into like okay okay okay >> um it can work like deep research was a >> um it can work like deep research was a >> um it can work like deep research was a consumer product and it's really was our consumer product and it's really was our consumer product and it's really was our first agentic first agentic first agentic >> uh thing out there >> uh thing out there >> uh thing out there >> um but I think what consumers want is I >> um but I think what consumers want is I >> um but I think what consumers want is I can just ask it anything and we'll do can just ask it anything and we'll do can just ask it anything and we'll do what what what >> um what needs to be done without any >> um what needs to be done without any >> um what needs to be done without any sort of retraining and um sort of retraining and um sort of retraining and um >> we'll get there just a matter of time >> we'll get there just a matter of time >> we'll get there just a matter of time >> at least a psychological goal is uh >> at least a psychological goal is uh >> at least a psychological goal is uh flight bookings bookings restaurant flight bookings bookings restaurant flight bookings bookings restaurant bookings, shopping, bookings, shopping, bookings, shopping, >> all this stuff. Um there are so many >> all this stuff. Um there are so many >> all this stuff. Um there are so many consumer problems and those are just the consumer problems and those are just the consumer problems and those are just the type of things that you would kick off, type of things that you would kick off, type of things that you would kick off, right? right? right? >> Yeah. >> Yeah. >> Yeah. >> The minute you have productivity, >> The minute you have productivity, >> The minute you have productivity, there's there's things you don't even there's there's things you don't even there's there's things you don't even think of as agentic tasks. think of as agentic tasks. think of as agentic tasks. >> Um like you're trying to get in shape. >> Um like you're trying to get in shape. >> Um like you're trying to get in shape. You don't think of that as a task you You don't think of that as a task you You don't think of that as a task you would delegate. would delegate. would delegate. >> Um unless you have a trainer, in which >> Um unless you have a trainer, in which >> Um unless you have a trainer, in which case you do, but most people don't, case you do, but most people don't, case you do, but most people don't, right? But if the EI knew that, it could right? But if the EI knew that, it could right? But if the EI knew that, it could totally start working in the background totally start working in the background totally start working in the background for you over very long periods of time for you over very long periods of time for you over very long periods of time and and getting you, you know, um, and and getting you, you know, um, and and getting you, you know, um, here's your fitness plan. Okay, I here's your fitness plan. Okay, I here's your fitness plan. Okay, I actually signed you up for this thing. actually signed you up for this thing. actually signed you up for this thing. You could imagine it being quite helpful You could imagine it being quite helpful You could imagine it being quite helpful if it's aligned with your with your if it's aligned with your with your if it's aligned with your with your long-term interest. long-term interest. long-term interest. >> You're going to give Ozanic a run for >> You're going to give Ozanic a run for >> You're going to give Ozanic a run for the money. the money. the money. >> We got to be careful what businesses we >> We got to be careful what businesses we >> We got to be careful what businesses we get into, but uh, hopefully we can help. get into, but uh, hopefully we can help. get into, but uh, hopefully we can help. >> That'll be great. Cannot wait. Cannot >> That'll be great. Cannot wait. Cannot >> That'll be great. Cannot wait. Cannot wait. Uh the second thing you said was wait. Uh the second thing you said was wait. Uh the second thing you said was um you know pro proactive users and that um you know pro proactive users and that um you know pro proactive users and that might require us to go beyond chat bots. might require us to go beyond chat bots. might require us to go beyond chat bots. >> What's an example of a modality that >> What's an example of a modality that >> What's an example of a modality that might take chat GPD beyond a chatbot? might take chat GPD beyond a chatbot? might take chat GPD beyond a chatbot? >> So chat will always be close to my >> So chat will always be close to my >> So chat will always be close to my heart. It's the way we grew up. Um, and heart. It's the way we grew up. Um, and heart. It's the way we grew up. Um, and it's an important modality to stay like it's an important modality to stay like it's an important modality to stay like I I I think I I I think I I I think >> it's less about chat and more about >> it's less about chat and more about >> it's less about chat and more about natural language to me where you know natural language to me where you know natural language to me where you know the fact that you can express yourself the fact that you can express yourself the fact that you can express yourself to the machine in ways that are very to the machine in ways that are very to the machine in ways that are very natural to you natural to you natural to you >> whether or not that's text whether or >> whether or not that's text whether or >> whether or not that's text whether or not that's voice whether or not that is not that's voice whether or not that is not that's voice whether or not that is you know um structured UI that is you know um structured UI that is you know um structured UI that is rendered by the model rendered by the model rendered by the model >> that is just very very powerful and >> that is just very very powerful and >> that is just very very powerful and that's here to stay but that's here to stay but that's here to stay but >> u I think the thing >> u I think the thing >> u I think the thing >> SA server >> SA server >> SA server >> that's right uh uh for those that don't >> that's right uh uh for those that don't >> that's right uh uh for those that don't know that's the name of our codebase um know that's the name of our codebase um know that's the name of our codebase um short for super assistant server Um short for super assistant server Um short for super assistant server Um because you know it's proof that this because you know it's proof that this because you know it's proof that this was always the vision and is always the was always the vision and is always the was always the vision and is always the vision. Um but uh you know the the the vision. Um but uh you know the the the vision. Um but uh you know the the the thing that that'll change I think is thing that that'll change I think is thing that that'll change I think is that chat is a great way of expressing that chat is a great way of expressing that chat is a great way of expressing your intent. It's a good way of your intent. It's a good way of your intent. It's a good way of communicating with the machine but it's communicating with the machine but it's communicating with the machine but it's not a great output. Um where in many not a great output. Um where in many not a great output. Um where in many cases what you want back is an artifact cases what you want back is an artifact cases what you want back is an artifact like here's your your your you know plan like here's your your your you know plan like here's your your your you know plan for your trip. Here is the analysis. for your trip. Here is the analysis. for your trip. Here is the analysis. >> Here is um you know an outcome that I >> Here is um you know an outcome that I >> Here is um you know an outcome that I delivered for you. you know, I just made delivered for you. you know, I just made delivered for you. you know, I just made you five bucks. you five bucks. you five bucks. >> Like, this is what I want my AI doing >> Like, this is what I want my AI doing >> Like, this is what I want my AI doing for me, right? Yeah, totally. I mean, for me, right? Yeah, totally. I mean, for me, right? Yeah, totally. I mean, this is what people care about, right? this is what people care about, right? this is what people care about, right? And and and and I think chat will always And and and and I think chat will always And and and and I think chat will always be there as the way that you sort of be there as the way that you sort of be there as the way that you sort of disambiguate your intent and you kick disambiguate your intent and you kick disambiguate your intent and you kick off the task, off the task, off the task, >> but I don't think it's necessarily the >> but I don't think it's necessarily the >> but I don't think it's necessarily the the the final deliverable. And I think the the final deliverable. And I think the the final deliverable. And I think that's that's that's the way in which we that's that's that's the way in which we that's that's that's the way in which we can evolve. So hopefully that's a very can evolve. So hopefully that's a very can evolve. So hopefully that's a very graceful transition because I'm very graceful transition because I'm very graceful transition because I'm very lucky and it's hard earned, lucky and it's hard earned, lucky and it's hard earned, >> you know, to to have a billion people >> you know, to to have a billion people >> you know, to to have a billion people coming to you weekly for a thing that coming to you weekly for a thing that coming to you weekly for a thing that they love. they love. they love. >> Yeah. But I think it's a great jumping >> Yeah. But I think it's a great jumping >> Yeah. But I think it's a great jumping off point because we have so much off point because we have so much off point because we have so much unsatisfied intent from people where unsatisfied intent from people where unsatisfied intent from people where they're trying clearly trying to do they're trying clearly trying to do they're trying clearly trying to do something and chat is helpful enough something and chat is helpful enough something and chat is helpful enough >> but it could be so much more helpful. Um >> but it could be so much more helpful. Um >> but it could be so much more helpful. Um and I think that's where we evolve. and I think that's where we evolve. and I think that's where we evolve. >> Yeah. And you must be sitting on so much >> Yeah. And you must be sitting on so much >> Yeah. And you must be sitting on so much of this data where people are showing up of this data where people are showing up of this data where people are showing up to chat and attempting as you said uh to chat and attempting as you said uh to chat and attempting as you said uh three years ago they were at least three years ago they were at least three years ago they were at least making the attempt. making the attempt. making the attempt. >> Yeah. >> Yeah. >> Yeah. >> So you might have at least the frequency >> So you might have at least the frequency >> So you might have at least the frequency histogram of like hey here are all the histogram of like hey here are all the histogram of like hey here are all the things that people want to achieve with things that people want to achieve with things that people want to achieve with us. We do uh we have like really awesome us. We do uh we have like really awesome us. We do uh we have like really awesome you know um classifiers that run you know um classifiers that run you know um classifiers that run automatically. It's fully privacy automatically. It's fully privacy automatically. It's fully privacy preserving but gives us a sense of you preserving but gives us a sense of you preserving but gives us a sense of you know what use cases people have know what use cases people have know what use cases people have >> and it's important right because when >> and it's important right because when >> and it's important right because when you make a new model you make a model you make a new model you make a model you make a new model you make a model update you want to know what use cases update you want to know what use cases update you want to know what use cases just got better what use cases got just got better what use cases got just got better what use cases got worse. worse. worse. >> Yeah. >> Yeah. >> Yeah. >> Um and that's not always always trivial >> Um and that's not always always trivial >> Um and that's not always always trivial to figure out unless you have really to figure out unless you have really to figure out unless you have really good analytics on the system. But so good analytics on the system. But so good analytics on the system. But so much of my learning is actually much of my learning is actually much of my learning is actually qualitative where I will just you know I qualitative where I will just you know I qualitative where I will just you know I have a habit of reaching out to a fairly have a habit of reaching out to a fairly have a habit of reaching out to a fairly random set of users to just figure out random set of users to just figure out random set of users to just figure out what they're doing what they're doing what they're doing >> and I've never worked on a product where >> and I've never worked on a product where >> and I've never worked on a product where three and a half years later you're three and a half years later you're three and a half years later you're still learning every time because still learning every time because still learning every time because usually by that time you know what the usually by that time you know what the usually by that time you know what the use cases are that your product can you use cases are that your product can you use cases are that your product can you know deliver on know deliver on know deliver on >> but our tech is so unusual in the fact >> but our tech is so unusual in the fact >> but our tech is so unusual in the fact that I keep learning about something that I keep learning about something that I keep learning about something crazy I didn't know was possible. crazy I didn't know was possible. crazy I didn't know was possible. >> Wow that's awesome. But basically a >> Wow that's awesome. But basically a >> Wow that's awesome. But basically a billion users, I suspect a small billion users, I suspect a small billion users, I suspect a small fraction of them are power users fraction of them are power users fraction of them are power users >> who are uh getting maybe thousands maybe >> who are uh getting maybe thousands maybe >> who are uh getting maybe thousands maybe maybe maybe tens of thousands of of of maybe maybe tens of thousands of of of maybe maybe tens of thousands of of of value on on their $200 subscription. value on on their $200 subscription. value on on their $200 subscription. >> Yeah. >> Yeah. >> Yeah. >> Um the vast majority is is you know >> Um the vast majority is is you know >> Um the vast majority is is you know middle of the pack and then and and a middle of the pack and then and and a middle of the pack and then and and a few call it casual users who are you few call it casual users who are you few call it casual users who are you know start using Chad GPD as search know start using Chad GPD as search know start using Chad GPD as search maybe or or or teach me about AI or or maybe or or or teach me about AI or or maybe or or or teach me about AI or or help me with my homework. Um what is help me with my homework. Um what is help me with my homework. Um what is your focus like maybe in those your focus like maybe in those your focus like maybe in those constituents power users, casual users constituents power users, casual users constituents power users, casual users and and early users or however you frame and and early users or however you frame and and early users or however you frame it, what is our focus on for each of it, what is our focus on for each of it, what is our focus on for each of those three factions? those three factions? those three factions? >> Yeah. Yeah. Well, first of all, I feel >> Yeah. Yeah. Well, first of all, I feel >> Yeah. Yeah. Well, first of all, I feel accountable to our entire user base. In accountable to our entire user base. In accountable to our entire user base. In fact, our non-users too because you fact, our non-users too because you fact, our non-users too because you products like like Chachet can have real products like like Chachet can have real products like like Chachet can have real externalities on on all humans. externalities on on all humans. externalities on on all humans. >> Yeah. But when I think about sort of the >> Yeah. But when I think about sort of the >> Yeah. But when I think about sort of the way we build, way we build, way we build, it's really useful to imagine the it's really useful to imagine the it's really useful to imagine the extremes. Um, one extreme being a user extremes. Um, one extreme being a user extremes. Um, one extreme being a user who doesn't care about AI at all. who doesn't care about AI at all. who doesn't care about AI at all. >> Um, who has a busy life. Um, and um, um, >> Um, who has a busy life. Um, and um, um, >> Um, who has a busy life. Um, and um, um, needs to be convinced of, you know, the needs to be convinced of, you know, the needs to be convinced of, you know, the value that we can provide because that value that we can provide because that value that we can provide because that forces you to really nail the interface forces you to really nail the interface forces you to really nail the interface and to expose the capabilities uh, that and to expose the capabilities uh, that and to expose the capabilities uh, that are hidden in the model in a way that are hidden in the model in a way that are hidden in the model in a way that people can actually gro. And then the people can actually gro. And then the people can actually gro. And then the other useful extreme is you know um our other useful extreme is you know um our other useful extreme is you know um our our power user base because power users our power user base because power users our power user base because power users are the users who teach us what's are the users who teach us what's are the users who teach us what's possible. Um possible. Um possible. Um >> um it's actually impossible for us to do >> um it's actually impossible for us to do >> um it's actually impossible for us to do all the product discovery all the product discovery all the product discovery um on our own um on our own um on our own >> simply by because of how empirical >> simply by because of how empirical >> simply by because of how empirical >> this technology is um and how much you >> this technology is um and how much you >> this technology is um and how much you actually learn post launch. actually learn post launch. actually learn post launch. >> So building you know um for each of >> So building you know um for each of >> So building you know um for each of those extremes can be valuable. Uh but those extremes can be valuable. Uh but those extremes can be valuable. Uh but our user base is incredibly diverse and our user base is incredibly diverse and our user base is incredibly diverse and um people have so many different use um people have so many different use um people have so many different use cases and this is why you know I like to cases and this is why you know I like to cases and this is why you know I like to look look at all kinds of different look look at all kinds of different look look at all kinds of different segmentations not just frequency but segmentations not just frequency but segmentations not just frequency but also you know what use cases are you also you know what use cases are you also you know what use cases are you coming to us for. Um coming to us for. Um coming to us for. Um >> but um definitely huge variety in the HP >> but um definitely huge variety in the HP >> but um definitely huge variety in the HP user base. user base. user base. >> Yeah >> Yeah >> Yeah >> I look up to Mac OS for example as an >> I look up to Mac OS for example as an >> I look up to Mac OS for example as an example where it really works for people example where it really works for people example where it really works for people who don't understand technology at all. who don't understand technology at all. who don't understand technology at all. it's entirely magical but if you are a it's entirely magical but if you are a it's entirely magical but if you are a power user you've got terminal you got power user you've got terminal you got power user you've got terminal you got settings you configure almost anything settings you configure almost anything settings you configure almost anything in Mac OS in Mac OS in Mac OS >> and it's really beautifully done where >> and it's really beautifully done where >> and it's really beautifully done where the complexity is progressively the complexity is progressively the complexity is progressively disclosed disclosed disclosed >> so um you can interact with it and love >> so um you can interact with it and love >> so um you can interact with it and love love the simplicity of it all but you love the simplicity of it all but you love the simplicity of it all but you can also got all the knobs and can also got all the knobs and can also got all the knobs and developers love it right developers love it right developers love it right >> and so I think this is kind of the >> and so I think this is kind of the >> and so I think this is kind of the inspiration for how we want to be in inspiration for how we want to be in inspiration for how we want to be in chatbt that doesn't mean we always live chatbt that doesn't mean we always live chatbt that doesn't mean we always live up to it but um it means that building up to it but um it means that building up to it but um it means that building for powers is extremely important for powers is extremely important for powers is extremely important >> and you know that's not just a property >> and you know that's not just a property >> and you know that's not just a property that I'm think is sort of aesthetically that I'm think is sort of aesthetically that I'm think is sort of aesthetically exciting. It's also really important in exciting. It's also really important in exciting. It's also really important in AI because it's the power users who show AI because it's the power users who show AI because it's the power users who show you what's possible. you what's possible. you what's possible. >> They are actually doing the product >> They are actually doing the product >> They are actually doing the product discovery discovery discovery >> because it would be impossible for us >> because it would be impossible for us >> because it would be impossible for us with such an empirical tech to do all with such an empirical tech to do all with such an empirical tech to do all the product discovery on our own. the product discovery on our own. the product discovery on our own. >> So the type of user who subscribes to >> So the type of user who subscribes to >> So the type of user who subscribes to Chad GPD Pro who used codeex before it Chad GPD Pro who used codeex before it Chad GPD Pro who used codeex before it quite worked quite worked quite worked >> who is now the strongest advocate of of >> who is now the strongest advocate of of >> who is now the strongest advocate of of cool tools tokens and teaching us what's cool tools tokens and teaching us what's cool tools tokens and teaching us what's what's possible. um that is an what's possible. um that is an what's possible. um that is an incredible valuable incredibly valuable incredible valuable incredibly valuable incredible valuable incredibly valuable member of the community member of the community member of the community >> and it might not show up in your you >> and it might not show up in your you >> and it might not show up in your you know um weekly active users as just one know um weekly active users as just one know um weekly active users as just one number right um but this is exactly why number right um but this is exactly why number right um but this is exactly why there isn't like a single north star there isn't like a single north star there isn't like a single north star >> and you really need to need need to take >> and you really need to need need to take >> and you really need to need need to take these different segments very seriously these different segments very seriously these different segments very seriously so um I love building for power users so um I love building for power users so um I love building for power users >> um >> um >> um >> and uh you know you you asked on you >> and uh you know you you asked on you >> and uh you know you you asked on you know token consumption etc it's so know token consumption etc it's so know token consumption etc it's so fascinating to see there's people who fascinating to see there's people who fascinating to see there's people who get incredible value um out of these get incredible value um out of these get incredible value um out of these products and u watching what they do is products and u watching what they do is products and u watching what they do is very informative. very informative. very informative. >> Okay. So, so we're very focused on the >> Okay. So, so we're very focused on the >> Okay. So, so we're very focused on the entire user base. Um learn a lot from entire user base. Um learn a lot from entire user base. Um learn a lot from the power users. Um the power users. Um the power users. Um >> you know the other thing I might say is >> you know the other thing I might say is >> you know the other thing I might say is the power users right now are getting um the power users right now are getting um the power users right now are getting um >> a lot of value almost too much value >> a lot of value almost too much value >> a lot of value almost too much value >> and a lot of >> and a lot of >> and a lot of >> no such thing. >> no such thing. >> no such thing. >> No such thing. the the the analog that >> No such thing. the the the analog that >> No such thing. the the the analog that is most common is the Uber and Lyft of is most common is the Uber and Lyft of is most common is the Uber and Lyft of the 2015 era, the 2015 era, the 2015 era, >> right? >> right? >> right? >> And you know, it took it took a while, >> And you know, it took it took a while, >> And you know, it took it took a while, but I know you were thinking about it a but I know you were thinking about it a but I know you were thinking about it a lot. I know you guys are thinking about lot. I know you guys are thinking about lot. I know you guys are thinking about pricing quite a bit. pricing quite a bit. pricing quite a bit. >> Yeah. >> Yeah. >> Yeah. >> Um maybe tell us a little bit about >> Um maybe tell us a little bit about >> Um maybe tell us a little bit about pricing. Um pricing. Um pricing. Um >> you know, right now pricing is pretty >> you know, right now pricing is pretty >> you know, right now pricing is pretty simple. uh is there a is there a path simple. uh is there a is there a path simple. uh is there a is there a path for for for folks who are getting a lot for for for folks who are getting a lot for for for folks who are getting a lot of great value to price that product of great value to price that product of great value to price that product differently and and and you know meet differently and and and you know meet differently and and and you know meet them where they are and and and and and them where they are and and and and and them where they are and and and and and the other way on the other side the other way on the other side the other way on the other side >> I mean pricing is there's no world in >> I mean pricing is there's no world in >> I mean pricing is there's no world in which pricing doesn't significantly which pricing doesn't significantly which pricing doesn't significantly evolve when evolve when evolve when >> the technology is changing this quickly >> the technology is changing this quickly >> the technology is changing this quickly right chat GPT originally was entirely right chat GPT originally was entirely right chat GPT originally was entirely free and the reason for that was that it free and the reason for that was that it free and the reason for that was that it was intended to be a demo was intended to be a demo was intended to be a demo >> and we were going to wind it down after >> and we were going to wind it down after >> and we were going to wind it down after a month a month a month >> we then realized that the demo went >> we then realized that the demo went >> we then realized that the demo went viral And people loved the demo and it viral And people loved the demo and it viral And people loved the demo and it was actually a product and but we was actually a product and but we was actually a product and but we realized to be a product you can't take realized to be a product you can't take realized to be a product you can't take the product down every time you're at the product down every time you're at the product down every time you're at capacity. So we you know ship capacity. So we you know ship capacity. So we you know ship subscriptions simply because it could subscriptions simply because it could subscriptions simply because it could shape the demand. It shape the demand. It shape the demand. It >> was a way of gracefully turning users >> was a way of gracefully turning users >> was a way of gracefully turning users away when we had to turn away someone away when we had to turn away someone away when we had to turn away someone and it felt like the fairest and most and it felt like the fairest and most and it felt like the fairest and most equitable way of doing so is saying hey equitable way of doing so is saying hey equitable way of doing so is saying hey you know if you really need this product you know if you really need this product you know if you really need this product pay a subscription fee and you got it. pay a subscription fee and you got it. pay a subscription fee and you got it. Then we figured out how to make the Then we figured out how to make the Then we figured out how to make the product stable and we had the choice of product stable and we had the choice of product stable and we had the choice of do we keep the subscription thing or do do we keep the subscription thing or do do we keep the subscription thing or do we go back to free and we realized we we go back to free and we realized we we go back to free and we realized we had consistently more tech that we had consistently more tech that we had consistently more tech that we couldn't scale. GPD4 being the first couldn't scale. GPD4 being the first couldn't scale. GPD4 being the first example because we had way too many free example because we had way too many free example because we had way too many free users to serve GPD4 and we put it behind users to serve GPD4 and we put it behind users to serve GPD4 and we put it behind the plus plan. And so, you know, the way the plus plan. And so, you know, the way the plus plan. And so, you know, the way we stumbled into subscriptions was was we stumbled into subscriptions was was we stumbled into subscriptions was was sort of accidental by trying to just sort of accidental by trying to just sort of accidental by trying to just solve for the user. Um, and it felt like solve for the user. Um, and it felt like solve for the user. Um, and it felt like the right way at the time um to to the right way at the time um to to the right way at the time um to to provide maximal access to our to to to provide maximal access to our to to to provide maximal access to our to to to our tech. Um, our tech. Um, our tech. Um, since then we've had so many other since then we've had so many other since then we've had so many other breakthroughs including test time breakthroughs including test time breakthroughs including test time compute where you can scale up compute where you can scale up compute where you can scale up >> um um intelligence >> um um intelligence >> um um intelligence >> um um kind of um as much as you want. >> um um kind of um as much as you want. >> um um kind of um as much as you want. Yeah, Yeah, Yeah, >> more or less. And um you know, it took >> more or less. And um you know, it took >> more or less. And um you know, it took us, you know, in the entire industry a us, you know, in the entire industry a us, you know, in the entire industry a little bit of time to turn that into little bit of time to turn that into little bit of time to turn that into product value, but we're here now where, product value, but we're here now where, product value, but we're here now where, you know, our our our our you know, our our our our you know, our our our our power users want to use more and more power users want to use more and more power users want to use more and more and more intelligence. And you it's and more intelligence. And you it's and more intelligence. And you it's possible that, you know, in in the possible that, you know, in in the possible that, you know, in in the current era having unlimited plan is current era having unlimited plan is current era having unlimited plan is like having unlimited electricity plan. like having unlimited electricity plan. like having unlimited electricity plan. You know, it just doesn't make sense You know, it just doesn't make sense You know, it just doesn't make sense because like, you know, people may need because like, you know, people may need because like, you know, people may need a lot a lot of electricity and they're a lot a lot of electricity and they're a lot a lot of electricity and they're getting a lot of value out of that. getting a lot of value out of that. getting a lot of value out of that. There's a reason you can't buy that, There's a reason you can't buy that, There's a reason you can't buy that, right? So, um, obviously I want to be right? So, um, obviously I want to be right? So, um, obviously I want to be really thoughtful about the way that we really thoughtful about the way that we really thoughtful about the way that we evolve our our plans and SKs and evolve our our plans and SKs and evolve our our plans and SKs and subscriptions, but you would be subscriptions, but you would be subscriptions, but you would be incredibly sub, you know, surprised if incredibly sub, you know, surprised if incredibly sub, you know, surprised if it didn't change given the magnitude and it didn't change given the magnitude and it didn't change given the magnitude and profoundness of of the technical profoundness of of the technical profoundness of of the technical breakthroughs that we've had and the breakthroughs that we've had and the breakthroughs that we've had and the product breakthroughs that follow. product breakthroughs that follow. product breakthroughs that follow. >> Yeah. Um, and you know, relatedly, so so >> Yeah. Um, and you know, relatedly, so so >> Yeah. Um, and you know, relatedly, so so I I imagine you're going to have I I imagine you're going to have I I imagine you're going to have something for the power users. something for the power users. something for the power users. >> Mhm. >> Mhm. >> Mhm. >> Um, what about the other side? How do we >> Um, what about the other side? How do we >> Um, what about the other side? How do we get um the casual users into the into get um the casual users into the into get um the casual users into the into the wheel and and still uh monetize the wheel and and still uh monetize the wheel and and still uh monetize them? them? them? >> As mentioned, you know, our our business >> As mentioned, you know, our our business >> As mentioned, you know, our our business model is will evolve and the northstar model is will evolve and the northstar model is will evolve and the northstar is access, right? We we we would like to is access, right? We we we would like to is access, right? We we we would like to pick a um way of of of of you providing pick a um way of of of of you providing pick a um way of of of of you providing an off we want to pro provide an an off we want to pro provide an an off we want to pro provide an offering that maximizes um the number of offering that maximizes um the number of offering that maximizes um the number of people can who can access our most people can who can access our most people can who can access our most powerful tools. I think for the longest powerful tools. I think for the longest powerful tools. I think for the longest time that has been subscriptions. time that has been subscriptions. time that has been subscriptions. >> Um, subscriptions have the downside of >> Um, subscriptions have the downside of >> Um, subscriptions have the downside of the fact that, you know, in many markets the fact that, you know, in many markets the fact that, you know, in many markets people don't people don't people don't >> have credit cards or they don't use >> have credit cards or they don't use >> have credit cards or they don't use credit cards to subscribe to software. credit cards to subscribe to software. credit cards to subscribe to software. Um, and we're interested uh in other Um, and we're interested uh in other Um, and we're interested uh in other ways that can maximize access of of the ways that can maximize access of of the ways that can maximize access of of the tech. Um, tech. Um, tech. Um, >> our ads pilots are in that spirit. You >> our ads pilots are in that spirit. You >> our ads pilots are in that spirit. You know, we we really view it as a tool of know, we we really view it as a tool of know, we we really view it as a tool of bringing chatt and our intelligence most bringing chatt and our intelligence most bringing chatt and our intelligence most broadly broadly broadly >> to anyone around the world. M >> to anyone around the world. M >> to anyone around the world. M >> um and it is an example of how we >> um and it is an example of how we >> um and it is an example of how we constantly need to evolve and figure out constantly need to evolve and figure out constantly need to evolve and figure out the best way to to you know bring the the best way to to you know bring the the best way to to you know bring the demand in line with what we are able to demand in line with what we are able to demand in line with what we are able to offer. offer. offer. >> Makes sense. Makes sense. You know the >> Makes sense. Makes sense. You know the >> Makes sense. Makes sense. You know the ads the ads piece is um is is has been a ads the ads piece is um is is has been a ads the ads piece is um is is has been a tricky one because you know Sam has tricky one because you know Sam has tricky one because you know Sam has historically expressed reluctance about historically expressed reluctance about historically expressed reluctance about ads and um ads and um ads and um >> you know we've got to maintain a lot of >> you know we've got to maintain a lot of >> you know we've got to maintain a lot of trust um with while delivering that. So, trust um with while delivering that. So, trust um with while delivering that. So, um, I guess what changed? um, I guess what changed? um, I guess what changed? >> I think we've talked about this several >> I think we've talked about this several >> I think we've talked about this several times in my my history at OpenAI, and times in my my history at OpenAI, and times in my my history at OpenAI, and every time it came up, we said if if we every time it came up, we said if if we every time it came up, we said if if we were to do ads, we'd have to be really were to do ads, we'd have to be really were to do ads, we'd have to be really thoughtful about the way we do it. Um, thoughtful about the way we do it. Um, thoughtful about the way we do it. Um, so the first thing we did, you know, so the first thing we did, you know, so the first thing we did, you know, starting, you know, end of last year was starting, you know, end of last year was starting, you know, end of last year was to really engage the company on if we to really engage the company on if we to really engage the company on if we put ads in chat GPT, how should we put ads in chat GPT, how should we put ads in chat GPT, how should we approach it? What should the principles approach it? What should the principles approach it? What should the principles weigh? what be how do you preserve the weigh? what be how do you preserve the weigh? what be how do you preserve the things that are magical about chat GBT things that are magical about chat GBT things that are magical about chat GBT while getting the benefits of ads which while getting the benefits of ads which while getting the benefits of ads which you know is is is our ability to bring you know is is is our ability to bring you know is is is our ability to bring >> um our most advanced tech to to to >> um our most advanced tech to to to >> um our most advanced tech to to to anyone um regardless of their ability to anyone um regardless of their ability to anyone um regardless of their ability to pay pay pay >> and um I really love where we ended up >> and um I really love where we ended up >> and um I really love where we ended up on the principal side on the principal side on the principal side >> on the experience side >> on the experience side >> on the experience side >> um we're very very early but on the >> um we're very very early but on the >> um we're very very early but on the principal side I feel really proud principal side I feel really proud principal side I feel really proud because you know it's it's very because you know it's it's very because you know it's it's very important that the answer of chatbt be important that the answer of chatbt be important that the answer of chatbt be independent as an example independent as an example independent as an example >> respecting user privacy is very >> respecting user privacy is very >> respecting user privacy is very important and there's a lot to learn um important and there's a lot to learn um important and there's a lot to learn um from you know the way that tech has from you know the way that tech has from you know the way that tech has evolved over the last few years evolved over the last few years evolved over the last few years >> um or really last decade um >> um or really last decade um >> um or really last decade um >> um and I I like that the principles are >> um and I I like that the principles are >> um and I I like that the principles are out there before we've even really out there before we've even really out there before we've even really gotten started um like we're very early gotten started um like we're very early gotten started um like we're very early with our pilots with our pilots with our pilots >> um you know it it's kind of interesting >> um you know it it's kind of interesting >> um you know it it's kind of interesting I was obviously very anxiously and I was obviously very anxiously and I was obviously very anxiously and eagerly looking at um our support um eagerly looking at um our support um eagerly looking at um our support um inbounds and data and um the most common inbounds and data and um the most common inbounds and data and um the most common inquiry about ads is not you know how do inquiry about ads is not you know how do inquiry about ads is not you know how do disable ads or turn off ads, but it's disable ads or turn off ads, but it's disable ads or turn off ads, but it's like how do I run an ad? like how do I run an ad? like how do I run an ad? >> Um because the entire ecosystem is >> Um because the entire ecosystem is >> Um because the entire ecosystem is really excited to be part of the story really excited to be part of the story really excited to be part of the story and to figure out a way to talk to chatb and to figure out a way to talk to chatb and to figure out a way to talk to chatb users. So, users. So, users. So, >> um there's a lot more to come. Um but I >> um there's a lot more to come. Um but I >> um there's a lot more to come. Um but I I I'm I'm very eager to get this right. I I'm I'm very eager to get this right. I I'm I'm very eager to get this right. >> Yeah. Yeah. I'm sure you guys will. Um >> Yeah. Yeah. I'm sure you guys will. Um >> Yeah. Yeah. I'm sure you guys will. Um switching gears, Nick, um something you switching gears, Nick, um something you switching gears, Nick, um something you and I have spoken about a little bit is, and I have spoken about a little bit is, and I have spoken about a little bit is, you know, distribution and partnerships. you know, distribution and partnerships. you know, distribution and partnerships. Uh there's a couple of big partnerships Uh there's a couple of big partnerships Uh there's a couple of big partnerships last year. Um Apple Reliance with with last year. Um Apple Reliance with with last year. Um Apple Reliance with with Gemini, those are two big user bases, Gemini, those are two big user bases, Gemini, those are two big user bases, right? A lot of India, a lot of the iOS right? A lot of India, a lot of the iOS right? A lot of India, a lot of the iOS users. Um talk tell us a little bit how users. Um talk tell us a little bit how users. Um talk tell us a little bit how you think about partnerships for Chad you think about partnerships for Chad you think about partnerships for Chad GPT to to to meet the meet the user GPT to to to meet the meet the user GPT to to to meet the meet the user base. Um and maybe specifically on those base. Um and maybe specifically on those base. Um and maybe specifically on those two as well. two as well. two as well. Look, um I think partnerships are a Look, um I think partnerships are a Look, um I think partnerships are a great way to to bring two two two two great way to to bring two two two two great way to to bring two two two two products together and to you know products together and to you know products together and to you know >> um expose >> um expose >> um expose um something like chatt to um people who um something like chatt to um people who um something like chatt to um people who might not other otherwise have might not other otherwise have might not other otherwise have encountered it. encountered it. encountered it. >> Um the thing that I care about most when >> Um the thing that I care about most when >> Um the thing that I care about most when considering something um like a considering something um like a considering something um like a partnership is what is the what is the partnership is what is the what is the partnership is what is the what is the user experience and can we make it user experience and can we make it user experience and can we make it amazing? Um because at the end of the amazing? Um because at the end of the amazing? Um because at the end of the day um when you look at um what's going day um when you look at um what's going day um when you look at um what's going on in the market um you can get users to on in the market um you can get users to on in the market um you can get users to click on things, you can get them to tap click on things, you can get them to tap click on things, you can get them to tap any sort of product um especially if it any sort of product um especially if it any sort of product um especially if it looks like a product they recognize etc. looks like a product they recognize etc. looks like a product they recognize etc. >> Um but if the experience isn't truly >> Um but if the experience isn't truly >> Um but if the experience isn't truly awesome um you people will churn or they awesome um you people will churn or they awesome um you people will churn or they will you know at least not retain in the will you know at least not retain in the will you know at least not retain in the way that you know we've been lucky to way that you know we've been lucky to way that you know we've been lucky to retain them on chatbt. So for that retain them on chatbt. So for that retain them on chatbt. So for that reason you know I'm super interested in reason you know I'm super interested in reason you know I'm super interested in in paths like that. Um but it needs to in paths like that. Um but it needs to in paths like that. Um but it needs to be great. Uh it needs to acrue to the be great. Uh it needs to acrue to the be great. Uh it needs to acrue to the user. Um we are very lucky to have um a user. Um we are very lucky to have um a user. Um we are very lucky to have um a great brand and a recognizable product great brand and a recognizable product great brand and a recognizable product um for many many folks and I want to um for many many folks and I want to um for many many folks and I want to make sure that anything we do is make sure that anything we do is make sure that anything we do is accretive to um um to all that. accretive to um um to all that. accretive to um um to all that. >> Nick, you are uh you're a master of >> Nick, you are uh you're a master of >> Nick, you are uh you're a master of trade-offs. You must be making a lot of trade-offs. You must be making a lot of trade-offs. You must be making a lot of trade-offs right now. trade-offs right now. trade-offs right now. >> Uh um tell us about tell us about some >> Uh um tell us about tell us about some >> Uh um tell us about tell us about some of the trade-offs you're making. tell us of the trade-offs you're making. tell us of the trade-offs you're making. tell us about, you know, an a trade-off that you about, you know, an a trade-off that you about, you know, an a trade-off that you might be making that people don't might be making that people don't might be making that people don't appreciate uh from the outside. appreciate uh from the outside. appreciate uh from the outside. >> There are a lot of trade-offs um indeed >> There are a lot of trade-offs um indeed >> There are a lot of trade-offs um indeed and um for different reasons, right? Um and um for different reasons, right? Um and um for different reasons, right? Um um the what I encounter a lot is trading um the what I encounter a lot is trading um the what I encounter a lot is trading off off off delivering on the people on on the use delivering on the people on on the use delivering on the people on on the use cases that exist in the product today cases that exist in the product today cases that exist in the product today and making them better versus and making them better versus and making them better versus productizing you know step change productizing you know step change productizing you know step change technology that's going to generate a technology that's going to generate a technology that's going to generate a whole another set of use cases whole another set of use cases whole another set of use cases >> because when you think about how chatb >> because when you think about how chatb >> because when you think about how chatb came to be it was a totally open-ended came to be it was a totally open-ended came to be it was a totally open-ended product. It was basically a user product. It was basically a user product. It was basically a user experience around a technical experience around a technical experience around a technical breakthrough. breakthrough. breakthrough. >> And we couldn't have told you all the >> And we couldn't have told you all the >> And we couldn't have told you all the ways that people find it valuable, ways that people find it valuable, ways that people find it valuable, >> but putting it out there was really >> but putting it out there was really >> but putting it out there was really important because it allowed us us to important because it allowed us us to important because it allowed us us to discover and the world to discover what discover and the world to discover what discover and the world to discover what we can do. we can do. we can do. >> And then postg >> And then postg >> And then postg um we can obviously very systematically um we can obviously very systematically um we can obviously very systematically go and improve on the things that people go and improve on the things that people go and improve on the things that people actually want to use it for. And when actually want to use it for. And when actually want to use it for. And when you're at a company in this moment where you're at a company in this moment where you're at a company in this moment where you both have such amazing traction with you both have such amazing traction with you both have such amazing traction with what exists today and the most what exists today and the most what exists today and the most mind-bending breakthroughs on the mind-bending breakthroughs on the mind-bending breakthroughs on the research side, the balance you have to research side, the balance you have to research side, the balance you have to strike is making the core product you strike is making the core product you strike is making the core product you have better today with all the things have better today with all the things have better today with all the things that matter, latency, um reliability, um that matter, latency, um reliability, um that matter, latency, um reliability, um making the use cases really great that making the use cases really great that making the use cases really great that people come to people come to people come to >> with um you know providing access to to >> with um you know providing access to to >> with um you know providing access to to the step change um And um uh you we try the step change um And um uh you we try the step change um And um uh you we try to get the balance right, but we're a to get the balance right, but we're a to get the balance right, but we're a small team and we don't always get it small team and we don't always get it small team and we don't always get it right. And for that reason, it's one of right. And for that reason, it's one of right. And for that reason, it's one of the most difficult um trade-offs that I the most difficult um trade-offs that I the most difficult um trade-offs that I have to deal with. have to deal with. have to deal with. >> Nick, I imagine one of the hardest >> Nick, I imagine one of the hardest >> Nick, I imagine one of the hardest trade-offs you guys make here is those trade-offs you guys make here is those trade-offs you guys make here is those uh GPUs that are melting between chat uh GPUs that are melting between chat uh GPUs that are melting between chat GPT, between codecs research. Uh how do GPT, between codecs research. Uh how do GPT, between codecs research. Uh how do you guys uh allocate the GPUs? you guys uh allocate the GPUs? you guys uh allocate the GPUs? >> That is a very good question. Um and >> That is a very good question. Um and >> That is a very good question. Um and I'll let you know when I figure it out. I'll let you know when I figure it out. I'll let you know when I figure it out. Just kidding. you know, we we've gotten Just kidding. you know, we we've gotten Just kidding. you know, we we've gotten we've gotten a lot better at this. Um, I we've gotten a lot better at this. Um, I we've gotten a lot better at this. Um, I really hope, by the way, to be at a really hope, by the way, to be at a really hope, by the way, to be at a point one day, and I've yet to reach point one day, and I've yet to reach point one day, and I've yet to reach that point, where that point, where that point, where >> we don't have to face this trade-off >> we don't have to face this trade-off >> we don't have to face this trade-off because it's really painful to have real because it's really painful to have real because it's really painful to have real user demand user demand user demand >> uh for products that you can't serve. >> uh for products that you can't serve. >> uh for products that you can't serve. >> Um, like you know, if if you only ever >> Um, like you know, if if you only ever >> Um, like you know, if if you only ever worked in software, that's entirely worked in software, that's entirely worked in software, that's entirely unusual dynamic, right? Where you just, unusual dynamic, right? Where you just, unusual dynamic, right? Where you just, you know, or you were limited by this you know, or you were limited by this you know, or you were limited by this zero sum resource out there. zero sum resource out there. zero sum resource out there. >> Um, >> Um, >> Um, >> the marketplaces have it. Um um but you >> the marketplaces have it. Um um but you >> the marketplaces have it. Um um but you know I think pure software doesn't know I think pure software doesn't know I think pure software doesn't doesn't really have the dynamic right. doesn't really have the dynamic right. doesn't really have the dynamic right. >> Yeah. >> Yeah. >> Yeah. >> So um you one thing we try to do >> So um you one thing we try to do >> So um you one thing we try to do obviously we prioritize our existing obviously we prioritize our existing obviously we prioritize our existing users um first we want to provide a fast users um first we want to provide a fast users um first we want to provide a fast reliable product um and that is critical reliable product um and that is critical reliable product um and that is critical and table stakes. and table stakes. and table stakes. >> Then when you look at new capabilities >> Then when you look at new capabilities >> Then when you look at new capabilities the sort of na naive the sort of na naive the sort of na naive >> u business school thing to do would be >> u business school thing to do would be >> u business school thing to do would be to probably you know look at revenue to probably you know look at revenue to probably you know look at revenue incremental revenue per GPU or something incremental revenue per GPU or something incremental revenue per GPU or something like that. Yeah, like that. Yeah, like that. Yeah, >> but this is where it's more an art than >> but this is where it's more an art than >> but this is where it's more an art than a science because we often have new a science because we often have new a science because we often have new breakthrough capabilities that are breakthrough capabilities that are breakthrough capabilities that are entirely zero to one. Deep research was entirely zero to one. Deep research was entirely zero to one. Deep research was one of those you know we couldn't have one of those you know we couldn't have one of those you know we couldn't have told you is there going to be demand for told you is there going to be demand for told you is there going to be demand for you know consumer demand for a research you know consumer demand for a research you know consumer demand for a research product but if you don't productize it product but if you don't productize it product but if you don't productize it uh um to find out uh um to find out uh um to find out >> um you you will never know. So you know >> um you you will never know. So you know >> um you you will never know. So you know this is where we have to be a little bit this is where we have to be a little bit this is where we have to be a little bit thoughtful on how we balance you know um thoughtful on how we balance you know um thoughtful on how we balance you know um things that are no-brainers that people things that are no-brainers that people things that are no-brainers that people are really going to love with things are really going to love with things are really going to love with things that are um brand new ideas. Then that are um brand new ideas. Then that are um brand new ideas. Then obviously on the research side, there's obviously on the research side, there's obviously on the research side, there's a reason that Mark has the job he has a reason that Mark has the job he has a reason that Mark has the job he has because a big part of um his his job is because a big part of um his his job is because a big part of um his his job is is figuring out what research to fund is figuring out what research to fund is figuring out what research to fund and um um you know, obviously GPU is a and um um you know, obviously GPU is a and um um you know, obviously GPU is a big part of that. So um very nuanced big part of that. So um very nuanced big part of that. So um very nuanced topic that we're continuously getting topic that we're continuously getting topic that we're continuously getting better at, but um for me the priority is better at, but um for me the priority is better at, but um for me the priority is always on our users. always on our users. always on our users. >> Yeah. The other takeaway that I had is >> Yeah. The other takeaway that I had is >> Yeah. The other takeaway that I had is you can you don't have line of sight to you can you don't have line of sight to you can you don't have line of sight to a time when you won't have that problem. a time when you won't have that problem. a time when you won't have that problem. >> It's it's been so fascinating. Um >> It's it's been so fascinating. Um >> It's it's been so fascinating. Um because because because you know we obviously have been you know we obviously have been you know we obviously have been incredibly lucky to uh encounter more incredibly lucky to uh encounter more incredibly lucky to uh encounter more and more users who want to use our and more users who want to use our and more users who want to use our technology but then the value that we're technology but then the value that we're technology but then the value that we're able to provide for each user is going able to provide for each user is going able to provide for each user is going up as well up as well up as well >> and um you know GP or GPU consumption >> and um you know GP or GPU consumption >> and um you know GP or GPU consumption you know it correlates pretty well with you know it correlates pretty well with you know it correlates pretty well with that value that value that value >> um and uh when you just look at token >> um and uh when you just look at token >> um and uh when you just look at token consumption per user um especially in consumption per user um especially in consumption per user um especially in the enterprise too which is you know um the enterprise too which is you know um the enterprise too which is you know um a a massive opportunity a a massive opportunity a a massive opportunity >> um you see um a lot of very GPU GPU >> um you see um a lot of very GPU GPU >> um you see um a lot of very GPU GPU hungry hungry workflows and um um yes hungry hungry workflows and um um yes hungry hungry workflows and um um yes demand keeps going up even as prices go demand keeps going up even as prices go demand keeps going up even as prices go down. down. down. >> This is a fascinating insight. People >> This is a fascinating insight. People >> This is a fascinating insight. People used to think that humans were you know used to think that humans were you know used to think that humans were you know you can't kind of make more humans well you can't kind of make more humans well you can't kind of make more humans well on a takes nine months and then 19 years on a takes nine months and then 19 years on a takes nine months and then 19 years but uh but you're saying well that's but uh but you're saying well that's but uh but you're saying well that's actually more more less finite resource actually more more less finite resource actually more more less finite resource than GPUs. Yeah, I mean on the human than GPUs. Yeah, I mean on the human than GPUs. Yeah, I mean on the human side um you can hire uh more humans and side um you can hire uh more humans and side um you can hire uh more humans and obviously we've been doing busy doing obviously we've been doing busy doing obviously we've been doing busy doing that and bring the best talent um across that and bring the best talent um across that and bring the best talent um across functions to OpenAI. Um in the world functions to OpenAI. Um in the world functions to OpenAI. Um in the world with agents you can also get more with agents you can also get more with agents you can also get more leverage per human um um you can make leverage per human um um you can make leverage per human um um you can make your humans very effective um at their your humans very effective um at their your humans very effective um at their job to do more job to do more job to do more >> but GPUs are zero sum um and if you >> but GPUs are zero sum um and if you >> but GPUs are zero sum um and if you don't have more GPUs you really have to don't have more GPUs you really have to don't have more GPUs you really have to figure out how do you make very very figure out how do you make very very figure out how do you make very very hard trades and hate making hard trades hard trades and hate making hard trades hard trades and hate making hard trades for users. for users. for users. >> Yeah. >> Yeah. >> Yeah. um hence the desire to um um have more um hence the desire to um um have more um hence the desire to um um have more GPUs. But uh it's it's useful to start GPUs. But uh it's it's useful to start GPUs. But uh it's it's useful to start with the most zero sum trade-off when with the most zero sum trade-off when with the most zero sum trade-off when you do your planning. So I think you do your planning. So I think you do your planning. So I think starting working backwards from GPUs um starting working backwards from GPUs um starting working backwards from GPUs um is usually pretty pretty good idea. is usually pretty pretty good idea. is usually pretty pretty good idea. >> Yeah. You know, one of the we have all >> Yeah. You know, one of the we have all >> Yeah. You know, one of the we have all these external data sources for charts these external data sources for charts these external data sources for charts of users and usage and of users and usage and of users and usage and >> act activity and retention all those >> act activity and retention all those >> act activity and retention all those things. What we don't have is tokens per things. What we don't have is tokens per things. What we don't have is tokens per user over time. user over time. user over time. >> And I bet that chart is like a sweet >> And I bet that chart is like a sweet >> And I bet that chart is like a sweet line going this way. I think internal is line going this way. I think internal is line going this way. I think internal is pretty good. Our internal uh employees pretty good. Our internal uh employees pretty good. Our internal uh employees is a pretty good indicator for what's is a pretty good indicator for what's is a pretty good indicator for what's about to happen. And um yes um the about to happen. And um yes um the about to happen. And um yes um the charts are are are mindboggling. charts are are are mindboggling. charts are are are mindboggling. >> Yeah. Yeah. Yeah. Fascinating. Uh okay, >> Yeah. Yeah. Yeah. Fascinating. Uh okay, >> Yeah. Yeah. Yeah. Fascinating. Uh okay, a couple of quick ones on the present a couple of quick ones on the present a couple of quick ones on the present before we go into the the landscape, before we go into the the landscape, before we go into the the landscape, which is, you know, shopping. Uh you which is, you know, shopping. Uh you which is, you know, shopping. Uh you know, we we just moved into a new house. know, we we just moved into a new house. know, we we just moved into a new house. We took some photos and we were hoping We took some photos and we were hoping We took some photos and we were hoping that all our furniture would magically that all our furniture would magically that all our furniture would magically appear that Chad Gibbly helped us paint. appear that Chad Gibbly helped us paint. appear that Chad Gibbly helped us paint. But But But >> you know a lot of a lot of uh recent >> you know a lot of a lot of uh recent >> you know a lot of a lot of uh recent updates on chat GPD shopping. Tell us updates on chat GPD shopping. Tell us updates on chat GPD shopping. Tell us tell us about it. What are you thinking? tell us about it. What are you thinking? tell us about it. What are you thinking? Yeah. On on shopping as Chad GP as a Yeah. On on shopping as Chad GP as a Yeah. On on shopping as Chad GP as a shopping assistant. Shopping is one of shopping assistant. Shopping is one of shopping assistant. Shopping is one of those use cases that exist organically those use cases that exist organically those use cases that exist organically in chat GBT today and they work. Um you in chat GBT today and they work. Um you in chat GBT today and they work. Um you can ask chat GPT about any purchase you can ask chat GPT about any purchase you can ask chat GPT about any purchase you might be planning and get pretty might be planning and get pretty might be planning and get pretty excellent advice. Uh but it's also one excellent advice. Uh but it's also one excellent advice. Uh but it's also one of those cases where the experience that of those cases where the experience that of those cases where the experience that exists in chat um today is it's not it's exists in chat um today is it's not it's exists in chat um today is it's not it's not the perfect experience that you not the perfect experience that you not the perfect experience that you would want um because shopping is very would want um because shopping is very would want um because shopping is very visual for example. So you're going to visual for example. So you're going to visual for example. So you're going to want to actually see products and images want to actually see products and images want to actually see products and images and be able to compare and contrast not and be able to compare and contrast not and be able to compare and contrast not just read you know walls of text. just read you know walls of text. just read you know walls of text. >> Um people care about the sources of you >> Um people care about the sources of you >> Um people care about the sources of you know um um um you know where can I learn know um um um you know where can I learn know um um um you know where can I learn more about you know a given product etc. more about you know a given product etc. more about you know a given product etc. Mhm. Mhm. Mhm. >> Um and um so there's a lot of work to do >> Um and um so there's a lot of work to do >> Um and um so there's a lot of work to do to make this discovery really really to make this discovery really really to make this discovery really really good and allowing people to use chat as good and allowing people to use chat as good and allowing people to use chat as a as a um as an assistant to find the a as a um as an assistant to find the a as a um as an assistant to find the right product to buy. right product to buy. right product to buy. >> Um and that's where our focus lies is >> Um and that's where our focus lies is >> Um and that's where our focus lies is making that really great and making that making that really great and making that making that really great and making that really great in a way that works for our really great in a way that works for our really great in a way that works for our retail partners as well. Um because as I retail partners as well. Um because as I retail partners as well. Um because as I mentioned earlier, there's huge appetite mentioned earlier, there's huge appetite mentioned earlier, there's huge appetite from the ecosystem to be part of the the from the ecosystem to be part of the the from the ecosystem to be part of the the ChachiBT journey. Um and um nailing the ChachiBT journey. Um and um nailing the ChachiBT journey. Um and um nailing the discovery piece is has has been um the discovery piece is has has been um the discovery piece is has has been um the most promising um focus here to date. most promising um focus here to date. most promising um focus here to date. >> Nick on chat GPT you must see a breath >> Nick on chat GPT you must see a breath >> Nick on chat GPT you must see a breath of information. You must see a breath of of information. You must see a breath of of information. You must see a breath of uh use cases that people are doing with uh use cases that people are doing with uh use cases that people are doing with Chad GPT and and tell us something about Chad GPT and and tell us something about Chad GPT and and tell us something about you know what what does the world you know what what does the world you know what what does the world underestimate about Chad GPT that you underestimate about Chad GPT that you underestimate about Chad GPT that you have maybe been surprised by or or or have maybe been surprised by or or or have maybe been surprised by or or or listener might be sub surprised by? listener might be sub surprised by? listener might be sub surprised by? there's been a real change in the way there's been a real change in the way there's been a real change in the way that people think of chat GPT that people think of chat GPT that people think of chat GPT >> um over the last year or so where um >> um over the last year or so where um >> um over the last year or so where um it's increasingly like a true thought it's increasingly like a true thought it's increasingly like a true thought partner to people partner to people partner to people >> um it's not just a thing that you know >> um it's not just a thing that you know >> um it's not just a thing that you know answers your question um but it's a answers your question um but it's a answers your question um but it's a thing that you can it's a sparring thing that you can it's a sparring thing that you can it's a sparring partner that you can actually think partner that you can actually think partner that you can actually think things through with things through with things through with >> and u that shows up in all kinds of >> and u that shows up in all kinds of >> and u that shows up in all kinds of domains ranging from life advice where domains ranging from life advice where domains ranging from life advice where you know if you got a you know if you got a you know if you got a >> relationship problem you can actually >> relationship problem you can actually >> relationship problem you can actually get a lot of value chat is helping you get a lot of value chat is helping you get a lot of value chat is helping you think through how to handle it and how think through how to handle it and how think through how to handle it and how to talk to you your partner about it. um to talk to you your partner about it. um to talk to you your partner about it. um all the way to a work setting where you all the way to a work setting where you all the way to a work setting where you know you're you're working on um um an know you're you're working on um um an know you're you're working on um um an analysis or you're like trying to figure analysis or you're like trying to figure analysis or you're like trying to figure out how to frame something or you're you out how to frame something or you're you out how to frame something or you're you know trying to build something and Chad know trying to build something and Chad know trying to build something and Chad GPT really shows up as um as a um second GPT really shows up as um as a um second GPT really shows up as um as a um second brain um of sorts and brain um of sorts and brain um of sorts and >> uh I think that's qualitatively >> uh I think that's qualitatively >> uh I think that's qualitatively different in terms of how the mental different in terms of how the mental different in terms of how the mental model it occupies with people model it occupies with people model it occupies with people >> and you see in the usage patterns and >> and you see in the usage patterns and >> and you see in the usage patterns and the use cases that exist and I think the the use cases that exist and I think the the use cases that exist and I think the more we nail things like you know more we nail things like you know more we nail things like you know proactivity which we talked about proactivity which we talked about proactivity which we talked about earlier in task etc. I think the more earlier in task etc. I think the more earlier in task etc. I think the more it's going to feel like a teammate in it's going to feel like a teammate in it's going to feel like a teammate in the workplace and like a super assistant the workplace and like a super assistant the workplace and like a super assistant at home at home at home >> and uh I think that's going to um >> and uh I think that's going to um >> and uh I think that's going to um meaningfully change the the use cases meaningfully change the the use cases meaningfully change the the use cases that people come for. that people come for. that people come for. >> Yeah. You know, I've been the the most >> Yeah. You know, I've been the the most >> Yeah. You know, I've been the the most highstakes thing I do with Chad GPT is highstakes thing I do with Chad GPT is highstakes thing I do with Chad GPT is uh we have a we have a new baby uh we have a we have a new baby uh we have a we have a new baby >> and when the baby's uh crying at 3 in >> and when the baby's uh crying at 3 in >> and when the baby's uh crying at 3 in the morning, the morning, the morning, >> Chad GPT, >> Chad GPT, >> Chad GPT, >> what you know what's what's going on? >> what you know what's what's going on? >> what you know what's what's going on? >> First of all, congrats. Second of all, >> First of all, congrats. Second of all, >> First of all, congrats. Second of all, I've heard this from all parents in my I've heard this from all parents in my I've heard this from all parents in my life. the chat has become indispensable life. the chat has become indispensable life. the chat has become indispensable indispensable indispensable indispensable >> as a thought partner and it makes sense >> as a thought partner and it makes sense >> as a thought partner and it makes sense right if you have a really specific right if you have a really specific right if you have a really specific scenario or you think it's a specific scenario or you think it's a specific scenario or you think it's a specific scenario to you chat really comes scenario to you chat really comes scenario to you chat really comes through and can um you know help you you through and can um you know help you you through and can um you know help you you know um um build confidence and I think know um um build confidence and I think know um um build confidence and I think that's such an empowering thing that's such an empowering thing that's such an empowering thing >> right like and I imagine new parents >> right like and I imagine new parents >> right like and I imagine new parents aren't always the most confident about aren't always the most confident about aren't always the most confident about what is the right thing to do and if what is the right thing to do and if what is the right thing to do and if chaty can make you um you know feel like chaty can make you um you know feel like chaty can make you um you know feel like you you you are you have agency and you you you are you have agency and you you you are you have agency and control and you know you know uh I think control and you know you know uh I think control and you know you know uh I think I think it's really valuable. I think it's really valuable. I think it's really valuable. >> Yeah, it's huge. Well, thank you for >> Yeah, it's huge. Well, thank you for >> Yeah, it's huge. Well, thank you for making Chad GPT. It's literally getting making Chad GPT. It's literally getting making Chad GPT. It's literally getting me an extra hour of sleep every day. me an extra hour of sleep every day. me an extra hour of sleep every day. >> It took a village. But that is a great >> It took a village. But that is a great >> It took a village. But that is a great metric. You know, that should be the metric. You know, that should be the metric. You know, that should be the northstar metric is like incremental northstar metric is like incremental northstar metric is like incremental hours of sleep. hours of sleep. hours of sleep. >> That's a great one. >> That's a great one. >> That's a great one. >> Incremental hours of sleep, incremental >> Incremental hours of sleep, incremental >> Incremental hours of sleep, incremental hours of joy. hours of joy. hours of joy. >> There you go. >> There you go. >> There you go. >> I mean, you joke, but like we talk about >> I mean, you joke, but like we talk about >> I mean, you joke, but like we talk about this a lot and um because spiritually this a lot and um because spiritually this a lot and um because spiritually that that that is pretty close to what that that that is pretty close to what that that that is pretty close to what we we we >> hope we can do, right? is is is help you >> hope we can do, right? is is is help you >> hope we can do, right? is is is help you re reach whatever you consider re reach whatever you consider re reach whatever you consider self-actualization. self-actualization. self-actualization. >> Yeah. >> Yeah. >> Yeah. >> Whether that that's sleep or joy or any >> Whether that that's sleep or joy or any >> Whether that that's sleep or joy or any other goal you might have. other goal you might have. other goal you might have. >> Yeah. Yeah. Yeah. Well, thank you for >> Yeah. Yeah. Yeah. Well, thank you for >> Yeah. Yeah. Yeah. Well, thank you for thank you to the village. thank you to the village. thank you to the village. >> We're going to switch gears and talk >> We're going to switch gears and talk >> We're going to switch gears and talk about the landscape. about the landscape. about the landscape. >> Sure. >> Sure. >> Sure. >> There's a lot going on on the field. Um >> There's a lot going on on the field. Um >> There's a lot going on on the field. Um you know, how would you frame Chad GPT's you know, how would you frame Chad GPT's you know, how would you frame Chad GPT's differentiation differentiation differentiation uh to to to people out there? Um there's uh to to to people out there? Um there's uh to to to people out there? Um there's a lot of different products out there. a lot of different products out there. a lot of different products out there. Look, it's the best time in history to Look, it's the best time in history to Look, it's the best time in history to be a consumer of technology. be a consumer of technology. be a consumer of technology. >> It is indeed. >> It is indeed. >> It is indeed. >> Um because uh you got options and the >> Um because uh you got options and the >> Um because uh you got options and the competition is intense. And I think competition is intense. And I think competition is intense. And I think that's beautiful and it's actually good that's beautiful and it's actually good that's beautiful and it's actually good for us too because for us too because for us too because >> if you were to premortem why a company >> if you were to premortem why a company >> if you were to premortem why a company like OpenAI does not achieve its like OpenAI does not achieve its like OpenAI does not achieve its mission, it's probably focus because of mission, it's probably focus because of mission, it's probably focus because of the sheer number of opportunities that the sheer number of opportunities that the sheer number of opportunities that become possible when you approach AGI, become possible when you approach AGI, become possible when you approach AGI, right? and having competition and and right? and having competition and and right? and having competition and and options out there, I think um it it options out there, I think um it it options out there, I think um it it forces us to focus on our customers too forces us to focus on our customers too forces us to focus on our customers too um and on the things that really matter um and on the things that really matter um and on the things that really matter which aren't always the most flashy which aren't always the most flashy which aren't always the most flashy things, right? Sometimes it's latency, things, right? Sometimes it's latency, things, right? Sometimes it's latency, reliability, um the quality of the user reliability, um the quality of the user reliability, um the quality of the user experience. experience. experience. >> So, uh I think it's a really good thing. >> So, uh I think it's a really good thing. >> So, uh I think it's a really good thing. >> Yeah. >> Yeah. >> Yeah. >> I think the biggest differentiation of >> I think the biggest differentiation of >> I think the biggest differentiation of Jet Beauty is the team behind it Jet Beauty is the team behind it Jet Beauty is the team behind it because, you know, we're not static, because, you know, we're not static, because, you know, we're not static, right? anything we build will get copied right? anything we build will get copied right? anything we build will get copied and you know sometimes in in in in ways and you know sometimes in in in in ways and you know sometimes in in in in ways that are high craft sometimes in ways that are high craft sometimes in ways that are high craft sometimes in ways that um you know are sort of um you know that um you know are sort of um you know that um you know are sort of um you know um check boxes and um it's really um check boxes and um it's really um check boxes and um it's really important to us that we evolve the important to us that we evolve the important to us that we evolve the category um and um build the super category um and um build the super category um and um build the super assistant that we've always imagined and assistant that we've always imagined and assistant that we've always imagined and I think the way the reason that I have I think the way the reason that I have I think the way the reason that I have confidence that that's possible at a confidence that that's possible at a confidence that that's possible at a speed that outpaces you know um um speed that outpaces you know um um speed that outpaces you know um um the the dynamic of being copied the the dynamic of being copied the the dynamic of being copied is that we have an amazing team. Um, and is that we have an amazing team. Um, and is that we have an amazing team. Um, and that we have an amazing team across that we have an amazing team across that we have an amazing team across research and engineering and design and research and engineering and design and research and engineering and design and all the different functions that it all the different functions that it all the different functions that it takes to make something amazing. And I takes to make something amazing. And I takes to make something amazing. And I think our unique ability has been to think our unique ability has been to think our unique ability has been to bring those functions together to build bring those functions together to build bring those functions together to build something that is sort of at the something that is sort of at the something that is sort of at the intersection of useful and possible intersection of useful and possible intersection of useful and possible >> right in that moment. >> right in that moment. >> right in that moment. >> Um, so you know, my best answer for you >> Um, so you know, my best answer for you >> Um, so you know, my best answer for you is we keep pushing forward and we hope is we keep pushing forward and we hope is we keep pushing forward and we hope to be um um expanding what people think to be um um expanding what people think to be um um expanding what people think of this product as. you know, last uh of this product as. you know, last uh of this product as. you know, last uh winter we had obviously uh you know, winter we had obviously uh you know, winter we had obviously uh you know, what was called Code Red. Google had a a what was called Code Red. Google had a a what was called Code Red. Google had a a great model. Uh there was a lot of, you great model. Uh there was a lot of, you great model. Uh there was a lot of, you know, talk about it. Mark Beni off know, talk about it. Mark Beni off know, talk about it. Mark Beni off switching very vocally to to to to switching very vocally to to to to switching very vocally to to to to Gemini and us delaying ads and health Gemini and us delaying ads and health Gemini and us delaying ads and health agents and shopping. Basically hit pause agents and shopping. Basically hit pause agents and shopping. Basically hit pause on everything, making tragedy better. on everything, making tragedy better. on everything, making tragedy better. >> Talk talk to us about that moment. Um >> Talk talk to us about that moment. Um >> Talk talk to us about that moment. Um both both about what led to that um and both both about what led to that um and both both about what led to that um and what was happening in that moment. what was happening in that moment. what was happening in that moment. >> Yeah. Um so first off code reds are a >> Yeah. Um so first off code reds are a >> Yeah. Um so first off code reds are a tool we use um to create focus and as tool we use um to create focus and as tool we use um to create focus and as you can imagine when you're in a place you can imagine when you're in a place you can imagine when you're in a place like open and this is what makes us like open and this is what makes us like open and this is what makes us special to um special to work here is is special to um special to work here is is special to um special to work here is is is is is >> there are so many different things >> there are so many different things >> there are so many different things >> going on it's a research lab we are >> going on it's a research lab we are >> going on it's a research lab we are pursuing many different ideas right pursuing many different ideas right pursuing many different ideas right >> and there's been these moments where u >> and there's been these moments where u >> and there's been these moments where u we've wanted the company to come we've wanted the company to come we've wanted the company to come together um um to solve a problem together um um to solve a problem together um um to solve a problem >> across boundaries you know no matter >> across boundaries you know no matter >> across boundaries you know no matter what your project might have And what your project might have And what your project might have And >> end of last year, we had one of those >> end of last year, we had one of those >> end of last year, we had one of those moments where we felt like we we need to moments where we felt like we we need to moments where we felt like we we need to show up for our users. We need to focus show up for our users. We need to focus show up for our users. We need to focus the things focus on the basics. Um like the things focus on the basics. Um like the things focus on the basics. Um like reliability, performance, um the way reliability, performance, um the way reliability, performance, um the way that talking to the model feels um that talking to the model feels um that talking to the model feels um making personalization really great. um making personalization really great. um making personalization really great. um all these elements that you know our our all these elements that you know our our all these elements that you know our our users care about and um I loved it um users care about and um I loved it um users care about and um I loved it um because it was really an opportunity to because it was really an opportunity to because it was really an opportunity to work with a bunch of folks who I don't work with a bunch of folks who I don't work with a bunch of folks who I don't normally get to work with on making the normally get to work with on making the normally get to work with on making the product great product great product great >> and we just exited the code red um >> and we just exited the code red um >> and we just exited the code red um >> which we knew we would um with the >> which we knew we would um with the >> which we knew we would um with the launch of 5.3 which you know is is a launch of 5.3 which you know is is a launch of 5.3 which you know is is a great model for the everyday user um great model for the everyday user um great model for the everyday user um it's great to talk to and um 5.4 four it's great to talk to and um 5.4 four it's great to talk to and um 5.4 four which is um workhorse if you're trying which is um workhorse if you're trying which is um workhorse if you're trying to do real knowledge work to do real knowledge work to do real knowledge work >> and um you know undoubtedly we're going >> and um you know undoubtedly we're going >> and um you know undoubtedly we're going to continue to use the tool um um of a to continue to use the tool um um of a to continue to use the tool um um of a code red whenever we want to create code red whenever we want to create code red whenever we want to create focus um but u I'm excited because I focus um but u I'm excited because I focus um but u I'm excited because I think um chat GBT um is is is in a great think um chat GBT um is is is in a great think um chat GBT um is is is in a great spot spot spot >> yeah so code red is over now >> yeah so code red is over now >> yeah so code red is over now >> that's correct >> that's correct >> that's correct >> it's not the new normal >> it's not the new normal >> it's not the new normal >> um it's not the new normal uh we want it >> um it's not the new normal uh we want it >> um it's not the new normal uh we want it to be a special thing but it is a tool I to be a special thing but it is a tool I to be a special thing but it is a tool I I suspect we will continue to use I suspect we will continue to use I suspect we will continue to use >> that's great that's great and Um maybe >> that's great that's great and Um maybe >> that's great that's great and Um maybe tangibly if you were to point at how did tangibly if you were to point at how did tangibly if you were to point at how did code red change chat GPT uh or maybe the code red change chat GPT uh or maybe the code red change chat GPT uh or maybe the ops or or how the team operates. ops or or how the team operates. ops or or how the team operates. >> The thing I try to get like you know >> The thing I try to get like you know >> The thing I try to get like you know foster with the team is focus. Um so we foster with the team is focus. Um so we foster with the team is focus. Um so we certainly more focused than we were six certainly more focused than we were six certainly more focused than we were six months ago months ago months ago >> on um you know the >> on um you know the >> on um you know the >> uh the things we really want to nail and >> uh the things we really want to nail and >> uh the things we really want to nail and some of those things are very behind the some of those things are very behind the some of those things are very behind the scenes like scenes like scenes like >> latency reliability >> latency reliability >> latency reliability >> those kind of things. >> those kind of things. >> those kind of things. >> Okay. And some of those things are like >> Okay. And some of those things are like >> Okay. And some of those things are like very considered efforts like you very considered efforts like you very considered efforts like you involving chatbt into the super involving chatbt into the super involving chatbt into the super assistant and um assistant and um assistant and um >> so focus is the main lasting artifact. >> so focus is the main lasting artifact. >> so focus is the main lasting artifact. Um and as you imagine um Um and as you imagine um Um and as you imagine um >> um it's hard to stay focused sometimes >> um it's hard to stay focused sometimes >> um it's hard to stay focused sometimes when there's so much going on in the when there's so much going on in the when there's so much going on in the space but um that's the hard job and you space but um that's the hard job and you space but um that's the hard job and you asked me about trade-offs earlier. asked me about trade-offs earlier. asked me about trade-offs earlier. >> Um um getting getting the team to focus >> Um um getting getting the team to focus >> Um um getting getting the team to focus on the things that really matter to on the things that really matter to on the things that really matter to users is certainly one of them. Um users is certainly one of them. Um users is certainly one of them. Um that's always worth it. that's always worth it. that's always worth it. >> Yeah. you know, in the back of my mind >> Yeah. you know, in the back of my mind >> Yeah. you know, in the back of my mind as I ask you that question as I ask you that question as I ask you that question >> is all the other founders that are that >> is all the other founders that are that >> is all the other founders that are that are in the arena right now. Uh and and are in the arena right now. Uh and and are in the arena right now. Uh and and just a reminder that hey, Code Red is a just a reminder that hey, Code Red is a just a reminder that hey, Code Red is a tool for for for you. Wartime at balance tool for for for you. Wartime at balance tool for for for you. Wartime at balance as we used to call it is is a tool. as we used to call it is is a tool. as we used to call it is is a tool. >> Yeah, I think you know every company >> Yeah, I think you know every company >> Yeah, I think you know every company does it differently um in terms of how does it differently um in terms of how does it differently um in terms of how you how you get stuff done. Um, but I you how you get stuff done. Um, but I you how you get stuff done. Um, but I think it it's really valuable to have think it it's really valuable to have think it it's really valuable to have terminology that um, you know, means terminology that um, you know, means terminology that um, you know, means something something something >> um, that, you know, signals to people >> um, that, you know, signals to people >> um, that, you know, signals to people it's okay to drop your other stuff and it's okay to drop your other stuff and it's okay to drop your other stuff and it's okay to, you know, focus on this it's okay to, you know, focus on this it's okay to, you know, focus on this thing together even if that wasn't your thing together even if that wasn't your thing together even if that wasn't your original job. original job. original job. >> Yeah. >> Yeah. >> Yeah. >> Um, so I think it worked really well um, >> Um, so I think it worked really well um, >> Um, so I think it worked really well um, at a place like OpenAI. Um, but I at a place like OpenAI. Um, but I at a place like OpenAI. Um, but I imagine startups would have an imagine startups would have an imagine startups would have an equivalent. equivalent. equivalent. >> Yeah. You know, one of the things that >> Yeah. You know, one of the things that >> Yeah. You know, one of the things that caught everybody's imagination uh, on caught everybody's imagination uh, on caught everybody's imagination uh, on our team was uh, what Peter was doing at our team was uh, what Peter was doing at our team was uh, what Peter was doing at OpenClaw. OpenClaw. OpenClaw. >> Mhm. >> Mhm. >> Mhm. >> Incredibly potent to put all the tools >> Incredibly potent to put all the tools >> Incredibly potent to put all the tools together. Obviously, Peter's a great together. Obviously, Peter's a great together. Obviously, Peter's a great builder. Congrats on on on bringing on builder. Congrats on on on bringing on builder. Congrats on on on bringing on Peter to the team. Um, tell us a little Peter to the team. Um, tell us a little Peter to the team. Um, tell us a little bit about what what what Peter's working bit about what what what Peter's working bit about what what what Peter's working on and when when might the uh uh the on and when when might the uh uh the on and when when might the uh uh the billions on Chad GPT have something to billions on Chad GPT have something to billions on Chad GPT have something to to to see there. to to see there. to to see there. >> Well, first of all, I'm very excited for >> Well, first of all, I'm very excited for >> Well, first of all, I'm very excited for for Peter to be here. Um, I uh um um was for Peter to be here. Um, I uh um um was for Peter to be here. Um, I uh um um was excited to have another German speaker excited to have another German speaker excited to have another German speaker in the house. He's he's Austrian. I'm in the house. He's he's Austrian. I'm in the house. He's he's Austrian. I'm German. So, we were we were um German. So, we were we were um German. So, we were we were um exchanging Guten Morgans. Um but the uh exchanging Guten Morgans. Um but the uh exchanging Guten Morgans. Um but the uh um yeah the the open claw is so um yeah the the open claw is so um yeah the the open claw is so inspiring because um it brought to life inspiring because um it brought to life inspiring because um it brought to life in in many ways um a vision that that in in many ways um a vision that that in in many ways um a vision that that that you we'd had um um in different that you we'd had um um in different that you we'd had um um in different forms know admittedly forms know admittedly forms know admittedly >> um around this kind of AI that is fully >> um around this kind of AI that is fully >> um around this kind of AI that is fully embodied that you know exists across embodied that you know exists across embodied that you know exists across different UIs that can do stuff for you different UIs that can do stuff for you different UIs that can do stuff for you that has state that has an interaction that has state that has an interaction that has state that has an interaction pattern that feels a little bit more pattern that feels a little bit more pattern that feels a little bit more like talking to a human, you know, like talking to a human, you know, like talking to a human, you know, because you um you open cloud allows you because you um you open cloud allows you because you um you open cloud allows you to you interact in a very very natural to you interact in a very very natural to you interact in a very very natural way where you can you send many texts way where you can you send many texts way where you can you send many texts back and forth and it's very curt and so back and forth and it's very curt and so back and forth and it's very curt and so there's a lot of elements of of of of there's a lot of elements of of of of there's a lot of elements of of of of OpenCloud that I think were very OpenCloud that I think were very OpenCloud that I think were very clarifying to to folks across the clarifying to to folks across the clarifying to to folks across the industry and um but the best you know I industry and um but the best you know I industry and um but the best you know I I'm I'm super excited to just like learn I'm I'm super excited to just like learn I'm I'm super excited to just like learn learn from Peter and bring in uh into learn from Peter and bring in uh into learn from Peter and bring in uh into the company and figure out what we can the company and figure out what we can the company and figure out what we can do together. So there there's there's a do together. So there there's there's a do together. So there there's there's a lot more to come. All right. So, now on lot more to come. All right. So, now on lot more to come. All right. So, now on to the most fun section. Rapid fire. to the most fun section. Rapid fire. to the most fun section. Rapid fire. >> All right. >> All right. >> All right. >> You ready? >> You ready? >> You ready? >> Sure. >> Sure. >> Sure. >> Well, we we'll start with my most my my >> Well, we we'll start with my most my my >> Well, we we'll start with my most my my my favorite game, which is long short. my favorite game, which is long short. my favorite game, which is long short. Uh, pick an idea, a startup, a business, Uh, pick an idea, a startup, a business, Uh, pick an idea, a startup, a business, a product that you love, you think you a product that you love, you think you a product that you love, you think you you're very bullish on. Yeah, I'm I'm if you're very bullish on. Yeah, I'm I'm if you're very bullish on. Yeah, I'm I'm if I were starting a company today, I I I'm I were starting a company today, I I I'm I were starting a company today, I I I'm really excited about these companies really excited about these companies really excited about these companies that are going into companies and that are going into companies and that are going into companies and getting extremely hands-on and doing getting extremely hands-on and doing getting extremely hands-on and doing effect effectively professional services effect effectively professional services effect effectively professional services >> um with AI because we've saturated all >> um with AI because we've saturated all >> um with AI because we've saturated all the emails the emails the emails >> um and you need to get proximate to the >> um and you need to get proximate to the >> um and you need to get proximate to the problems. So um that's it's it's those problems. So um that's it's it's those problems. So um that's it's it's those companies that that um I'm I'm paying companies that that um I'm I'm paying companies that that um I'm I'm paying attention to. attention to. attention to. >> Fascinating. So this is, you know, this >> Fascinating. So this is, you know, this >> Fascinating. So this is, you know, this is an example. This would be like, hey, is an example. This would be like, hey, is an example. This would be like, hey, you're going and either acquiring or or you're going and either acquiring or or you're going and either acquiring or or or going inside an operating firm that or going inside an operating firm that or going inside an operating firm that has scale and and and and and a humming has scale and and and and and a humming has scale and and and and and a humming engine. engine. engine. >> Exactly. >> Exactly. >> Exactly. >> And making that a more efficient engine. >> And making that a more efficient engine. >> And making that a more efficient engine. >> Yeah. Or or or just like, you know, >> Yeah. Or or or just like, you know, >> Yeah. Or or or just like, you know, you're doing contracts for for for for you're doing contracts for for for for you're doing contracts for for for for customers that have really hard problems customers that have really hard problems customers that have really hard problems and you're actually going in and and you're actually going in and and you're actually going in and committing to solving the problem. committing to solving the problem. committing to solving the problem. >> Um outcomes. >> Um outcomes. >> Um outcomes. >> Yeah. because like you know there >> Yeah. because like you know there >> Yeah. because like you know there there's a reason I think that we made so there's a reason I think that we made so there's a reason I think that we made so much progress on math and coding um but much progress on math and coding um but much progress on math and coding um but not on many other domains because those not on many other domains because those not on many other domains because those are domains we are approximate to we as are domains we are approximate to we as are domains we are approximate to we as people who work in labs and people who work in labs and people who work in labs and >> there's all kinds of other domains that >> there's all kinds of other domains that >> there's all kinds of other domains that we are not as proximate to and if you we are not as proximate to and if you we are not as proximate to and if you get proximate I think you can you know get proximate I think you can you know get proximate I think you can you know build something transformative and I build something transformative and I build something transformative and I think this is more important now think this is more important now think this is more important now >> um precisely because um you know the >> um precisely because um you know the >> um precisely because um you know the easy problems have been solved um the easy problems have been solved um the easy problems have been solved um the obvious problems have been solved by the obvious problems have been solved by the obvious problems have been solved by the models models models >> credit where credit is due I think not >> credit where credit is due I think not >> credit where credit is due I think not notebook spoke LM is awesome and notebook spoke LM is awesome and notebook spoke LM is awesome and differentiated and helps me learn new differentiated and helps me learn new differentiated and helps me learn new stuff. I think it's great. stuff. I think it's great. stuff. I think it's great. >> It's so good. >> It's so good. >> It's so good. >> Yeah, >> Yeah, >> Yeah, >> it's so good. >> it's so good. >> it's so good. >> I think this is the example of you can >> I think this is the example of you can >> I think this is the example of you can innovate and you can build something um innovate and you can build something um innovate and you can build something um totally different. It's awesome. totally different. It's awesome. totally different. It's awesome. >> Yeah. Yeah. Yeah. It's so good. >> Yeah. Yeah. Yeah. It's so good. >> Yeah. Yeah. Yeah. It's so good. Particularly for uh I found it for some Particularly for uh I found it for some Particularly for uh I found it for some more technical uh uh learning to be a more technical uh uh learning to be a more technical uh uh learning to be a very approachable way to to very approachable way to to very approachable way to to >> totally learn. And it's really cool. I >> totally learn. And it's really cool. I >> totally learn. And it's really cool. I feel like AI an underrated capability of feel like AI an underrated capability of feel like AI an underrated capability of AI is to just transform things into a AI is to just transform things into a AI is to just transform things into a different medium. different medium. different medium. >> Mhm. And I think that's so important for >> Mhm. And I think that's so important for >> Mhm. And I think that's so important for learning like we just la um um launched learning like we just la um um launched learning like we just la um um launched these like dynamic um math blocks which these like dynamic um math blocks which these like dynamic um math blocks which allow you to visually understand math allow you to visually understand math allow you to visually understand math inside chatb learning is obviously a big inside chatb learning is obviously a big inside chatb learning is obviously a big use case for us too use case for us too use case for us too >> and I think just being able to transform >> and I think just being able to transform >> and I think just being able to transform >> things from text to visual you know soon >> things from text to visual you know soon >> things from text to visual you know soon from you know visual to video and like from you know visual to video and like from you know visual to video and like all these different media is amazing all these different media is amazing all these different media is amazing because people have such different ways because people have such different ways because people have such different ways of processing information um and some of processing information um and some of processing information um and some people are like auditory learners some people are like auditory learners some people are like auditory learners some people are visual some people like people are visual some people like people are visual some people like reading uh so I think that's really reading uh so I think that's really reading uh so I think that's really magical Um and um a great great angle to magical Um and um a great great angle to magical Um and um a great great angle to take. take. take. >> Yeah. Amazing. Amazing. Amazing. Uh you >> Yeah. Amazing. Amazing. Amazing. Uh you >> Yeah. Amazing. Amazing. Amazing. Uh you know, one of the things I think about a know, one of the things I think about a know, one of the things I think about a lot is education and and and education lot is education and and and education lot is education and and and education for for for kids now in school. Um the for for for kids now in school. Um the for for for kids now in school. Um the world's changing so fast. world's changing so fast. world's changing so fast. >> I'm not sure our education system is >> I'm not sure our education system is >> I'm not sure our education system is changing that fast. changing that fast. changing that fast. >> Yeah. >> Yeah. >> Yeah. >> What advice would you have for for >> What advice would you have for for >> What advice would you have for for students who are in school now? Um you students who are in school now? Um you students who are in school now? Um you know, who might have to adapt faster know, who might have to adapt faster know, who might have to adapt faster than the system around them might adapt? than the system around them might adapt? than the system around them might adapt? It's a really good question and It's a really good question and It's a really good question and something that I've thought a lot about something that I've thought a lot about something that I've thought a lot about um myself um myself um myself and you know the I think the most and you know the I think the most and you know the I think the most important perma skill in this era is uh important perma skill in this era is uh important perma skill in this era is uh curiosity I think because >> if the machine can answer all your >> if the machine can answer all your questions you better have good questions you better have good questions you better have good questions. questions. questions. Um, and the only way to have good Um, and the only way to have good Um, and the only way to have good questions, I think, is to questions, I think, is to questions, I think, is to >> pursue the things you were actually >> pursue the things you were actually >> pursue the things you were actually excited about from an early age and excited about from an early age and excited about from an early age and throughout your entire life. throughout your entire life. throughout your entire life. >> Yeah. >> Yeah. >> Yeah. >> And, um, I reflect on this because the >> And, um, I reflect on this because the >> And, um, I reflect on this because the only reason I'm here and working on this only reason I'm here and working on this only reason I'm here and working on this stuff is because I thought it was neat stuff is because I thought it was neat stuff is because I thought it was neat when I got, you know, nerd sniped in when I got, you know, nerd sniped in when I got, you know, nerd sniped in >> um, in the interview process, right? And >> um, in the interview process, right? And >> um, in the interview process, right? And it was like, it was like, it was like, >> that's right. >> that's right. >> that's right. >> This is so cool. And and so no matter >> This is so cool. And and so no matter >> This is so cool. And and so no matter what you're doing, I think that's an what you're doing, I think that's an what you're doing, I think that's an important skill is to be curious and important skill is to be curious and important skill is to be curious and learn to stay curious. And I think I'm learn to stay curious. And I think I'm learn to stay curious. And I think I'm confident that um if you foster that confident that um if you foster that confident that um if you foster that skill um you will know how to adapt to skill um you will know how to adapt to skill um you will know how to adapt to you know an evolving you know an evolving you know an evolving >> landscape of tools and AIs and and jobs. >> landscape of tools and AIs and and jobs. >> landscape of tools and AIs and and jobs. Um so that would be my advice. Um so that would be my advice. Um so that would be my advice. >> Yeah, curiosity is has always been the >> Yeah, curiosity is has always been the >> Yeah, curiosity is has always been the poorest scale. Our friend uh Bill Gurley poorest scale. Our friend uh Bill Gurley poorest scale. Our friend uh Bill Gurley wrote about it in his book Running Down wrote about it in his book Running Down wrote about it in his book Running Down a Dream. Um but curiosity have to check a Dream. Um but curiosity have to check a Dream. Um but curiosity have to check that out. that out. that out. >> Yeah. Um, what what is a job that uh >> Yeah. Um, what what is a job that uh >> Yeah. Um, what what is a job that uh gets more valuable, not less, as uh AI gets more valuable, not less, as uh AI gets more valuable, not less, as uh AI gets better as as AGI arrives? gets better as as AGI arrives? gets better as as AGI arrives? >> Well, I think maybe the easy answer is >> Well, I think maybe the easy answer is >> Well, I think maybe the easy answer is being an entrepreneur. being an entrepreneur. being an entrepreneur. >> Um um because it's the best time to >> Um um because it's the best time to >> Um um because it's the best time to build ever build ever build ever >> in terms of like being able to >> in terms of like being able to >> in terms of like being able to self-actualize your self-actualize your self-actualize your >> Yeah. >> Yeah. >> Yeah. >> your idea. Yeah, >> your idea. Yeah, >> your idea. Yeah, >> but maybe maybe one that is maybe >> but maybe maybe one that is maybe >> but maybe maybe one that is maybe nonobvious is I think writing actually nonobvious is I think writing actually nonobvious is I think writing actually >> um is very important and it's not >> um is very important and it's not >> um is very important and it's not because the AI can't write you know AI because the AI can't write you know AI because the AI can't write you know AI will become amazing at writing just like will become amazing at writing just like will become amazing at writing just like any other domains but because I think any other domains but because I think any other domains but because I think the skill of writing the skill of writing the skill of writing >> forces you to be very clear >> forces you to be very clear >> forces you to be very clear >> of what you have to say >> of what you have to say >> of what you have to say >> and even though prompt engineering is >> and even though prompt engineering is >> and even though prompt engineering is obviously going to go away and has gone obviously going to go away and has gone obviously going to go away and has gone away to much extent away to much extent away to much extent >> the idea of expressing what you want >> the idea of expressing what you want >> the idea of expressing what you want >> to a machine >> to a machine >> to a machine >> requires you to be a pretty good writer >> requires you to be a pretty good writer >> requires you to be a pretty good writer and a very precise um um writer. So I I and a very precise um um writer. So I I and a very precise um um writer. So I I would say that that is a you know any would say that that is a you know any would say that that is a you know any profession that involves very clear profession that involves very clear profession that involves very clear writing and therefore thinking I think writing and therefore thinking I think writing and therefore thinking I think is is is um um well set up. Yeah, 100%. is is is um um well set up. Yeah, 100%. is is is um um well set up. Yeah, 100%. Honestly, I mean there this is the whole Honestly, I mean there this is the whole Honestly, I mean there this is the whole thing about slot, right? There's so much thing about slot, right? There's so much thing about slot, right? There's so much >> that's the other thing. I think there's >> that's the other thing. I think there's >> that's the other thing. I think there's going to be a permanent need for high going to be a permanent need for high going to be a permanent need for high quality, trusted, authoritative content quality, trusted, authoritative content quality, trusted, authoritative content and tools like CHAP can help you and tools like CHAP can help you and tools like CHAP can help you discover that content. discover that content. discover that content. >> Yeah. >> Yeah. >> Yeah. >> But I think the need for amazing um um >> But I think the need for amazing um um >> But I think the need for amazing um um content is is is also here to stay. content is is is also here to stay. content is is is also here to stay. >> Uh and final question, what has been >> Uh and final question, what has been >> Uh and final question, what has been your AGI feel the AGI moment? When did your AGI feel the AGI moment? When did your AGI feel the AGI moment? When did you feel it? I've had so many honestly. you feel it? I've had so many honestly. you feel it? I've had so many honestly. Um, and it's Um, and it's Um, and it's it's definitely not stopped. Um, it's definitely not stopped. Um, it's definitely not stopped. Um, a few weeks or so after I joined Open a few weeks or so after I joined Open a few weeks or so after I joined Open AI, GP24 had finished training AI, GP24 had finished training AI, GP24 had finished training >> and I remember trying it out and it >> and I remember trying it out and it >> and I remember trying it out and it actually it didn't impress me at all. actually it didn't impress me at all. actually it didn't impress me at all. Um, nor anyone else that week because it Um, nor anyone else that week because it Um, nor anyone else that week because it kind of didn't work. And it's because we kind of didn't work. And it's because we kind of didn't work. And it's because we hadn't figured out how to post train it. hadn't figured out how to post train it. hadn't figured out how to post train it. And uh I think seeing it go from And uh I think seeing it go from And uh I think seeing it go from kind of wait is this really a thing or kind of wait is this really a thing or kind of wait is this really a thing or was GPT3 kind of it to wow actually this was GPT3 kind of it to wow actually this was GPT3 kind of it to wow actually this is an entire step change with what felt is an entire step change with what felt is an entire step change with what felt to me at the time who didn't understand to me at the time who didn't understand to me at the time who didn't understand much about AI at all as like just some much about AI at all as like just some much about AI at all as like just some tweaks or some a little bit of final tweaks or some a little bit of final tweaks or some a little bit of final stretch work stretch work stretch work >> was profoundly humbling because you can >> was profoundly humbling because you can >> was profoundly humbling because you can realize that you might it might not look realize that you might it might not look realize that you might it might not look like we are close like we are close like we are close >> to really powerful useful AI But we >> to really powerful useful AI But we >> to really powerful useful AI But we probably are. Um, probably are. Um, probably are. Um, >> and then the moment that, you know, >> and then the moment that, you know, >> and then the moment that, you know, really, you know, there was two things really, you know, there was two things really, you know, there was two things that GBD4 did that that GBD4 did that that GBD4 did that felt like AGI to me. One is it could do felt like AGI to me. One is it could do felt like AGI to me. One is it could do poetry and I didn't think it was poetry and I didn't think it was poetry and I didn't think it was possible for AI model to do poetry. It possible for AI model to do poetry. It possible for AI model to do poetry. It just kind of just kind of just kind of >> fundamental philosophically, it just >> fundamental philosophically, it just >> fundamental philosophically, it just didn't feel like didn't feel like didn't feel like >> in scope >> in scope >> in scope >> and then the other one was it could >> and then the other one was it could >> and then the other one was it could produce code that actually worked and produce code that actually worked and produce code that actually worked and compiled. And then my next moment where compiled. And then my next moment where compiled. And then my next moment where I stared at the ceiling just in awe was I stared at the ceiling just in awe was I stared at the ceiling just in awe was when I realized GPD4 could just simulate when I realized GPD4 could just simulate when I realized GPD4 could just simulate an entire computer terminal um um like a an entire computer terminal um um like a an entire computer terminal um um like a full computer with commands etc. And I'm full computer with commands etc. And I'm full computer with commands etc. And I'm like, wait, how would this be imbued in like, wait, how would this be imbued in like, wait, how would this be imbued in a in a in a language model? And there's a in a in a language model? And there's a in a in a language model? And there's been so many moments since then, been so many moments since then, been so many moments since then, honestly. Like reasoning was a moment. honestly. Like reasoning was a moment. honestly. Like reasoning was a moment. One of the moments was when I think Mark One of the moments was when I think Mark One of the moments was when I think Mark and I were uh uh giving a demo of and I were uh uh giving a demo of and I were uh uh giving a demo of reasoning uh in front of the um whole reasoning uh in front of the um whole reasoning uh in front of the um whole company. Um and um this was a moment company. Um and um this was a moment company. Um and um this was a moment where we were still trying to kind of where we were still trying to kind of where we were still trying to kind of find use cases that were hard enough for find use cases that were hard enough for find use cases that were hard enough for the AI for the reasoning to, you know, the AI for the reasoning to, you know, the AI for the reasoning to, you know, make it make a difference. We're way make it make a difference. We're way make it make a difference. We're way past that point, we know. But at the past that point, we know. But at the past that point, we know. But at the time, you know, I think we were having time, you know, I think we were having time, you know, I think we were having to do a puzzle in front of everyone and to do a puzzle in front of everyone and to do a puzzle in front of everyone and um I think one of the moments that made um I think one of the moments that made um I think one of the moments that made me totally feel the AGI is like um we me totally feel the AGI is like um we me totally feel the AGI is like um we were in the middle of the demo and were in the middle of the demo and were in the middle of the demo and everyone started laughing and I was everyone started laughing and I was everyone started laughing and I was like, "Wait, what what is funny?" And like, "Wait, what what is funny?" And like, "Wait, what what is funny?" And then I stared at the screen because we then I stared at the screen because we then I stared at the screen because we were showing this chain of thought as it were showing this chain of thought as it were showing this chain of thought as it was streaming out of the model. Um and was streaming out of the model. Um and was streaming out of the model. Um and the model swore and said like, "Oh, damn the model swore and said like, "Oh, damn the model swore and said like, "Oh, damn it. May I have to adjust because I it. May I have to adjust because I it. May I have to adjust because I realized I had made a mistake in the realized I had made a mistake in the realized I had made a mistake in the puzzle." And uh the fact that they did puzzle." And uh the fact that they did puzzle." And uh the fact that they did that, but in particular the fact that it that, but in particular the fact that it that, but in particular the fact that it did that in a way that was entirely did that in a way that was entirely did that in a way that was entirely emergent from the you know RL process emergent from the you know RL process emergent from the you know RL process completely blew my mind um and you know completely blew my mind um and you know completely blew my mind um and you know made me you know um uh feel quite humble made me you know um uh feel quite humble made me you know um uh feel quite humble about what else these models might be about what else these models might be about what else these models might be able to do. So um that was one of those able to do. So um that was one of those able to do. So um that was one of those moments. moments. moments. >> Yeah. >> Yeah. >> Yeah. >> Uh and then most recently watching >> Uh and then most recently watching >> Uh and then most recently watching people use codecs like like watching people use codecs like like watching people use codecs like like watching people have people have people have >> walk around with their computer open uh >> walk around with their computer open uh >> walk around with their computer open uh because they don't want the task to end. because they don't want the task to end. because they don't want the task to end. Um yeah uh watching people who have Um yeah uh watching people who have Um yeah uh watching people who have never coded in their life make stuff and never coded in their life make stuff and never coded in their life make stuff and bring ideas uh to life that feel feels bring ideas uh to life that feel feels bring ideas uh to life that feel feels like an AGM. So honestly it just it's like an AGM. So honestly it just it's like an AGM. So honestly it just it's just accelerating for me and it doesn't just accelerating for me and it doesn't just accelerating for me and it doesn't wear off at all. Um and uh everyone has wear off at all. Um and uh everyone has wear off at all. Um and uh everyone has a different thing obviously but those a different thing obviously but those a different thing obviously but those are were some of mine. are were some of mine. are were some of mine. >> Yeah. You know it's uh 10 years ago >> Yeah. You know it's uh 10 years ago >> Yeah. You know it's uh 10 years ago there was a product called kite. I don't there was a product called kite. I don't there was a product called kite. I don't know if you remember it was for software know if you remember it was for software know if you remember it was for software engineers. It was like an AI coding engineers. It was like an AI coding engineers. It was like an AI coding product. Mhm. product. Mhm. product. Mhm. >> That's when I that's when I felt the >> That's when I that's when I felt the >> That's when I that's when I felt the hunger for for for for for personal AI hunger for for for for for personal AI hunger for for for for for personal AI and you know nothing happened for 10 and you know nothing happened for 10 and you know nothing happened for 10 years and then everything happened in years and then everything happened in years and then everything happened in the last 10 months. the last 10 months. the last 10 months. >> The timing thing is really hard because >> The timing thing is really hard because >> The timing thing is really hard because it's it's actually quite it's it's actually quite it's it's actually quite >> possible to predict where things will >> possible to predict where things will >> possible to predict where things will end up I think um in terms of the kind end up I think um in terms of the kind end up I think um in terms of the kind of product form factors you're going to of product form factors you're going to of product form factors you're going to have but to know when it happens it's have but to know when it happens it's have but to know when it happens it's really hard for me to make statements on really hard for me to make statements on really hard for me to make statements on anything between anything between anything between >> sort of eventually and in three months. >> sort of eventually and in three months. >> sort of eventually and in three months. >> Yeah. because of all the ambiguity >> Yeah. because of all the ambiguity >> Yeah. because of all the ambiguity around, you know, um um around, you know, um um around, you know, um um >> well, that's a tight enough window, you >> well, that's a tight enough window, you >> well, that's a tight enough window, you know, now and three months is a tight know, now and three months is a tight know, now and three months is a tight enough window. enough window. enough window. >> Three months is pretty pretty okay. Try >> Three months is pretty pretty okay. Try >> Three months is pretty pretty okay. Try to stick to the three-month plan more or to stick to the three-month plan more or to stick to the three-month plan more or less. Um um though, you know, my team less. Um um though, you know, my team less. Um um though, you know, my team would probably tell me we don't, but I I would probably tell me we don't, but I I would probably tell me we don't, but I I try. But yeah, anything in between three try. But yeah, anything in between three try. But yeah, anything in between three months and eventually is is is months and eventually is is is months and eventually is is is difficult. Um difficult. Um difficult. Um >> yeah. Yeah. Yeah. Well, thanks for doing >> yeah. Yeah. Yeah. Well, thanks for doing >> yeah. Yeah. Yeah. Well, thanks for doing it. You've got a lot going on. This was it. You've got a lot going on. This was it. You've got a lot going on. This was a total treat. We so excited to see all a total treat. We so excited to see all a total treat. We so excited to see all the great products you release for us. the great products you release for us. the great products you release for us. Um, Um, Um, we can do anything to be of help, let us we can do anything to be of help, let us we can do anything to be of help, let us know. know. know. >> Awesome. Thanks very much. Thanks for >> Awesome. Thanks very much. Thanks for >> Awesome. Thanks very much. Thanks for having me. having me. having me. >> Of course, man. This was fun. As a reminder to everybody, just our As a reminder to everybody, just our opinions, not investment advice.