EP 104: Sam Altman (CEO, OpenAI) talks GPT-4o and Predicts the Future of AI

On the day of the ChatGPT-4o announcement, Sam Altman sat down to share behind-the-scenes details of the launch and offer his predictions for the future of AI. Altman delves into OpenAI's vision, discusses the timeline for achieving AGI, and explores the societal impact of humanoid robots. He also expresses his excitement and concerns about AI personal assistants, highlights the biggest opportunities and risks in the AI landscape today, and much more. (00:00) Intro (00:50) The Personal Impact of Leading OpenAI (01:44) Unveiling Multimodal AI: A Leap in Technology (02:47) The Surprising Use Cases and Benefits of Multimodal AI (03:23) Behind the Scenes: Making Multimodal AI Possible (08:36) Envisioning the Future of AI in Communication and Creativity (10:21) The Business of AI: Monetization, Open Source, and Future Directions (16:42) AI's Role in Shaping Future Jobs and Experiences (20:29) Debunking AGI: A Continuous Journey Towards Advanced AI (24:04) Exploring the Pace of Scientific and Technological Progress (24:18) The Importance of Interpretability in AI (25:11) Navigating AI Ethics and Regulation (27:26) The Safety Paradigm in AI and Beyond (28:55) Personal Reflections and the Impact of AI on Society (29:11) The Future of AI: Fast Takeoff Scenarios and Societal Changes (30:59) Navigating Personal and Professional Challenges (40:21) The Role of AI in Creative and Personal Identity (43:09) Educational System Adaptations for the AI Era (44:30) Contemplating the Future with Advanced AI Executive Producer: Rashad Assir Producer: Leah Clapper Mixing and editing: Justin Hrabovsky Check out Unsupervised Learning, Redpoint's AI Podcast: https://www.youtube.com/@UCUl-s_Vp-Kkk_XVyDylNwLA 🎥 Subscribe on YouTube: https://www.youtube.com/channel/UCugS0jD5IAdoqzjaNYzns7w?sub_confirmation=1 Follow on Socials 📸 Instagram - https://www.instagram.com/theloganbartlettshow 📱 X - https://twitter.com/loganbartshow 🎬 Clips on TikTok - https://www.tiktok.com/@theloganbartlettshow About the Show Logan Bartlett is a Software Investor at Redpoint Ventures - a Silicon Valley-based VC with $6B AUM and investments in Snowflake, DraftKings, Twilio, and Netflix. In each episode of The Logan Bartlett Show, we sit down with the people behind today’s most important startups and extract the tactics, lessons, and frameworks they’ve learned the hard way. Conversations span hiring to GTM, product, growth, fundraising and everything in between - collectively forming the ultimate playbook to make you a better CEO, investor or board member. Tap follow and enable notifications to stay ahead of the game.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:05Logan Bartlett?

  Welcome to Logan Bartlett Show. On this episode, what you're going to hear is a conversation I had with co-founder and CEO of OpenAI, Sam Altman. Now, if this is your first time listening to the Logan Bartlett Show, this is a podcast where I discuss with leaders in technology, as well as investors, some of the lessons that they've learned in operating or investing in businesses, mostly in the technology field. And this discussion with Sam is a little bit different in which I pushed on a number of things related to artificial intelligence, as well as where OpenAI is headed, given how topical it is in the news, and Sam's perspective on such a leading frontier that is artificial intelligence. You'll hear that discussion with Sam here now.

• 0:44Speaker 01

  Thanks for doing this.

• 0:44Logan Bartlett?

  Yeah, of course. All right, I want to start off easy. What's the weirdest thing that's changed in your life in the last four or five years running OpenAI? Like, what's the most unusual shift that's happened?

• 0:58Speaker 01

  Um, I mean, quite a lot of things, but the sort of inability to just be like mostly anonymous in public is very, very strange. I think if I had thought about that at the time, I would have said, okay, this is like a weirder, this will be a weirder thing than it sounds like. But I didn't really think about it. It's like a much weirder thing. It's like a strangely isolating way to live.

• 1:20Logan Bartlett?

  You believed in AI and the power of the business. So did you just not think through the derivative implications of running something that was that powerful?

• 1:27Speaker 01

  I didn't think, there were all of these other things. I'm like, oh, AI is going to be like really important. OpenAI is going to be a really important company. I didn't think I would like not be able to like go out to dinner in my, in my own city.

• 1:39Logan Bartlett?

  That's weird.

• 1:39Speaker 01

  That's weird.

• 1:40Logan Bartlett?

  You made an announcement earlier, did I?

• 1:42Speaker 01

  We did.

• 1:42Logan Bartlett?

  Multimodal 4O?

• 1:45Speaker 01

  Yeah.

• 1:45Logan Bartlett?

  That's the Omega sign, right?

• 1:47Speaker 01

  Yeah, oh, just the, like, oh, like Omni.

• 1:49Logan Bartlett?

  Yeah, Omni, okay, sorry. It works across text, voice, vision. Can you speak to why this is important?

• 1:57Speaker 01

  Um, because I think it's like an incredible way to use a computer. This fact, this, I, we've had like voice.

• 2:06Speaker 01

  The idea of like voice controlled computers for a long time. You know, we had Siri and we had things before that. They've never to me felt natural to use. And this one, many different reasons, what it can do, the speed, adding in other modalities, the inflection, the naturalness, the fact that you can do things like say, hey, talk faster or talk in this other voice and that it's the the fluidity, the pliability, whatever you want to call it. I just can't believe how much I love using it.

• 2:41Logan Bartlett?

  Yeah, Spike Johnson would be proud.

• 2:42Speaker 01

  It's.

• 2:43Logan Bartlett?

  Are there use cases that you've gravitated to?

• 2:47Speaker 01

  Well, I've only had it for like a week or something. But one surprising one is putting my phone on the table while I'm like really in the zone of working. And then without having to like change windows or change what I'm doing, using it as like another channel. So I'm like working on something I would normally like stop what I'm doing, switch to another tab, Google something, click around or whatever. But while I'm like still doing it, to just ask and get like an instant response without changing from what I was looking at on my computer, that's been a surprisingly cool thing.

• 3:19Logan Bartlett?

  What actually made this possible? Was it an architectural shift or more compute?

• 3:25Speaker 01

  I mean, it was like all of the things that we've learned over the last several years, we've been working on audio models, we've been working on visual models, we've been working on tying them together, we've been working on more efficient ways to train our models. It's not like, okay, we unlocked this one crazy new thing all at once, but it was putting a lot of pieces together.

• 3:46Logan Bartlett?

  Do you think you need to develop like an on-device model to decrease latency to the point for usability?

• 3:53Speaker 01

  Uh, for video, maybe it would be hard to deal with network latency at some point. Like, like the, the, a thing that I've always thought would be super amazing is to put on someday a pair of AR goggles or whatever and just like speak the world in real time and watch things change. And that might get harder over network latency, but for this.

• 4:15Speaker 01

  You know, two, three hundred milliseconds of latency feels super like feels faster than a human responding to me in many, many cases.

• 4:23Logan Bartlett?

  Is is video in this case images?

• 4:26Speaker 01

  Oh, sorry. I meant video if you wanted like generated video, not not not input video.

• 4:31Logan Bartlett?

  Got it. Got it. So so currently it's working with actual video as is.

• 4:35Speaker 01

  Well, like frame by frame of.

• 4:36Logan Bartlett?

  Frame by frame. So it's okay. Got it. You're related recently to Chat GPT, maybe not being their the next big launch, not being GPT five. It feels like there's been sort of an iterative approach to model development that you guys have have taken. Is it fair to say that's how we should think about it going forward? That it's not going to be some big launch? Here's Chat GPT five, but instead.

• 5:02Speaker 01

  We honestly don't know yet. I I think that definitely one thing I've learned is that AI and surprise do not go well together. And although, you know, the traditional way a tech company launches products, we should probably do something different. Now, we could still call it GPT five and launch it in a different way, or we could call it something different. But I don't think we've figured out how to do the naming or branding for these things yet. Like, it made sense to me from like GPT one to GPT four at the launch. Now, obviously, GPT four has continued to get much better. We also have this idea that there's going to be like, you know, maybe there's like one underlying kind of like

• 5:44Speaker 01

  virtual brain and it can like think harder in some cases than others, or maybe it's different models, but maybe these are just in care if they're different or not. So I don't think we know the answer to how we're gonna like product market all of this yet.

• 5:57Logan Bartlett?

  Does that mean maybe that the the the needs of the compute to make incremental progress on models might be less than what it's been historically?

• 6:07Speaker 01

  I sort of think we'll always use as much compute as we get. Now, we are finding incredible efficiency gains, and that's really important. One of the, you know, the cool, the cool thing that we launched today is obviously the voice mode. But maybe the most important thing is we were able to make this so. Efficient that we're able to serve it to free users. Like best model in the world by a good amount of people look at that little thing. Served to like anybody who wants to download chat GPT for free. And it was a remarkable efficiency gain over GPT four and GPT four turbo. And we have a lot more to gain there.

• 6:41Logan Bartlett?

  I've heard you say that chat GPT didn't actually change the world in and of itself, but maybe just changed people's expectations for the world.

• 6:50Speaker 01

  Yeah. Like, I don't think you can find much evidence in the economic measurement of your choice that chat GPT really inflected productivity or whatever.

• 7:00Logan Bartlett?

  Maybe customer support.

• 7:01Speaker 01

  Maybe some, maybe some areas.

• 7:02Logan Bartlett?

  Summarization.

• 7:02Speaker 01

  Like if you look at like global GDP, you know, can you detect when chat GPT launched? Probably not.

• 7:07Logan Bartlett?

  Is there, is there a point that you think will be able to determine a GDP of function?

• 7:13Speaker 01

  Yeah, I don't know if you'll ever be able to say like this was the one model that did it. But I think if we look at the graph, a couple of decades in the future, it'll be like, hmm, something changed.

• 7:22Logan Bartlett?

  Yeah. Are there applications or areas that you think are most promising in the next 12 months?

• 7:28Speaker 01

  I'm sure I'm biased just because of where, what we do here, but coding, I think is a, is a really big one.

• 7:33Logan Bartlett?

  Kind of related to the bitter lesson. You spent some time recently talking about the difference between deeply specialized models, uh, trained on specific data for specific purposes versus generalized models that are capable of true reasoning.

• 7:45Speaker 01

  I would bet that it's the generalized model that's going to matter.

• 7:48Logan Bartlett?

  And what is the most important thing there as you think about like someone that's focused singularly on a so data set and all the integrations associated with something very narrow?

• 8:01Speaker 01

  If the model can do generalized reasoning, if it can like figure out new things, then if it needs to figure out how to work with a new kind of data, you can feed it in and it can do it. Um, but it doesn't go the other way around, like a bunch of specialized models that. I don't think a bunch of specialized models put together can't figure out the generalized reasoning.

• 8:20Logan Bartlett?

  So the implications for that of coding specific models probably be?

• 8:25Speaker 01

  I think a better way of saying this is I think the most important thing to figure out is the true reasoning capability. And then we can use it for all sorts of things.

• 8:32Logan Bartlett?

  What do you think the principal means of communication between humans and AI is in two years?

• 8:38Speaker 01

  Natural language seems pretty good. I I'm interested in this general idea that we should design a future that humans and AIs can sort of use together. Using the same way. So I'm like more excited about humanoid robots than I am for other forms of robots. Because I think the world is like very much not designed for humans. And I don't want that to get reconfigured for some more efficient kind of thing. I like the idea that AIs that we talk to AI in language that's like very well human optimized. And that they even like talk to each other that way, maybe, I don't know. But I think this is I think this is generally an interesting direction to push.

• 9:18Logan Bartlett?

  You said recently something to the effect of the models might ultimately get commoditized over time. But the most important thing would likely be the personalization of the models to each individual first.

• 9:30Speaker 01

  Yeah.

• 9:30Logan Bartlett?

  Do I have that right?

• 9:32Speaker 01

  I'm not certain on this, but I think it's like a thing that I would that would seem like reasonable to me. Yeah.

• 9:38Logan Bartlett?

  Then beyond personalization, do you think it's just normal business UI and ease of use that ultimately wins for end users?

• 9:46Speaker 01

  Those are those will for sure be important. They they always are. You know, I can imagine other things where there's like a sort of marketplace or a network effect of some sort that matters. Where it's, you know, we want our agents to communicate. There's the different companies in an app store. But I I sort of think that the rules of business kind of generally apply. And whenever you have a new technology, you're tempted to say they don't. But that's always like fake news and not always usually fake news. And all of the traditional ways that you create enduring value will will still matter here.

• 10:17Logan Bartlett?

  When you see open source models like catch up to benchmarks and all of that.

• 10:25Logan Bartlett?

  What's your reaction to it? Is that?

• 10:28Speaker 01

  I think it's great.

• 10:29Logan Bartlett?

  Yeah.

• 10:29Speaker 01

  I mean, I think that there are.

• 10:33Speaker 01

  You know, like many other kinds of technology, there will be a place for open source. There'll be a place for like hosted models and that's fine. Hmm. It's good.

• 10:42Logan Bartlett?

  I'm not going to ask about any specifics related to this, but there have been press

• 10:46Speaker 01

  I might answer.

• 10:47Logan Bartlett?

  There's been press reports related to looking to raise major amounts of money. Wall Street Journal, I think, was a credible one to galvanize investment in fabs. Semi-industry, TSMC and Nvidia have been ramping pretty aggressively to meet expectations of the need for AI infrastructure. You recently said that you think the world needs more AI infrastructure and then you said a lot more AI infrastructure.

• 11:13Speaker 01

  I do think.

• 11:14Logan Bartlett?

  Is there something you're seeing on the demand side that would require way more AI infrastructure than what we're currently getting out of TSMC and Nvidia?

• 11:25Speaker 01

  So first of all, I'm confident that we will figure out how to bring costs to deliver current systems way, way down. I'm also confident that as we do that, demand will increase by a huge amount. And third, I'm confident that by building bigger and better systems, there will be even even more demand. We should all hope for a world where intelligence is too cheap to meter. Hmm. It's just wildly abundant. People use it for all sorts of things and you don't even think about whether like, oh, you know, do I want this? Do I, you know, do I want this like reading all my emails and responding to them for me? Or do I want this like curing cancer? Of course you pick curing cancer. But the answer is like, you'd love for it to do both things. And I just want to make sure we have enough for everybody to have that.

• 12:08Logan Bartlett?

  I don't need you to comment on your own personal efforts here, although again, if you want to, please let me know. But humane and limitless and some of these like different physical device assistance. What do you think those have gotten wrong? Or where do you think the the adoption maybe hasn't met user desires just yet?

• 12:29Speaker 01

  I think it's just early. I have been an early adopter of many types of computing.

• 12:36Speaker 01

  I had and very much loved the compact TC1000, like when I was a freshman in college.

• 12:44Speaker 01

  I thought it was just like so cool and like that was a long way from the iPad. A long, long way from the iPad, but you know, it was directionally right. Then I got a trio. I was like the, I was very not cool college kid. I had like a old Palm Trio. And when it was like a, that was not a thing that kids had. And that was a long way from the iPhone, but we got there eventually. And you know, these things feel like a very promising direction that's going to take some iteration.

• 13:13Logan Bartlett?

  You mentioned recently that a number of businesses that are building on top of G P T four will be steamrolled, I think was your term, by future G P T. I guess, can you elaborate on that point? And second, like, what are the characteristics of A I first businesses that you think will survive? G P T's advancement?

• 13:32Speaker 01

  The only framework that I have found that works for this is you, you can either build a business that bets against the next model being really good, or a model that bets on that happening and benefits from it happening. So if you're doing a lot of work to make one use case really work that was just beyond the capability of G P T four, G P T four, oh no. And then you get it to work, but then G P T five comes out and it does that and everything else really well. You're kind of like sad about the effort you put into that one thing to get it to barely work. But if you had something that just like kind of worked okay across the board and people were finding things to use for, but you didn't put in like tons of work to, to make this one thing kind of possible.

• 14:16Speaker 01

  And then G P T five, or whatever we call it, comes along and it's just way better, everything you like, you got the rising tide lifted all your boats. Effect, you know, what I would suggest is like, you're not building an A I business. In most cases, you're building a business. And A I is a technology that you use. In the early days of the App Store, I think there were a lot of things that like filled in some very obvious crack. And then eventually Apple fixed that and there wasn't, you know, you didn't keep needing like a flashlight app that from the App Store, which is like part of the O S and that was like going to happen. And then there were, I think, things like Uber that were enabled by having smartphones, but really built a very defensible, long-term business.

• 15:00Speaker 01

  And I think you just want to go for that latter category.

• 15:03Logan Bartlett?

  I can come up with a lot of incumbent businesses that leverage you all that fit that. Framework in some ways. Are there any like novel types of concepts that you sort of think is in that example, the Uber? And it doesn't need to be, it could be a real company if you think of one, or even if it's a toy or just something that's interesting that you think is like enabled in that way?

• 15:28Speaker 01

  Um, I would actually bet on the new companies for like many of these cases. A very common example people use is trying to build like the AI doctor, like the AI diagnostician. And people talk about, oh, I don't want to do a startup here because Mayo Clinic or take your pick is going to do it. And I would actually bet it's a new company that does something like that.

• 15:49Logan Bartlett?

  Hmm. Do you have any advice for CEOs beyond that who are want to be proactive about preparing for these types of disruptions?

• 15:59Speaker 01

  I would say like bet that intelligence as a service gets better and cheaper every year, and it is necessary, but not sufficient for you to win. So the big companies that take years to implement this, you can like beat them, but every other startup is, that's, you know, paying attention is going to do this too. And so you still have to figure out like, what's the long-term defensibility of my business? Now, the playing field is way more open than it's been in a long time. There's incredible new things to do, but you don't get a pass on like the hard work of building enduring value, even though you can now do it in more ways.

• 16:38Logan Bartlett?

  Hmm. Is there a job title or a type of job responsibility that you could envision existing or being mainstream in five years because of AI that like is maybe niche or non-existent today?

• 16:52Speaker 01

  That's a great question, and I don't think I've ever gotten it before. It's people always ask like, what job is going to go away? The new one is a more interesting question. Let me think for a second. Um, I mean, there's like a lot of things that I could talk about that I think are sort of less interesting or less huge. Uh, what I'm trying to do is like come up the areas of like, what will 100 million people do or 50 million people do? Um, the broad category of new kinds of art, entertainment, sort of more like human-to-human connection, I don't know what that job title is going to be, but I think. And I don't know if this like we get there in five years, but I think there's going to be a premium on like

• 17:36Speaker 01

  human in-person like fantastic experiences. I don't know what we'll call that, but I could see that being like a very huge category of something new that we do.

• 17:45Logan Bartlett?

  The most recent public tender of OpenAI was ninety billion or something in about there. Are there one or two things that you sort of look at as milestones? That will get OpenAI to be a trillion dollar company? Short of AGI.

• 18:01Speaker 01

  Uh, I think if we can just keep improving our technology at the rate we've been doing it and figuring out how to continue to make good products with it and revenue keeps growing like it's growing. I don't know about specific numbers, but I think we'll be fine.

• 18:16Logan Bartlett?

  Is the the business monetization model today, the one that you think creates the one trillion dollar equity value?

• 18:24Speaker 01

  I mean, the chat GPT subscription model like really works well for us. Like surprisingly, I wouldn't have bet on that. I wouldn't have been confident it's going to do as well as it has, but it's been good.

• 18:34Logan Bartlett?

  Do you do you think post AGI, whatever that term actually means? We'll be able to, I don't know, ask AGI what the monetization model is that might be different?

• 18:46Speaker 01

  Yeah, yeah, should be able to.

• 18:49Logan Bartlett?

  I think we maybe saw in November, not to rehash, uh, that that the existing OpenAI structure left some things to be desired, which I don't think we need to rehash in total. You talked about it enough, I think, but um, you spoke into making changes along the way. What do you think the appropriate structure is going forward?

• 19:11Speaker 01

  Um, I think we're close to being ready to talk about that. Uh, we're like, we've been hard at work on all sorts of conversations and brainstorming there.

• 19:23Speaker 01

  I think like hopefully in a like this year, I think we'll be right on this calendar year. You tell me first.

• 19:30Logan Bartlett?

  Listen, when Larry and Brett Taylor got Battlefield promoted to board directors, I was waiting for, you know, my call never came through. But I, one of the interesting things I think about preconceptions around AI, to your point on the monetization model and all that is, I think we've all, I've heard you speak about it. Manual work, obviously first, followed by, you know, white collar, followed by creative. Obviously, it's proven to be kind of the opposite in some ways. Are there other things that are counterintuitive that you've looked at being like, well, I would have presupposed it to be this way, but it's actually proven to be the exact opposite.

• 20:05Speaker 01

  That's definitely the mega surprise to me, the one that you mentioned. There's other, like, I don't think I would have expected it to be so good at legal work so early, just because I think of that as like a very precise, complex thing. But, but no, definitely the big one is the the observation of like, physical labor, cognitive labor, creative labor.

• 20:25Logan Bartlett?

  For those that haven't heard, you make the point about AGI and why you dislike the term. Can you elaborate on on that point?

• 20:33Speaker 01

  Because I know, I don't, I no longer think it's like a moment in time. I obviously have so many naive conceptions when you start any company. And particularly in a field that's like moving around as much as this one is. But my naive conception when we started is that we would like get to a moment where we didn't have AGI and then we did. And it would be a real discontinuity. And I still think there's some chance of a real discontinuity. But on the whole, I think it's going to look much more like a continuous exponential curve, where what matters is the pace of progress year over year over year.

• 21:14Speaker 01

  And you and I will probably not agree on the month or even the year that we're like, okay, now that's AGI. We can come up with other tests that we will agree with, but even that is harder than it sounds. And, you know, GPT-4 is definitely not over a threshold that I think almost anyone would call an AGI. And I don't expect our next big model to be either. But I can imagine that we're like only maybe one or two or some small number of ideas away and a little bit more scale from something where we're like, hmm, this is now kind of different. And I think it's important to. Stay vigilant about that.

• 21:49Logan Bartlett?

  Is there a more modern Turing test? We can call it the Bartlett test where that you think like, hey, when it crosses this threshold?

• 21:59Speaker 01

  I think when it's capable of doing better research than like all of OpenAI put together, even one OpenAI researcher, that is like a somehow very important thing that feels like it could or maybe even should be a discontinuity.

• 22:13Logan Bartlett?

  Does that feel close?

• 22:17Speaker 01

  Probably not, but I wouldn't, I wouldn't rule it out.

• 22:19Logan Bartlett?

  What do you think the biggest obstacles that you see to reaching AGI? It sounds like you think maybe the scaling laws have runway currently and holding for the next couple of years?

• 22:30Speaker 01

  Yeah, I think the biggest obstacles are new research. And, you know, one of the things I've had to learn shifting from like internet software to AI is research does not kind of work on the same schedule as engineering, which usually means it takes much longer, it doesn't work, but sometimes means it works tremendously faster than anyone could have predicted.

• 22:51Logan Bartlett?

  What is that? Can you elaborate on that point that it's like not as linear in progress?

• 22:57Speaker 01

  I think the best way to elaborate on that is like historical examples. I'm going to get the numbers wrong here, but.

• 23:03Logan Bartlett?

  I'm sure no one will try to correct you.

• 23:04Speaker 01

  Someone will.

• 23:05Logan Bartlett?

  Yeah.

• 23:06Speaker 01

  I think the neutron was first theorized in the early 1900s. It was maybe first detected in the 10s or 20s. And the work on what became the atomic bomb started in the 30s and happened in the 40s. Like from, from not really having no idea that such like, that there was even the idea of a thing like a neutron to being able to like make an atomic bomb and just like break all of our intuitions about physics.

• 23:43Speaker 01

  That's like wildly quick. There are other examples that are sort of less pure science. Like there's the famous quote about the Wright brothers. Again, I'm going to get the numbers wrong here, but let's say it was like 1906. They said they thought flight was 50 years away and 1908 they did it, whatever, something like that. And then many, many other examples throughout the history of science and engineering. There's also plenty of things that we theorize that never happen or take decades or centuries longer than we thought, but sometimes it does go really fast.

• 24:13Logan Bartlett?

  Interpretability, where are we on this path and how important is that long term for AI?

• 24:22Speaker 01

  There's different kinds of interpretabilities. There's the like, do I understand like every, what's happening at like every mechanical layer through the network? And then there's, can I like look at the output and say there's a logical flaw here or whatever? I am excited about the work going on at OpenAI and elsewhere in this direction. And I think that interpretability as a broader field seems like promising and exciting.

• 24:47Logan Bartlett?

  I won't pin you down. I assume you'll have a nice announcement when you're ready to say something. But do you think that that is going to be a requisite to mainstream AI adoption? Maybe within enterprises or something?

• 25:03Speaker 01

  GPT-4 is like quite widely adopted at this point.

• 25:06Logan Bartlett?

  Yeah, that's true. There's maybe a few things that I think you get asked questions about or maybe accused is too strong of a term, but that people are suspicious about. One of which is I think there's this needle threading that exists between being excited about AGI, but also feels like you have a personal kind of apprehension about you, Sam, OpenAI generally being the ones to harness it and unilaterally make decisions, which has led to some, you know, some body, some governmental structure where there's elected leaders instead of you making these decisions.

• 25:50Speaker 01

  Yeah, I think for like, I think it'd be a mistake to go regulate, heavily regulate like current capability models, but when the models, which I believe they will, pose significant catastrophic risk to the world, I think having some sort of oversight is probably a good thing. Now, there is some needle threading about where you set those thresholds and how you test for it. And it would be a real shame to sort of stop the tremendous upsides of this technology and letting people that want to go train models in their basement be able to do that. That'd be really, really bad. But, you know, if we have international rules for nuclear weapons. It's a good thing.

• 26:31Logan Bartlett?

  The regulatory capture group, which I'm sure we can think of which VCs fall into that bucket of accusatory around this regulation. What do you think they don't see about the potential risks inherent in AI?

• 26:50Speaker 01

  Well, I think they just don't get, I don't think they like on the whole seriously wrestled with AGI. These were also people who like, some of the loudest voices about AI regulatory capture were, you know, totally decrying it as a possibility not that long ago, not all. But I do have empathy for where they're coming from, which is like, regulation has not been really bad for technology. Like, look what happened to the European technology industry. Like, I get it. I really do. And yet, I think that there is a threshold that we are heading towards, above which we may all feel a little bit different.

• 27:22Logan Bartlett?

  Do you think open source models themselves present inherent danger in some ways?

• 27:30Speaker 01

  No current one does. But I could imagine one that could.

• 27:34Logan Bartlett?

  I've heard you say that safety is kind of a false framing in some ways because it's more of a discussion about what we explicitly accept, like airlines.

• 27:44Speaker 01

  Yeah, it's more like, safety is not a binary thing. Like, you are willing to get on airplanes because you think they're pretty safe, even though you know they crash once in a while. And what it takes for, to call an airline safe is like, a matter of some discussion. Some people have different opinions on, and.

• 28:07Logan Bartlett?

  It's a topical point right now.

• 28:08Speaker 01

  Topical point right now. They have gotten just unbelievably safe overall, like triumphantly safe. But safe does not mean no one will ever die in an airplane.

• 28:15Logan Bartlett?

  Similarly, medicine, we really, the side effects and some people have adverse consequences around it. And then there's the implicit side of safety as well, like social media, right? Or things that have negative association. Is there something that you could imagine seeing on the safety paradigm that would?

• 28:36Logan Bartlett?

  Cause you to act differently than pushing forward?

• 28:42Speaker 01

  Yeah, we have this thing called our preparedness framework. That's sort of exactly that saying that, you know, in these categories at these levels, we'd act differently.

• 28:48Logan Bartlett?

  I've had Eliezer on the podcast.

• 28:50Speaker 01

  How was that?

• 28:51Logan Bartlett?

  It was wonderful. We sat for the longest podcast I've ever done. I think it was four hours of us.

• 28:57Speaker 01

  He has more free time than me, so I apologize. I can't go that long.

• 29:00Logan Bartlett?

  I, we can, we can do multiple sessions. We don't need to do them all now. I think that his, his points, I think, stay fairly consistent.

• 29:06Speaker 01

  I'm grateful he exists.

• 29:07Logan Bartlett?

  He's a very interesting guy to sit down with for four hours and talk. We went a bunch, a bunch of different directions. But I'd be remiss as a, as a friend of the pod to not ask a fast takeoff question. I'm curious, like, there's so many different fast takeoff scenarios and one of the constraints that I think we point to today is just a lack of AI infrastructure. Right? And I guess if there was some, some researcher developed a modification to the current transformer architecture, where suddenly the amount of data and hardware scale needed drastically reduced more like

• 29:47Logan Bartlett?

  human brain or something like that. Is it possible we could see like a fast takeoff scenario?

• 29:55Speaker 01

  Possible, of course, and it may not even need a modification. It is still not what I believe is the most probable path, but I don't discount it. And I think it's important that we consider it in the space of what could happen. I think things will turn to be more continuous, even if they're accelerating. I don't think we're likely to go to sleep one day with like, pretty good AI and wake up the next day with genuine superintelligence. But even if, even if the takeoff happens over a year or a few years, that's still fast in some sense. There's another question about even if you got to this like really powerful AGI, how much does that change society on the next day versus the next year versus the next decade?

• 30:40Speaker 01

  And my guess is in most ways, it's not a next day or next year thing, but over the course of a decade, then the world will look quite different. I think the inertia of society is like a good helpful thing here.

• 30:50Logan Bartlett?

  One of the things I think people also find they have suspiciousness around. I imagine the questions you don't love getting are Elon Equity and November Board Structure. Those are probably the three.

• 31:06Speaker 01

  Which one of those?

• 31:06Logan Bartlett?

  I've answered them a lot of times. Which one of those do you like the least?

• 31:09Speaker 01

  I don't, I mean, I don't hate any of them. I just don't have any new to say on any of them.

• 31:13Logan Bartlett?

  But, um, well, I guess I'm not going to ask the Equity one specifically because I think you've answered that in more than enough ways, although it is, people still don't seem to like the answer that enough money is a thing.

• 31:30Speaker 01

  Yeah, if I like made a trillion dollars and then gave it away, it would just, it would like fit with, I think, the expectation or the sort of way it's usually done.

• 31:38Logan Bartlett?

  There was another Sam that thought about.

• 31:41Speaker 01

  Oh, that's true.

• 31:42Logan Bartlett?

  Trying that in some ways.

• 31:43Speaker 01

  Yes.

• 31:43Logan Bartlett?

  Yeah, comparatively.

• 31:44Speaker 01

  No, I just mean like most people who make a ton of money.

• 31:46Logan Bartlett?

  Yeah, yeah. What, uh, what do you feel like your motivations, this pursuit of AGI, like outside of the Equity? I think most people take solace in the fact that like, oh, well, even if I have some higher mission, I still get paid for it in some ways. Like, what are your motivations now coming into work every day? Like, what's the most fulfillment derived from?

• 32:10Speaker 01

  Look, I tell people this all the time. I'm willing to make a lot of other life trade-offs and sacrifices right now because I think this is the most exciting, most important, like, best thing I will ever touch. And it's an insane time and I'm happy it won't be forever. Like, you know, someday I get to go retire on the farm and I'll remember this fondly, but be like, oh, man, those were stressful, long, long stressful days. But it's also just incredibly cool. Like, I can't believe I'm, this is happening to me. It's like, this is like amazing.

• 32:42Logan Bartlett?

  Was there a single moment, I guess we go back to the same example of not being able to go out in your city or whatever, but has there been a single moment that was most surreal? That like, oh geez, I don't know. I mean, you've done a podcast with Bill Gates. I'm sure you have your speed dial. If I took your phone right now, it would have a lot of very interesting people on it. Was there a single moment over the course of the last couple of years that you were like, this is a uniquely surreal moment?

• 33:07Speaker 01

  Kind of every day, there's something that's like, wow, if I could like, if I had like a little bit more mental space to step back, it's like, this would be crazy. Um. Kind of a fish in water. But yeah, it is kind of like that effect. Uh, after all of that, like November stuff happened that, you know, like that day or the next day, whatever, I got like, uh, I don't know, 10, 20 texts, I mean, like that from like major world, like presidents, prime ministers of countries, whatever. And that was not the weird part. The weird part was that happened and I was like, um, you know, kind of responding, saying like, thanks, whatever, and it felt like very normal. And then I, we had these like insane, super jammed, like four and a half days and just this like crazy

• 33:51Speaker 01

  state and it was, it was just like weird, like not sleeping much, not really eating. Energy levels like very high, very clear, very focused, but just like your body was like in some weird, like adrenaline charged state for a long time. And then it was like, all this happened the week before Thanksgiving and it was kind of crazy, crazy, crazy, got resolved on Tuesday night.

• 34:12Speaker 01

  You canceled our podcast. Cancelled our podcast. Sorry, I don't usually cancel things. Anyway, then on that Wednesday, uh, like now it's the Wednesday before Thanksgiving, Ali and I drove up to Napa and, uh, stopped at this diner. Gott is very good. And on the drive up there, I realized I hadn't like eaten in like days. And then all of a sudden, like, kind of like normal, it was just like, okay, you know, this is like normally where we'd be doing on the weekend, heading out, like, whatever. And go to, uh, Gott's, order like four entrees, like heavy, like, you know, fried, like heavy, entrees, like two milkshakes just for me and I just sat there and ate. And it was very satisfying.

• 34:55Speaker 01

  And as I was doing that, um, one of them, president of this one country texted again and just said like, oh, I'm so happy this all resolved, like great, whatever. And then it hit me that like, oh yeah, like all of these people had texted me and it wasn't weird. And the weird part was like realizing that that had like happened in the middle of it. And that that should have been this very weird experience and it wasn't. So that was like one that sticks out. Yeah, that is interesting. My takeaway is human adaptability to almost anything is just like much more remarkably strong than we realize and you can get used to anything as the new normal, good or bad, pretty fast. And I kind of like, over the last couple of years, have Learned that lesson many times, but I think it says something remarkable about

• 35:41Speaker 01

  humanity and good for us and good as we stare down this like big transition.

• 35:45Logan Bartlett?

  I remember post nine eleven, I'm sure you remember exactly where, but I was in Southern New Jersey and our town, you know, whatever, dozens of people passed away and the how close the town came together after a terrorist attack happened and it seemed so normal, like that it was just the normalcy of it, or I have friends in Israel right now and you talk to them about it and they're like, no, it's it's normal. I'm like, well, there's a war going like it's got to be surreal. And they're like, well, I mean, what are you gonna do? You go about your day, you go get your food, all that. And it's it's amazing, these psychological impacting things. At the end of the day, we need to go get

• 36:27Logan Bartlett?

  food and we need to, you know, talk to our friends and all this stuff. So it is it is amazing how much that can happen.

• 36:33Speaker 01

  It really like genuinely, that's been my big surprising takeaway to like feel it so bitterly.

• 36:40Logan Bartlett?

  As you think about like models becoming smarter and smarter, what you kind of touched on this a little bit earlier with the the creative element, like, what do you think remains uniquely human as models start doing more and more capabilities of what we used to consider?

• 36:59Speaker 01

  I think many, many years from now, humans are still going to care about other other humans. I, you know, I was reading the internet just a little bit and everyone's like, oh, everyone's gonna fall in love with ChatGPT now and everybody's, you know, like, it's gonna be the ChatGPT girlfriend, whatever, whatever. I bet not. I bet we're, I think we're so wired to care long term about other humans in all sorts of like big and small ways that that's going to remain like our obsession with other people. Sounds like you hear a lot of conspiracy theories about me. You probably don't hear a lot of conspiracy theories about AI. You might not care if you did hear one. I think we're like not going to watch robots play each other in soccer probably as our like main hobby.

• 37:39Logan Bartlett?

  As you run OpenAI, the company itself, and you you built a lot of rules or frameworks at Y C on how to run businesses. And then you've you've broken a lot of them.

• 37:55Speaker 01

  Some.

• 37:56Logan Bartlett?

  Are there are there different types of people you hire for this business than you would have had you started a consumer internet company within the executive ranks or a B two B software company or something?

• 38:09Speaker 01

  Researchers are very different than like product engineers for the most part.

• 38:15Logan Bartlett?

  Brad or Mira or some of the executives like researchers are unique, but does OpenAI bring in a different type of executive or do you hire for a different trait?

• 38:26Speaker 01

  So I mostly have not like I am a sometimes you hire externally for executives, but I'm a big believer that if like you generally promote it's not it's probably a mistake to only promote people to be executives because that could reinforce a monoculture and you know, I think you want to bring in some new very senior people. But we mostly like homegrown talent here, and I think that's a positive, given how different what we do is from what you would do somewhere else.

• 38:52Logan Bartlett?

  Is there a decision that you've made over the course of OpenAI? That that felt the most important at the time of making it? And how did you go about making it?

• 39:09Speaker 01

  It'd be hard to point to just a single one, but the decision that we're going to do what we call iterative deployment, that we're not going to go build AGI in secret and then put it out into the world at once, which was the prevailing wisdom and the L A's or plan and others. I think that was like a quite important decision we made, and it felt like a really important one at the time.

• 39:30Logan Bartlett?

  If if another company that

• 39:32Speaker 01

  Betting on language models was an important decision and felt like an important one at the time.

• 39:35Logan Bartlett?

  I actually don't know the story of betting on language models. How did that come to be originally?

• 39:40Speaker 01

  Well, we were we had these other projects. We were doing the robot thing and video games. There was a very small effort started with one person looking at.

• 39:51Speaker 01

  Looking at language modeling and Ilya really believed in it. We really believed in like the general direction became language models, let's say. And did GPT one, we did GPT two, we started to study scaling laws, scaled GPT three. And then we made a big bet, this was what we were gonna do. And it was not, it looks so, all of these things look so obvious in retrospect. They really don't feel that way at the time.

• 40:17Logan Bartlett?

  One other thing you brought up recently was the, there's two approaches to AI, the replication of yourself and then the smartest employee.

• 40:25Speaker 01

  Oh, it's not, not AI itself, but like how you want to use it. Like when you imagine using your personal AI.

• 40:32Logan Bartlett?

  So there's a subtle distinction when you said it, but, but can you, can you expound on, cause it seemed like a fairly profound distinction of how at least Sam thinks about the, the future of AI use cases. So can you explain that point again? Cause clearly I misunderstood it.

• 40:50Speaker 01

  If you're gonna text me in, you know, five years in the future, I think you want to be clear of whether you're texting me or my AI assistant. And then if it's my AI assistant that's gonna like, you know, bundle messages together and you'll get a reply later. Or, or, you know, if it can easily do something you might ask my human assistant to do, then fine, you'll know that.

• 41:16Speaker 01

  I think there will be value in keeping what those things are separate. And not that it's like, all right, the AI is truly just an extension of Sam. I don't know if I'm talking to Sam or Sam's AI ghost, but that's okay, cause it's the same thing. It's this merged entity. I think, I think there will be like Sam and Sam's AI assistant. And also I want that for myself. Like, I don't want to feel like this thing is just like this weird extension of me, but that it's a separate entity that I can communicate with across a barrier.

• 41:45Logan Bartlett?

  You see it in, in music or creative where it becomes pretty easy to replicate a Drake or a Taylor Swift audio, we probably need some form of validation or some centralization that validates, say, this is actually the, the creative work of XYZ person. You're probably gonna want some version of that at a personal level too.

• 42:05Speaker 01

  Yeah, but it's like, you know, the, the way I think about like OpenAI is it's, I don't like, there's different people and I'm asking them to do things and they go off. Or they ask me to do things and I go off.

• 42:17Speaker 01

  But it's not a single like board. And I think that's like a way we're all comfortable.

• 42:22Logan Bartlett?

  And so, so what is that? Can you tie that back? Like the decentralization of letting individuals do their?

• 42:30Speaker 01

  Not, well, also that, but I meant more just kind of like, what is the abstraction of what my personal AI is going to be like?

• 42:37Logan Bartlett?

  Got it.

• 42:38Speaker 01

  Like, do I think of that as this is just me and it's gonna like, take over my computer and do what's best and because it's me, that's gonna be totally fine. And it's answering messages on my behalf and it's, you know, gonna just like, I'm slowly gonna like take my hands off the controls and it's slowly gonna like be me. Or do I think of this as like, this is a really great person I work with, that I can say, hey, can you do this thing? Get back to me, you're done. But I think of it as not me.

• 43:06Logan Bartlett?

  As you think about the educational system and as we think about like the class of, college class of 2030 or 2035 or whatever, whatever, some group in the future,

• 43:20Logan Bartlett?

  are there changes specifically that you think should be made within the college educational system to prepare people for the future we have?

• 43:32Speaker 01

  The biggest one is I think people should not only be allowed, but required to use the tools. There will be some cases where we want people to do something the old fashioned way, because it helps with understanding. You know, like I remember sometimes in math class or whatever, there'd be something you can't use.

• 43:48Logan Bartlett?

  No calculators on the test.

• 43:50Speaker 01

  Yeah, but on the whole, like in real life, you get to use the calculator. And so you need to understand it, but then you gotta be proficient using the calculator too. And if you did math class and never got to use the calculator, you would be like a less, less good at the work you need to do later. You know, if all of the open AI researchers never got to use a calculator, open AI probably wouldn't have happened. Computers at least, you know? We don't try to teach people not to use calculators, not to use computers. And I think. We shouldn't train people not to use AI either. It's just going to be an important part of like doing valuable work in the future.

• 44:25Logan Bartlett?

  Hey guys, I'm Jacob Afaron, a partner of Logan's at Redpoint. Wanted to take a quick break from the episode to let you know that Redpoint's AI podcast, Unsupervised Learning, now has its own YouTube channel. We have an incredible set of guests really at the forefront of the AI revolution. So if you're interested in what's happening in AI, what it means for businesses in the world, definitely subscribe. Now back to the show. Last one. In Planning for AGI and Beyond, you wrote, "The first AGI will be just a point along the continuum of intelligence," which we spoke about earlier. "We think it's likely the progress will continue from there, possibly sustaining the rate of progress we've seen over the past decade for a long period of time." Do you ever personally stop and process or visualize like what the future will look like in that?

• 45:10Logan Bartlett?

  Or is it just too abstract to contemplate?

• 45:14Speaker 01

  All the time. I mean, I don't visualize it like, you know, we have these like flying cars in a Star Wars future city and I like that, but like definitely what it means when one person can do the work of hundreds or thousands of well-coordinated people and what, what it means when, I don't want to say we can discover all of science, but kind of what it feels like, like what it would feel to us like is if we could discover all of science.

• 45:42Logan Bartlett?

  Be pretty cool.

• 45:42Speaker 01

  Yeah.

• 45:43Logan Bartlett?

  Sam, thanks for doing this.

• 45:44Speaker 01

  Thank you.

• 45:48Logan Bartlett?

  Thank you for listening to this episode of the Logan Bartlett Show with CEO and co-founder of OpenAI, Sam Altman. If you enjoyed this conversation, really appreciate it if you like and subscribe and share with anyone else that you think might find interesting, as well as come back for next week where we'll have another exciting episode with a different founder and CEO of an important company in technology. Thanks everyone for listening and have a good week.