Greg Brockman on Why OpenAI Says We’re Entering the AGI Era

25:22All they do is wreck our health and wreck our personalities. and the idea that humans are going to just run out of ideas of cool things to do or how to make the world better or problems to solve seems a little absurd to me. And so far, at least in the numbers, the better AI gets, the higher employment goes, not the lower. And so I wonder, and of course, it's unknowable. You know, we've never had this technology before. It's getting better and so forth. So how do you kind of think about the future of employment as it relates to these models and AI as it progresses? Well, I do have a fundamental belief that AI is surprising.

26:01And I think we even put this in the OpenAI launch post back in the day, in 2015, just saying that the history so far has been somehow it just doesn't play out the way that you think it does, even when there's this like logical conclusion it should be a certain way. I think the same will be true. I think that there's something that we've learned about that humans, I think like for any job that we almost, it's easy to not give it as much credit for how deep the field is and how much sort of sophistication, building relationships. Accountability is a good example of something where I think that people setting goals and being accountable for outcomes, like those feel fundamental to me.

26:35Those feel like the things that we actually should preserve for the long term. That's something that feels like deeply human. People are not valuable just because we can do tasks. right we're valuable because of our people and i think that it's important not to lose sight of that in some of these narratives and i think that the way that things will change and how what we do with our time evolves and we clearly will be in a world of abundance and how do we ensure that that abundance is broadly distributed um but also at the same time i think that we should be in a world where the ceiling of ambition is higher than ever before and i think we're going to see a wave of entrepreneurship where it's actually already starting i've heard um from someone in you know a particular industry was saying that a bunch of people in his world are now making the leap to go quit and start their own firms and that they're doing it because they have these ai tools and they're just like i can do so much more and so it's the barest entry and for andreason this should be a wonderful renaissance yeah well it's been a lot of fun for us in just going okay there are you know particularly for our young people because you know they get by default the grunt work.

27:38But like, what if the AI does the grunt work, then they can really develop much faster, actually, because they can kind of get involved on the, you know, really the real part of our business, which is what is the relationship with the entrepreneur? How do we open up the world for them? How do we make them feel like, oh, they can do anything and they're an important CEO and they can go build things? And as opposed to, you know, spend the whole weekend writing an investment memo, which, by the way, I have to say, ask for the fairy, get it, Friday, your best. It's awesome. I love hearing that. Yeah.

28:15Yeah. And again, I do think it's going to be a nuanced story, right? I don't think that we should paint that everything's going to be rosy and it's all going to be just easy. I think it's going to be hard. I think there's going to be change. But I think that it can be a much better world. I think the future can be much better than the past for everyone. Yeah. And that's, it feels like what we should expect, you know, like before the plow, you You know, the world was a lot worse. Like, it was just a worse life, even though it did put, like, a lot of human labor out of business, you know, and created the whole Luddite movement and all those kinds of things.

28:48You know, nobody here wants to go back to 1870. And so the idea that, no, we don't want to go into the future now seems a little short-sighted. But I think the speed at which things are moving is very, very scary for people. And we really recognize the fact of how things are moving and that we spend a lot of time really trying to understand as well as we can how people are feeling, how we can be showing up better. And I think that two things like one is that when we think about development, the pace of progress, we're being very deliberate about it. Safety is our foremost priority. We think about how do we build this technology in a safe, secure way and what should those standards be?

29:27And you can see that showing up in a lot of our comms inside the building. it is absolutely what people are thinking about and what we care about is that we really want this technology to empower everyone broadly. And I think that for us as a world to really think about how do we get the most out of this technology? How do we get the benefits? How do we mitigate the risks? I think this is going to become the most important conversation that we have. And I think that that will emerge over even maybe the next one to two years. I think that this should be something that is front and center. I think people sense it.

29:58You can sense it in how people react right now and even thinking about things like data centers and these kinds of questions of, do we want AI? And how do we think about where it's appropriate? And how do we ensure child safety? All of these kinds of questions, these are core questions that we care so much about getting right. To that end, why do we think sentiment in AI is higher in certain Asian countries? All Asian countries. Well, and actually in European countries, everywhere. But the U.S. has like got the lowest AI sentiment. Why is that? Or maybe more? What's driving that? What can we do about it?

30:29Like, what can we learn right from? Well, one thing that I think about is that I think we as a field, as a company, need to do a much better job of articulating to people why they benefit. Why is this a good thing for them? And not just for the country, right? Which I think that this technology is going to be and is rapidly becoming the single most important strategic priority and resource for the United States. It's Abino. Yes. Absolutely. You look at ChatGDT, 300 million health queries, there are 300 million people every single week using it for help, right? That's a huge deal. And we're at a billion, almost 1.1 billion weekly active users.

31:09I think within the US, it's about 100 million, something like that. Like a third of the population, if I have that number correct, right? Is using chat every single week. So people are touching this technology. But I think that for many people, there are some people who have gone very deep and really gone through the health journey, for example. that's been true for my family for my wife that she has a number of health conditions of the we don't even really know how we would have managed these before chat and there's just so much toil and time and just getting to the right answer and a doctor tells you something you don't know what the thing is and how do you get that that sort of sanity check to really even understand it people who i that their life was saved through information delivered by chat gbt i'll tell you story for one of my friends is that she was in the hospital and the doctor was about to inject a antibiotic.

31:59And she was like, give me a moment. She typed in to chat, shoot you tea. And chat said, absolutely do not take that. If you do, you may die because you have this thing that you had a year ago. You have this condition, like this kind of thing. Your reaction showed the doctor. I know, right? And the doctor said, oh my goodness. No, no. That's absolutely right. I had no idea. I only had five minutes to read your chart. Yeah. Many such cases, by the way. At least only stories in your chart, at least. Exactly. And so these kinds of stories, I think, don't get told nearly enough, but they're out there.

32:31I hear them every day. And the people who run their small business on chat and would be totally unable to do it otherwise, like that kind of empowerment. Again, people who are able to save money, make money, live a better life. Those kinds of stories, I think, need to be in the public consciousness as we approach this question. So it's painting the narrative that you've got a teacher in your pocket, a doctor in your pocket, something, you know, a lawyer in your pocket, therapist in your pocket, you know, all these utilities in your pocket, while also not threatening the same, well, also telling the teachers and doctors and lawyers and therapists that, hey, you've now got this tool too, and it's going to make your business better as well.

33:04Yes, and it's not just the narrative, it's the reality, right? You need both. I think that many other countries are looking in, seeing the position that the U.S. is in, right? Seeing the potential of this technology. And partly, do you think about demographics? That I think in many of these other countries, it's more keenly felt that there's an older generation that's much larger than the younger population that is going to need to support them. These questions of how is that supposed to work? And so I think that there's something about really thinking to the future and thinking about what's possible, how do you get the benefits out of this technology and really wanting to lean into that that I think we're seeing across the world.

33:42And so again, I think that there's something that we need to do better as a field and as a company in order to communicate this domestically. But I think the potential is there and we're in such a privileged position and leading this field in a way that I think was not guaranteed and it's not guaranteed to remain true for the future either. Yeah, particularly if we ban data centers. I think that'll be a problem for us maintaining our lead. It will drive the data centers overseas, which is what happened with Silicon back in the 80s or so. Right, right. And there are so many, you know, one of the interesting things about data centers is it creates so many blue-collar manufacturing jobs.

34:22I think Switch employs like 45 ,000 people on kind of a union contract basis to build data centers. That's just one of the data center providers in the U.S. And they're great jobs. They're high paying. And then, you know, I think that while there have been bad actors in the data center space, most of them are very good actors and contribute to the power grid, don't waste water, and are not noisy. And so, like, not that there was never an issue, but, like, we could just say, hey, you have to be a well-behaved data center as opposed to, like, we're going to ban them or, like, we're going to stop AI, which I, like, we're not going to, even as a country, we're not big enough to stop AI.

35:16So that idea, like AI will continue without us, and then we'll have zero say, as opposed to we're the leaders, and then we have all the say. So it's a really, really important cultural message. I think it's very important. And I think on data centers, so we've made commitments on not increasing people's electricity bills. Our data centers are all closed-loop water. So the amount of water used by Abilene, which is the data center that actually trained Astra, that it uses about the same amount of water as an office building, right? So it's really, yeah, the technology is quite advanced on that. And we have a number of community commitments so that we can actually help in Ohio and Georgia, where we have data centers we've announced, we've talked about how we're providing credits to every college student for codex access.

36:00So there's this broad set of benefits that we're bringing to bear. But again, I think that we need to do even more. And, you know, like I think making those kinds of things a requirement to build a data center is very reasonable. But, like, let's have positive some ideas as opposed to, okay, we're going to jump out of the AI game as a country and we'll let China or whomever dictate what it's going to be. Speaking of contributions, you guys have made a billion-dollar commitment to frontline defenders. Why don't you talk about that? So we believe that every organization, every company, every government, critical infrastructure, such as water service providers, hospitals, should all be using this defenders window to secure themselves.

36:43But not every organization will have the capital required to do it. So we have a billion dollar commitment to frontline defenders. So to organizations that we all rely on every day in our communities to access our models to secure themselves. We think this is the beginning. This is not the end. We're working closely with partners. For example, Proudstrike and we are working together to provide discounted access to defenders as well. And I think that there should be a global effort in order to bring these tools to bear to really secure every single organization, given what we see coming and what's possible.

37:18Yeah, and that's a super positive advance because this is our before AI. Hospitals were getting broken into, held hostage all the time. Our water supply has been hacked by foreign actors, state actors. And so, like, we're already dealing with kind of our critical infrastructure was not built with cybersecurity in mind. It's not been maintained with cybersecurity in mind. And here is an opportunity to go from not even secure in a pre-AI world to completely secure. So, to me, this is like an incredibly important effort to, you know, not have our water supply and our hospitals at risk. I really agree with that perspective, right?

38:07That the point of, I think that we as a society have been lax, right? That we've allowed tech debt to pile up. That every cybersecurity organization, I've never met a CISO who felt that they were appropriately resourced, right? That they were appropriately prioritized. Never. And particularly not in the public sector. That's right. And so I think that we have to change that. And we should have changed this years ago. But now is a moment where we actually have a real both motivation to do it and a real ability to do it. And I think that delivering the secure world that we all deserve so that we can really depend on it and be safe and secure in our daily lives and online lives, like, that to me feels like table stakes.

38:45We absolutely need to do this. Yeah, definitely. That's a great effort. Closing the loop on Astra, you've emphasized that capabilities still remain jagged. what do you think still left to go or still needs to be fleshed out that gets approximates most of your definition of AGI? Well, I think that AGI has turned out to be less of a point in time and more of this sort of fuzzy spectrum. And for me, Astra has really hit something that I'm like, okay, I think this is pretty reasonable to call it AGI in that with its computer use capabilities, you really can ask it to do long of tasks and it'll just do it.

39:19That we've seen it run coherently for 24 hours to go accomplish tasks that I think are quite amazing and across a wide variety of domains. Now, it still is jagged. And so that there are still places where, for example, it's writing. It's pretty good writing. It's the first time it's not slop writing, but it's not great writing. And I think that there's a number of areas where I feel like we just need to polish it a little bit and it would be fantastic. And it's just like not quite there. So I see this, like, I saw someone post a graph on Twitter of like, you know, this like kind of, you know, jagged frontier and that where we really need to be is a much more steady across the board, really hit on all these categories.

40:00But I think that what people are finding is that it is so capable across such a wide variety of tasks that it is accelerative, it is empowering. And it's something that I think we've never really seen a model that's been a jump like this. Yeah. One of the things that's been interesting for me is that as you solve problems, sometimes the world doesn't realize it. Like, so I haven't seen a hallucination in quite some time. But nobody says, oh, the models don't hallucinate anymore. It's just kind of in the ethos of that's what AI does. How do you, do you think that'll just go away over time or is it, you know, does there need to be some, like, continual education for the non-hardcore tech people?

40:51I think one of the most important problems we actually have is the continual education, right? Really, how do you, people shouldn't have to extract from the AI what it's capable of. It should go the other way around. The AI should say, hey, I can help you in this new way. So we have about, you know, we have over a billion weekly active users on ChatGPT, but I think we have something like another maybe 1.5 billion people who have used ChatGPT and don't use it anymore. Oh, wow. Right? So think about that. That's a significant fraction of the planet. And those people, exactly, those people, we should really be able to go back to and say, hey, we have made so much progress.

41:27We think we can be useful to you in these ways. And I think that that just shows you the kind of problem we have in front of us is that these AIs, like if you look at ChatGPT and ChatGPT work, they're both text boxes, right? And it's like this new text box is way better than the old text box. But there's still some things that the old text box is better at. So don't always use it. It's like, that is not the AI we were promised. The AI we were promised should be an AI that you talk to over voice primarily. You can talk to it over text if you want to. That it has persistence. That it has memory.

41:56It has context. It knows you. It's trustworthy that you have seen it be proactive and help solve problems for you. That help in your personal life and your work life. And that's how it should be. It should be something that is able to, that you can really sort of rely on for the things that you care about. That empowers you and helps you solve your goals. And I think that being able to explain to you how it can help you is a core part of that. Interesting. And proactively do it. That's such an interesting idea. Like, we need more helpfulness out of our AIs. Yes. Which is kind of a thing. Like, some humans aren't.

42:34And probably the humans who develop AI are not very helpful people, I would guess, just being around engineers and researchers. You'd be surprised. I think we have very, very helpful engineers at OpenAI. But there is something about, if you think about how do you work with another person, right? A new coworker you've never worked with. It takes you a little bit of time, right? You kind of feel them out. You see how they respond in different areas. People do not come with an instruction manual. And often, actually, sometimes it's interesting in areas like consulting or something where they really lean into like Myers-Briggs and that they do say like, here's like a quick way to know who I am and how I operate.

43:07So that there is some precedent for how humans can kind of present a little bit more. You have a resume, you have a certain track record. People can ask for back channels on you. So we have built up a way of how do you understand how a human will work and what the best way is to get the best out of that person. And I think sort of figuring out what is the right analog for AI, and especially as AI changes and we produce new tools and product surface and new models and all these things, I think that this will be a very important society-company interplay. And again, I think that what our North Star should be is simplicity, right?

43:43That we really should be one AI that's unified, that makes it so easy and smooth for you to be less engaging with the computer and less wrapping yourself around the computer. The computer should be there to empower you to help serve you. Right, right. On that note, the business is ripping. You guys have such broad surface area in terms of what you cover. How do you decide in terms of prioritizing where to go deepest, what not to build? And then also your role has also evolved and changed and you've encompassed so many things, research, product, commercialization, organization management, et cetera.

44:19How are you also thinking about prioritizing your time? Well, they go hand in hand. So this year, the theme was focus. I think that we really realize that we can't do it all, right? We need to pick. And particularly, there's one thing we're trying to accomplish, which is our mission, right? We want to ensure AGI benefits all of humanity. Now, how do you backsell from that? What are the areas like deployment and productization is actually something that does reinforce that, right? That we do want to bring this technology to bear and have it uplift everyone and people deploying it in useful applications, all of that personal life, work life, the whole thing.

44:52Very core. But how do you, when you think about this moment we're in of this agentic coding takeoff, that exponential, what areas reinforced that and which ones were kind of just sort of, you know, they got labeled a side quest in the media, but just were not on track for it, even if they were individually something very exciting, was a very core question that we had to grapple with. And so things like Sora, that's maybe the highest profile one of these projects that we decided to cancel. Very, very painful, by the way. Not an easy thing to do, but it was so critical to unleash the business in many ways so we could really focus.

45:27Bringing together the consumer and enterprise side of chats into chat work, that's another area where we really had to focus and really say this is what we're doing. So a lot of the way that we've thought about this to unlock this moment is to really have vision about where we think the future is going and how do we think that the new capabilities that are emerging can best be brought to bear with a single unified stack that works across the different areas, different walks of life, different areas that we're trying to focus on. And it's been painful, right, that if you look for the first half, I think that there's just a lot of metrics that were not looking the direction that we wanted and that there was a lot of just sort of telling the team we just need to focus on the basics.

46:04like one of my favorite management books is The Score Takes Care of Itself. Have you guys read that one? Yeah, Keith Reboi's favorite. Yeah, it's a great one. And it just is a very empowering book because you just realize it's like you cannot affect the outcome. You can only affect the inputs, right? You can only affect the like the basics. And so focus on those basics, right? You don't win the Super Bowl by saying, I wanna win the Super Bowl. You win it by blocking and tackling. And so that's what we have done for this whole year. And for myself, I throughout OpenAI I have always focused on whatever is the most important problem that I think that I can move the needle on that just isn't going to happen without me.

46:39And for the past two years, it's been the data centers, the infrastructure, the machine learning, engineering. And that's an area where we really spent a lot of effort to get our pre-training infrastructure into great shape. This year, it's really been about the business. It's really been about the, okay, we've figured out how to get the research really humming. We figured out how to get the infrastructure really humming. But how do we really bring this technology to the world? And I think that that's where I've been really putting a lot of my efforts and trying to bring together a bunch of functions that were otherwise kind of running in parallel or crosswise.

47:12And that is something where I think as a founder, as someone who has kind of touched every part of this business from the beginning, I think I've been uniquely able to go in and make the changes, make the hard decisions and really figure out this is the direction. Let's go. and a lot of my style is that I like to lead from the trenches. And so I get very deep in the weeds on what the thing is and really try to keep asking a lot of questions. Like that's actually a lot of my style is just asking like, wait, does this make sense still? I don't quite get that. Sometimes when things are confused, for example, over the past couple of days, there've been times when it's just like, we've got a thing, we got to figure out how to even talk about it.

47:46How do we think about it? How should the world think about this? And I'm just like, let's just get everyone who can touch different parts of the elephant on a call. We're like going through a Google doc on Hangout and just kind of like being like, Like, does this line make sense? Wait, what do we really mean by this? And so really trying to up-level execution, sometimes in small ways and sometimes large. That's fantastic. By the way, exact right way to operate. Do you know what the next year we'll focus on? Or keep it up for now? Look, I think that the business is a huge area that I think we're not done yet with really up-leveling every part of execution.

48:18So I think there's a lot more to do there. But I also think we are moving into a new phase of AI development, right? I call this and we call this that we're now in the AGI era. And I think that that is something that you can debate. Is it this model, previous model, next model? It doesn't matter. The point is that we are in a new phase where safety, security, alignment, really thinking about these things, not just at deployment time, but all the way back at development time, evaluation. It's objective. This is critical. It must happen. This is core to our mission. This is core to what we need to do.

48:46And so a lot of what I spend my time thinking about is making sure, do we have all the right processes? Are we talking about the right things? Do we have plans that really at a operational level, at a practical level, lead us to the kind of security and variance and the kinds of safety guarantees that we view as core to our mission, what we need to do? And so I think that, again, the theme of OpenAI, certainly for the past five years, has been deeper co-design, deeper intertwining across these functions that are maybe on the surface very disparate, right? All the way from go-to-market to long-term research to chip design.

49:24By building these in a coherent way where everyone has context, right? They kind of understand how do I fit into the overall picture? What are we trying to do? And what is the end outcome we want to achieve? You've like, that is what has to happen. So I think that the areas that I will focus on, I think will be dictated by the areas that most need that intertwining. And I think that I see us moving more and more in concert in lockstep as time goes on. I, we could go all day, but we have a hard stop. I think this is a great place to wrap. Greg, thank you so much for coming on the podcast. Thank you for having me.

49:57Great, fantastic. Thanks for listening to this episode of the A60Z podcast. If you liked this episode, be sure to like, comment, subscribe, leave us a rating or review, and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts, and Spotify. Follow us on X at A16Z and subscribe to our Substack at a16z.substack.com. Thanks again for listening, and I'll see you in the next episode. As a reminder, the content here is for informational purposes only. should not be taken as legal business, tax, or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund.

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