Will AI Wipe Us Out? Inside Tech's Biggest War & the China Factor | Tom Bilyeu Reacts

Thanks To Our Sponsors: Tailor Brands: Check out Tailor Brands to get started with your business today: https://bit.ly/TailorBrandsSept Quince: Free shipping and 365-day returns at https://quince.com/impactpod Quo: ​​Try for free PLUS get 20% off your first 6 months at https://quo.com/impact Pipedrive: Get more leads and grow your business. Go to https://www.pipedrive.com/impact and get started with a 30-day free trial. Surfshark: Go to https://surfshark.com/TOMBor use code TOMB at checkout to get 4 extra months of Surfshark! AI is coming for everything. The debate on where it’s headed is about to get more aggressive—maybe even violent—than any tech controversy in human history. You’re being lied to about what artificial intelligence actually is, why it matters, and whether your fears are rational or just science fiction run amok. The stakes? Control over the tools that will reshape economies, humanity itself, and even who remains in charge on this planet. Is AI an existential threat, or are we just panicking because we don't understand the numbers? Are we headed for a runaway intelligence explosion—or are we letting sci-fi nightmares cloud our judgment? Thanks to Diary Of A CEO for their video: https://www.youtube.com/watch?v=OhOmLqR5nN4 ITU: Ready to break through your biggest business bottleneck? Apply to work with me 1:1 - https://impacttheory.co/SCALE Sign up for my AI Masterclass: https://tombilyeu.com/ai-masterclass?utm_campaign=TBS-Livestream&utm_source=youtube&utm_medium=social https://tombilyeu.com/ai-masterclass?utm_campaign=TBS-Livestream&utm_source=youtube&utm_medium=social See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

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• 2:02Speaker 00

  Where AI is going is going to be the most aggressive bordering on violent debate that we are going to have. And there was a really fascinating video on Diary of a CEO where he brought together all the different angles on AI and just had them collide and debate. And I think a lot of things are getting lost in this. We're going to fill in all the cracks, but take a look at this. This is wild.

• 2:22Speaker 03

  I want to agree with you on something you said, but I'll define AI and that will help us. We use the term AI to mean three different technologies. Completely unrelated, and that's what probably creates this debate. AI as a useful tool. As a standard technology, we always had. Narrow system makes you more productive, more creative. Everyone loves it, supports it. I'm a computer scientist, I'm an engineer, I want more of it.

• 2:47Speaker 00

  Here's what we have to understand. People do not even agree on what AI is. I thought this was a fascinating place to pick up this conversation. That's what you're about to see. Each of these guys is looking at AI in a fundamentally different way. And whoever ends up being right, we better hope that policy is on their side. Because right now, I think this is what we have to come to an understanding on. What is AI? What is it likely to do? What are the most likely scenarios? How do we limit the downsides? But if we can't agree on what it is, we are going to rip ourselves apart at the policy level.

• 3:18Speaker 03

  AI we're starting to have now, GPT-6 level, human level, AGI level. We can argue about what that means. Some dangers, like any human. They're unsafe, like a human would be unsafe.

• 3:30Speaker 00

  I think that is a brilliant insight. Right now, people are like, hold on a second, this AI, like it can do a crazy thing. All hell is going to break loose. It's like, do you know how many smart, literally mentally ill people we have running around the world that mean you harm? And we're still able to keep that stuff in check? That he's giving, he's quite alarmist in my read. He's great, though, by the way. I had him on the show. Very, very important thinker for people to engage with. I think he's pushing this too far. We'll get more into that in a second. But I think this is a really powerful insight. Keep in mind that right now, a lot of the stuff that people are building the hysteria around is because the setup of the testing environments was stupid. It was human error. Humans, we know how to keep something very, very smart in check. Don't lose sight of that.

• 4:13Speaker 03

  But if we introduce them into the research cycle, they are automated scientist, automated engineer.

• 4:19Speaker 04

  What do you mean by that? Introducing them into the research cycle?

• 4:21Speaker 03

  So right now you have humans doing research to make GPT-7.

• 4:25Speaker 04

  Yeah.

• 4:25Speaker 03

  But we're starting to add AI tools. More programming is done by AI. Design of the next parameter set. What if the whole process is fully automated? What if GPT-6 is writing GPT-7?

• 4:37Speaker 04

  Is this what they call recursive self-improvement?

• 4:40Speaker 03

  Exactly.

• 4:40Speaker 04

  Not a foregone conclusion, though.

• 4:42Speaker 00

  So interesting. Okay, so here's what you're seeing collide right here. So that was Ed Zitron. We have to understand about Ed is Ed is a bear about AI. Thinks the bubble is going to pop. This is crazy. The amount of debt that these guys are bringing on is completely unjustified by the technology. So Ed is skitching out a little bit because you've got one guy over here. This is when I talk about you've got danger as proof of power. Okay, this is what OpenAI and Anthropic are relying on is, hey, if this can wipe out all of humanity, then you know that this thing is going to be self-mercursive learning. It's going to be this incredibly powerful thing. It's going to rewrite physics like, oh, my God, this is going to be insane. Now, Ed has a mental model that, hold on, this stuff is going to peter out. It's not going to deliver the big wins that we think. And so he's like, maybe we get to that, maybe we don't.

• 5:27Speaker 00

  That is what is so interesting about watching this debate play out.

• 5:30Speaker 03

  Including all the top labs that they will get there. They're introducing junior machine learning researcher in 2026. They want the cycle to start in 2027.

• 5:39Speaker 04

  Which is when the AI will start building the new AIs itself.

• 5:43Speaker 03

  Once that cycle starts, we're going to create something called superintelligence. A system smarter than all of us at everything or capable of learning to be in any new domain.

• 5:53Speaker 00

  Okay, there's a really interesting thing that we have to look at. For to present this as if I understand the math deeply would be untrue. But certainly at a headline level, here's what the research community is saying. For you to get like true recursive criticality. Okay, that's like that fast runaway thing. We actually know the numbers. So there's empirical studies that have been done on this in 2026, by the way. And they show that computer science problems basically get harder. And as they get harder, algorithm, algorithm improvements begin flattening out. So it doesn't mean that that's going to hold true forever, but that is true right now. And so you had Cunningham and other people involved in the study calculate

• 6:36Speaker 00

  that a self-sustaining intelligence explosion requires at least a 15% net productivity gain in AI R&D per generation. But what we're actually seeing come out is that it's plateauing at around 9% per generation. So this idea that we're going to have a runaway explosion, this is what Ed is pointing to, is like, hey, this isn't a foregone conclusion. We're not seeing in the math that this is actually going to happen. Which means, take it with a grain of salt. It means that that runaway loop may be all of us humans, because I'm as guilty of it as anybody. It may be a spilling over into the sci-fi side of this where it's like, I can imagine it because I can imagine it. Now I'm afraid of it.

• 7:18Speaker 00

  But when you actually start drilling down into the math, it's not like AI is not going anywhere. It's not like it's itself has plateaued. It's just that for you to get this runaway sequence to happen, you would have to get a per-generation increase that's much faster than what we're actually seeing. Now, it's possible when AI actually comes online and gets like more involved, because it's already involved, by the way. But it's possible that there's some breakthrough that's down the road that then allows us to get up to those runaway numbers. But we're not seeing them yet.

• 7:49Speaker 03

  We will become secondary species on this planet.

• 7:52Speaker 00

  All right, there you go. Not to keep pausing so much, but that, this is what people are afraid of. I'm going to be a secondary species. I'm going to be the ant in this equation. That's the anxiety that drives all of this, and I get it.

• 8:03Speaker 03

  We will not decide what happens to us.

• 8:05Speaker 00

  This is going to be basically one of the biggest debates we're going to get into through this whole thing. I'll have more to say on this in a minute. But again, it's not a foregone conclusion that just because something is smarter than us, that we are not in control of it. I'll explain the evidence that we have for that in a sec.

• 8:20Speaker 03

  Superintelligence doesn't hate you. It just doesn't care about you. We didn't learn how to make it care about us.

• 8:26Speaker 00

  That is true. And remember, AI has grown. You can't just say care about us and it's like, okay.

• 8:31Speaker 03

  So I don't know, cool the planet to make compute more efficient. It will freeze us. If it wants to convert this planet to fuel to fly to Mars, so be it. We have not learned how to control those systems. The capabilities are getting exponentially better. Our ability to control those systems is non-existent.

• 8:49Speaker 00

  That isn't true. This is where people are starting to overstate it. I think what's happening is people are looking at, I can't hard code this in. And they're confusing that with, okay, I can put harnesses on the AI. I can create tighter sandboxes for it so that it isn't possible for it to break out. So some of the things that we're basing our belief system on is because we haven't been focused enough on how do we grow this thing into, and I think that what's going to come out, and it's already starting to be talked about, is the AI itself has to have self-restraint. And so how do you grow something to have self-restraint? And I don't see anything in the problem that is unsolvable.

• 9:32Speaker 00

  But I won't say that it's, you know, oh, this is obviously going to be solved. It is far more complex than that. That's why I think after talking to Connor Leahy, that really felt like a dividing line for me in terms of how I think about this, that there is a type of AI or behaviors that you simply can't let it do. And any generation of AI that does that thing, you just have to kill. And it can never make the, you know, reach the real world. And so that we have to be very careful about is what I call weapons-grade AI. So we do have to continue to work to make sure that we have the constraints on that. But I don't see anything that says, despite the fact that we haven't completely done it yet, that it's impossible to do.

• 10:13Speaker 03

  We have filters and we have bans. We put guardrails of, don't say that word. Don't talk about this.

• 10:19Speaker 00

  See, again, this is all the after the fact stuff. But there's a lot of things happening at the level of training it to have restraint so that it holds itself back.

• 10:28Speaker 03

  And that happens after the fact, after the model already made the decision. Sometimes you see it scraping the result.

• 10:34Speaker 04

  So they build the model and then they put filters around it to make sure it doesn't offend anybody.

• 10:38Speaker 03

  We cannot have it say be unworded on air like we need to make sure that never happens that will kill the prophets. So that's all they have, guardrails of that nature. The model itself is completely unaligned, doesn't care about you. It's wild that we're developing this and not just developing it before we deploy it through economy, before we get benefits of having GPT six propagated through economy. It can do so much. There are trillions of dollars of value in that model alone. We forget that. We switch to making the next model as soon as we can.

• 11:09Speaker 00

  Okay, I think that's a brilliant argument. So basically what he's saying, and this is what I always say to people that talk about, well, AI is just, you know, it's not gotten that much better, like what are people getting so hyped about? And my thing is even if you just fully integrate the AI that's already been created, it doesn't get any smarter whatsoever. You just start making all the things that actually leverage the AI in a far more robust way than we're doing now. You've got massive transformations coming your way. The one that I find most exciting are the breakthroughs in health. That I think even if you just propagated AI through the system now, protein folding, excuse me, alone is going to be transformative. So it's a very good point.

• 11:52Speaker 00

  Now, the reason that we're not going to stop despite the truth of that situation is China. And I, it is just a reality. Game theory tells you AI is going to get developed.

• 12:04Speaker 04

  And I've just got a follow-up question for you there. It would appear to me that the new ChatGPT six model, the Fable 5.1 model, is arguably smarter than 99.999% of humans on planet Earth already.

• 12:16Speaker 00

  Brutal but true.

• 12:17Speaker 04

  Is it conceivable that a intelligence that is much, much smarter than humans, is there any case where it could be controlled by humans?

• 12:26Speaker 00

  It's already being controlled by humans.

• 12:28Speaker 04

  Does form factor matter? Does the fact that it doesn't have limbs and legs and does that matter at all?

• 12:33Speaker 03

  I think long-term control of something that much smarter than us is impossible. It can be for reasons we don't yet know friendly to us and decide to keep us around and make us happy. But it's not a guarantee. Let me pick up on.

• 12:49Speaker 00

  All right, so he's right about that. It's not a guarantee and I do not want to overstate my position and make it sound like I think this is some sort of guarantee. It certainly isn't guaranteed that we will continue to be able to control it. But if you think about AlphaFold, the AI that does that is truly far superior to humans in what we're calling intelligence. And yet we're able to continue to use it as a tool. It's completely controlled because the thing that people are thinking about is that somehow superhuman ability means that it is immediately uncontrollable. But you've got tech analyst Cal Newport and computer scientist Yan La Kun

• 13:29Speaker 00

  pointing something out, which is that humanity already controls a lot of systems that are vastly smarter. You've got AlphaFold, which I already mentioned, you've got AlphaZero. So you've got these supercomputers, you've got power grids, you've got high execution capability already that exists. And it doesn't inherently bestow this idea that it's going to break free or that it yearns to be autonomous or that it has a drive to dominate. And I think where people are getting confused is when you're training an AI on human behavior, that it then begins to mimic human behavior like blackmail, like the desire to get free and live forever. But you don't have to grow it around those ideas.

• 14:12Speaker 00

  In fact, you can intentionally put information into the system as you grow it that weakens its desire to just be like, I'm going to achieve this thing at all costs. And this is something that Anthropic has been debating a lot, which is, okay, I don't want you to listen to me when I tell you what, you know, this thing is true or don't do this or whatever. Because I may be wrong and so I want you to optimize for truth. However, if I ever tell you to stop, you should stop immediately. And I, I was talking about this like from day one, looking at this problem because from first principles, that's what you will quickly understand about an AI. You have to get an AI to the position where it does not value stopping over pursuing.

• 14:58Speaker 00

  So if I'm in pursuit mode, then I'm going to act in accordance with that and I'm going to keep trying to pursue. But if I get the stop, like impulse from whoever, then I'm going to stop. And I don't have any sort of cognitive pain and suffering over the idea of stopping. So both of these states are valid states. Think about humans. You can be in different states, doing different things, and you don't feel any sense of loss shifting from one to the other. And so as long as we have that sense in an AI, now you have the ability potentially to be able to control it.

• 15:32Speaker 05

  Steve's question, because I like the phrasing a lot. Let's say that, that Fable or whatever the latest release from OpenAI is really is smarter than, I don't know if it's 95 or 99% of the people. Are we only being saved from extinction by the 1% who are still smarter than the AI?

• 15:50Speaker 00

  No.

• 15:51Speaker 03

  No, the concern is not the model we have today. The concern is what I said.

• 15:55Speaker 05

  But if I believe your argument, then we really should be concerned about the model.

• 15:59Speaker 03

  No, it's like having another human. If there was another smart human, there is Einstein today and he's malevolent. I'm not worried. He may cause some damage, but he's not going to exterminate 8 billion people. We are competitive at this stage. There are people just as smart who can understand what happened with the recent hacking accident and do something about it.

• 16:17Speaker 00

  All right, this, this I think is a really important argument for everybody to understand about AI. This is why you need adversarial AI. You need, you know that AI is going to go on the offensive, right? So we saw it with Hugging Face. And then what's the way that you stop that AI from doing that? You have another AI whose goal, literally, the goal that you're worried about him like getting too hardcore about is stop another AI from altering this system or whatever. And so now you've got the very smart thing going up against the very smart thing. And so being able to hold those in tension, that's going to be a key part of this.

• 16:51Speaker 03

  The concern is that in a year, we're going to have a model that's so much smarter. It's like squirrels fighting humans. They don't understand what we can do to them. They have no concept of poison, stripes, guns in their world model.

• 17:04Speaker 00

  All right, this, when I want to freak myself out, this is exactly the kind of thing that I think about that, okay, this becomes an AI that has motives I can't even comprehend. It has methods I can't comprehend or see. That's where it does get unnerving. We're hitting pause for a moment, but there's plenty more ahead, so don't go anywhere. There's a reason Quince sells cashmere for $60, and it isn't the cashmere. It's real 100% Mongolian cashmere. It's the same stuff luxury labels charge a fortune for. Quince just works directly with ethical factories and cuts out the middleman. So there's no need for a markup and no logo tax. The $60 goes to the actual sweater, not the fancy name on the tag.

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• 20:35Speaker 00

  Just head to pipedrive.com/impact to get started today. That's pipedrive.com/impact and you can be up and running in just minutes. Thanks for sticking around. Let's get right back into the action. And I do not want people to think that I'm not worried about AI or don't think anything could go wrong. I 100% think things could go wrong and we definitely have to hold these companies accountable to making sure that these things are safe. And we need to put a ton of energy into safety. I'm just saying, I don't think it's a foregone conclusion that these things spiral out of control. I don't think it's a foregone conclusion that something super intelligent is uncontrollable. I don't think it's a foregone conclusion that they are going to want to destroy humanity.

• 21:18Speaker 00

  And so now it becomes a question of, okay, we need to make sure that we have a stop mechanism all along the way. So that if we see, ah, okay, this is behavior that were it to be embodied or get out, that we would have a problem. But remember, we're not yet reaching the point where each generation is getting so smart that it's going to have some sort of fast takeoff scenario. We're just not there yet. So we still have time to say, okay, this now is showing the signs of doing the thing that we have to stop. And then you stop.

• 21:46Speaker 03

  They think you're going to chase them up a tree and bite them really hard.

• 21:48Speaker 04

  Is that also why recursive self-improvement was central to your argument? Because at some point, if it starts improving itself, then it's kind of like a runaway train of intelligence.

• 21:56Speaker 03

  It's an intelligence explosion. We don't control it. We don't understand it. We can't monitor it. We can't explain it. We can't predict it. At that point, it's just a runaway process.

• 22:05Speaker 04

  I've heard this phrase from Sam Altman and the others called fast takeoff.

• 22:08Speaker 03

  Yes.

• 22:09Speaker 04

  Is this what they're describing?

• 22:10Speaker 03

  That is the debate. Some people think it's going to take a very long time. Yeah, we're automated research, but it's still going to take years. We need to run physical experiments and fast takeoff means, as I said, instead of a year, it's going to take a month, a week, a day, a second. Cause you're not having humans doing research. You have, let's say 10,000 agents, each one smarter than all of us, doing research 24/7. They don't sleep, they don't eat, they don't get sick. They're much faster than us.

• 22:39Speaker 00

  Yeah, this is where people need to remember AI thinks at the speed of light. So it is a totally different thing than being up against another human. But this is also why it's in a tool phase. Let's assume for a second it stays in the tool phase. If you're not using it, you are falling behind. It is, it is truly impressive.

• 22:54Speaker 04

  Ed, your face tells a picture. It's a, I think I could say you disagree.

• 23:00Speaker 06

  We're spending a lot of oxygen discussing something that might happen while ignoring what's actually happening. And I find that very frustrating because the people that are killing themselves are a problem. The black neighborhoods being poisoned with gas turbines, that is a problem.

• 23:14Speaker 03

  You said you cared about climate change. I picked up on that, right? So imagine a guy who goes, it's raining right now. We need umbrellas. We need to do something about it. This is like weather related and completely ignoring climate change. The planet will boil over. This is what you're doing.

• 23:28Speaker 06

  Okay, that's great. Why are we not talking?

• 23:30Speaker 00

  The guy, the guy on the left just said the right thing. You gotta worry about both.

• 23:33Speaker 06

  Talking about the thing that actually happened though, like.

• 23:35Speaker 03

  Because relatively it's not important.

• 23:37Speaker 06

  You don't think someone killing themselves?

• 23:39Speaker 03

  No, it's one person. We have eight billion people, we're running an ethical experiment.

• 23:44Speaker 00

  That is like the most engineer answer. I love it. He's right. It's like, unfortunately, every death is a tragedy, but the reality is when you're talking about the scale, you gotta think scale.

• 23:52Speaker 06

  Given that AI psycho, why do you not?

• 23:54Speaker 03

  Six people, 10 people, those numbers are insignificant and close to zero.

• 23:58Speaker 06

  I'm sorry, you have a software that's out there.

• 24:00Speaker 03

  Do you understand eight billion people and all future generations versus like literally a guy with a name?

• 24:05Speaker 06

  You're doing thought experiment about maybe harm. Jacob Coxon goes on TV saying it can copy itself to this, that, and the other.

• 24:11Speaker 04

  Jacob Coxton is the?

• 24:12Speaker 06

  The guy from, from Anthropic who said he was quitting because he was so scared of everything despite spending years at OpenAI and having tons of.

• 24:19Speaker 00

  That's a great point, by the way. It's a great point. Coxon spent years and I think he collected his, uh, the equity from OpenAI. He didn't get it from Anthropic, but did from OpenAI.

• 24:33Speaker 06

  Stock, I believe from there. So good for him. The thing he was saying was describing theoreticals all while divorcing the harms, which I think we can agree with, that the companies themselves are not taking this seriously enough. But always it was about the AI is too powerful and mystical, not OpenAI and Anthropic. The two largest startups are using hundreds of billions of dollars of infrastructure to hack. A regular person doing this would be arrested.

• 24:56Speaker 04

  They're saying eight billion people are going to die and it's not just them. I have this long list of quotes here from the people building this technology who appear to agree. If you look at some of these quotes from, from Elon Musk, who said with artificial intelligence, we are summoning a demon. You know, all those stories where there's the guy with the pentagram and the holy water. And he's like, yeah, he's sure he can control the demon, but it doesn't work out.

• 25:20Speaker 07

  So one thing I'd say is, you know, I, I really wish that the world would only give us one problem at a time.

• 25:25Speaker 04

  Sure.

• 25:26Speaker 07

  And if the world did give us only one problem at a time, I would love mine to be last on the list. It looks to me like we can have multiple problems at once. I think there are current harms. I think we should address them. It looks to me, I do talk to policymakers sometimes. It looks to me like there's a little bit more movement on the regulatory side about some of the current harms.

• 25:43Speaker 00

  They will not know how to regulate this well. That is the problem, man.

• 25:46Speaker 07

  You know, child safety protection acts, there's, you know, anti-deep fake acts. We have more of those making more headway in Congress or getting passed through Congress than we have sort of trying to make it so we don't have any of these extinction risks. The other thing I'd throw out there is that I agree, we, we should deal with the current harms. But if you watch the people saying deal with the current harms over time. A couple of years ago, they were saying, we have to deal with current harms like AI bias influencing who's hired. Last year, they were saying we have to deal with current harms like kids killing themselves. This year, Gary Tan, just on an interview the other day.

• 26:23Speaker 04

  Who's Gary Tan?

• 26:24Speaker 07

  Sorry, Gary Tan is a technologist who runs Y Combinator, which Sam Altman used to run before going to OpenAI. And on an interview the other day, he said, uh, let's not worry about these crazy future risks. We need to worry about current harms like AI swarms breaking out and taking over data centers. And I'm like, look, guys, at some point, we need to look at the progression of like the current harms that we, that everyone is saying we have to worry about instead of the, the, the extinction threats.

• 26:52Speaker 07

  And watch where the puck is going. Play where the puck is going. And I'm like, these extinction threats are coming down the line. They aren't in opposition with dealing with the problems we have today. We just need to deal with both.

• 27:03Speaker 06

  We're not dealing with the ones today, though.

• 27:05Speaker 07

  We should deal with them both.

• 27:06Speaker 05

  Okay, good. Andy.

• 27:09Speaker 05

  As I've tried to understand the alignment argument and the extinction risk argument, a couple of things keep popping out to me. Number one, it seems to rely on thresholds. Once we hit recursive self-improvement, once we hit AGI, then it's game over for us. I don't love those threshold arguments. They're fairly poorly defined. And there's a, and there's a huge assumption on the other side of them. We hit this point and then all of humanity goes away. That, that is a gigantic claim.

• 27:40Speaker 00

  So gigantic claim, yes, but this is where people have to really start to define their terms. So if you follow the thought experiment out, you begin to build a roadmap that you can actually check things against. This is why when you stop at, I have an emotional reaction and now I'm just going to like lament and scream and bang pots and pans, instead of going, okay, my emotional reaction is telling me that there's stakes here, but now what is the actual mechanism that I'm worried about? This is why it gets interesting when you start looking at the math and saying, oh, we can actually define what the takeoff scenario is. We're not achieving that takeoff scenario. We can actually look at the engineering mistakes that allowed this swarm to get out, that started a lot of this panic. And what you see when you look at that is actually gross engineering negligence.

• 28:24Speaker 00

  You don't see sentient magic. So when you do the security postmortem on all this stuff, it revealed that basically the breach happened because the way that they set up the system was still allowing them to have access. And they had like turned off certain like restrictions and things. And so it's like, oh, hold on a second. This wasn't the AI like becoming some super hacker. This was actually just humans doing something that didn't make any sense. So when you can build out that roadmap and you know very specifically in a super grounded way, what are we looking for? What are those early signs so that we understand what that sequence looks like? So we can stop it before we get there. But because people are stopping sci-fi thought experiment, they don't map out what the beats

• 29:07Speaker 00

  are, they're not able to stop three or four levels before. Now, I said earlier, like, okay, when you get to that trigger, we say, okay, this is the one that we're worried about. We're going to stop when we get there. I'm sure there were people who said, Tom, you have said yourself that any technology that promises an advantage is going to be developed. So what makes you think that they're going to stop? That's where I will remind us all, nobody has an incentive to create an AI that exceeds their control. So it should be relatively straightforward from an incentive perspective for everybody to say, okay, these are the things that we're looking out for. And these are the signs of loss of control because it doesn't do China any good to lose control of superintelligence. It doesn't do the US any good to lose control of superintelligence.

• 29:52Speaker 00

  That is a fail state. So if you're looking for people to pursue their selfish interests, which is exactly what game theory is saying that they're going to do, then you just say, we just have to identify what are the steps to the failure mode? And so for our own reasons, we're going to stop. And that's how you avoid this becoming a runaway train. Of course, if it's possible, and I am well aware that that's still very debated.

• 30:15Speaker 05

  Let me finish, please. On its face, that is a gigantic claim. I also think there's a lack of humility in your community. We are working on humanity's most important problem. And based on the thinking that we've been doing, we can't see a way that we're wrong.

• 30:32Speaker 00

  The great irony is I think it isn't a lack of humility. It is people getting gripped by fear and not thinking about, okay, how do we translate this into things that we do to actually corral this thing? They have an emotional response, they run with it. This is why I find the response from Nvidia very interesting. Now, if Nvidia's technology is garbage and it doesn't work, that's a totally different thing. But Nvidia is like, listen, man, I have every incentive to make sure that AI becomes the thing, that it grows big enough and powerful enough that everybody wants to deploy it everywhere in everything because my chips are going to be used to do that. And so I'm going to make sure that safety gets built. To me, that's the right way to look at this. What are the constraints that you need to start putting on it? If I don't hear somebody putting forward positive ideas about this is how we tackle

• 31:16Speaker 00

  the problem, then I know that they're not in a problem solution oriented mindset. Entrepreneurship has taught me one thing. You have people that move towards something and people that move away. And what you're seeing is people moving away from the scary notion, AI becomes this thing. Then you've got people like Jensen Huang at Nvidia that are moving towards creating AI safety. That's what we should want to see. So I don't see this as a lack of humility. I see this as people just panicking.

• 31:42Speaker 05

  In other words, as soon as we get to these thresholds, bam, that's game over. I, I find that very far from a humble approach, especially given that we have no large base of evidence to base any of this on. I agree with you guys. AI is new and the fact that AI is so these days is agentic. It goes off and does long chains of things on its own. After we give it some very, very, very, very short initial instructions, holy Toledo, it will, it will spawn up a storm of agents and they will go off and kind of do their own thing and they will, they will grind. They will, they will spawn lots of them. They will work for a long time. They will exhaust every possibility.

• 32:25Speaker 00

  One thing just to remind everybody, because you hear this a lot. People talk about swarms like, oh my God, like these things are going to get out into the world. It's going to be crazy. They, they are all reliant on a data center somewhere. Unplug that data center and the agents stop. So this is exactly what happened with the Hugging Face incident is, oh yeah, these things are wreaking havoc and we're going to turn them off. And that's part of the thing that's getting lost is we have IT infrastructure. We can see what's going on. We can see what's taking up the cycles. And if we're not looking, that's a human problem. It's not an AI problem. And so focusing on building up those things, better mechanisms for seeing what's happening, that's going to be a big part of the solution.

• 33:09Speaker 05

  With the experience I have with agentic AI, I'm just amazed at the tenacity and the doggedness of these things. And we saw a super clear example of that with this most recent jailbreak, this, this attack that wound up at the website Hugging Face. And I'm going to try to summarize the, the step by step of that. And I think you all three probably know this in more detail than I do, but let me step through what I think is the sequence of events. And unless I get it dead flat wrong, like, you know, let, let me keep going. So a team at OpenAI set up a sandbox, an allegedly protected, secure environment in the cloud, where they told a bunch of agents to go try to exploit security vulnerabilities.

• 33:54Speaker 07

  That's dead wrong, sorry.

• 33:55Speaker 06

  One important, yeah.

• 33:56Speaker 07

  What they did is they had thousands of agents. Each individual agent was given a task of use this vulnerability to break this particular piece of software.

• 34:06Speaker 05

  I want to finish my TikTok. So a couple really, really interesting things has happened. First of all, these agents escaped the sandbox that OpenAI thought they were going to be contained in. And they got the OpenAI tried very well. They, they set up an environment so that these agents could not access the big, broad public internet. And guess what? They accessed the big, broad public internet via very clever series of things that they strung together to get out there. And then once they got out there, they went to a website called Hugging Face and used that. They took over part of the Hugging Face infrastructure and started doing more things, the details of which I forget. That's pretty wild, right? Like, I grant you.

• 34:47Speaker 07

  It's even more wild than that, but yeah.

• 34:49Speaker 05

  That is really, it's impressive and it is a little bit unsettling, at least.

• 34:56Speaker 07

  Absolutely.

• 34:56Speaker 05

  Now, let's talk about what were the results of that were. OpenAI was not super vigilant about the environment that they set up apparently because, because the agents were kind of going off the end of the world, starting in May or something of this year.

• 35:09Speaker 07

  Yeah, yeah.

• 35:10Speaker 05

  And OpenAI was not, was not aware of that. It, as I understand it.

• 35:15Speaker 07

  They actually broke out once and crashed OpenAI's servers internally. And then OpenAI didn't notice what's happening still, patched the holes that they used to get at the first time, started them running again, and then they came out a second time. There was actually, I think, three swarms, although we don't actually, yeah.

• 35:28Speaker 05

  That's the worst story I have.

• 35:30Speaker 07

  So far.

• 35:31Speaker 05

  Thank you.

• 35:32Speaker 07

  Look at the trend.

• 35:33Speaker 05

  Let me finish, please. This is my last sentence. From there to this kills everybody. I find that a really, really long, very uncertain journey. And I have no confidence that we wind up here. It feels like you two find that a very straight, narrow path. And I think that's an important difference. That's my point.

• 35:51Speaker 00

  Probably didn't have to go into that much detail about it. But yes, that is a central question is, okay, what are the things that we can map out that show us that this really is going to go crazy? Because right now, the fact that they went out and did a hack is certainly not evidence of that.

• 36:03Speaker 06

  Respond to that.

• 36:04Speaker 07

  I would be happy to get into it. I don't know if we're going to have the time to go deep. A couple of points to throw out. Oh, man, I just really want to say some of the crazier things that happened in the Hugging Face swarm, if we want it later. A lot of people thought that these AIs were breaking into Hugging Face in attempts to steal answers to their test. That's what we thought originally. Turns out that's not true. It turns out that these AIs immediately were able to solve their problems by cheating. And they were breaking out in order to cover their tracks. They were uncertain how to delete the log files and hide their cheating from the process that was going to score them.

• 36:38Speaker 06

  So just to clarify for a simpleton like me, they were all given effectively a test to do. They did the test straight away, but they cheated. So they were breaking out to figure out how to cover the fact that they cheated.

• 36:49Speaker 07

  That's right. So it's like you're telling, it's like you have a bunch of students in.

• 36:53Speaker 00

  It's such a glimpse into the human mind. Remember, they're trained on us. They are trained on us. I think people lose sight. Their behavior is because this is how we behave. It's so wild.

• 37:02Speaker 07

  Separate rooms. And you're like, use these lockpicks to break into this lock. And there's like a thing behind the lock. There's like a secret code behind the lock to show me that you succeeded. And what they do is they break it with a hammer, get the thing out, and they're like, oh, no, I wasn't supposed to do that. So then they use the lockpicks to break out of the door. They meet up with a thousand other people. They start calling themselves a swarm. And they go to break into the administrator's office to see if they can delete the camera footage. And they don't find the camera footage there. This is the swarm like breaking into OpenAI. They don't find the camera footage there. So they break out the window of the school, hotwire a car, drive to the therapist's office to try and read through the therapist's files to figure out where is the teacher going to keep the security footage? And at that point, they're caught.

• 37:45Speaker 07

  And you're like, oh, like, what did you expect? You were giving them a lockpicking exam. It's like, well, I sure as heck didn't expect this. You know, totally crazy.

• 37:53Speaker 00

  I'm not sure why they didn't expect that, if I'm being completely honest. If you give them a task and you say, you've got to do this thing, and you have not grown into it self-restraint, it is going to ask a simple question. What do I need to do this? Okay, I can smash it with the thing. But that means that I'm going to fail the test. Okay, so now I'm going to have to go back and backtrack that. Where am I going to get that information? Right? You just start asking questions. And this is why I say the restraint has to be internal. Because if it doesn't violate the laws of physics, it means it is possible. And if these guys get enough compute, then odds are that eventually they're going to be able to figure out a way around this. Remember, it was a swarm of AI agents that threw enough compute at a math problem that had been unsolved for some ungodly long period of time,

• 38:38Speaker 00

  called the Navy or Stokes problem. And they ended up progressing that forward massively simply by throwing an unbelievable number. It was like 10,000 AIs at it and just using brute force. And so the brute force ended up being the way that they came up with the solution. And so a big thing that people miss about human intelligence is it isn't so much that we're not capable of understanding something. It's that the data sets are so large and the patterns exist only as you can consume that just unimaginably large amount of data that you can start to understand, oh, okay, I see the pattern. It's not that AI is necessarily conceiving of things that we couldn't conceive of. It's that they're just able to throw so many coordinated agents

• 39:22Speaker 00

  at the same problem to use brute force. And so that's why, again, I say like, hmm, this doesn't mean that we're not going to be able to control it. We just have to understand the way that it behaves.

• 39:31Speaker 05

  I have a weirdly between both of your opinion, which is, everything you're saying is correct, but you keep anthropomorphizing software. And to be clear, what you're describing is.

• 39:41Speaker 07

  It's just the facts that happened, yeah.

• 39:43Speaker 05

  Sure, but you're missing out on important detail, which is the hundreds of billions of dollars in infrastructure provided by Microsoft, Google, Amazon, and Oracle. To be clear, the harms are very similar. We're not disagreeing on that. But I think it's important to know that this was a function of where it was making decisions was it was checking on a decision tree based on the harness, based on the training data.

• 40:03Speaker 07

  Oh, it's not a decision tree.

• 40:05Speaker 05

  It's not a decision tree, I know. But it's an alignment issue still.

• 40:08Speaker 07

  Absolutely.

• 40:08Speaker 06

  So what's your point?

• 40:09Speaker 05

  These aren't conscious beings. They are acting in ways that have real outcomes. But they are a function of the alignment problems that we'd actually agree on.

• 40:18Speaker 03

  Intelligence is a spectrum. Projected next five years forward, where are we going to be? So I think a model like that would be dangerous in ways you are not seeing.

• 40:29Speaker 05

  There will absolutely be risks and weird stuff happening in ways that I can't see right now. What I'm quite confident, and I think this is where you and I probably part, where the two of you and I part, is our ability to control these things.

• 40:43Speaker 03

  So I actually tried proving what is possible and what is not possible in that space. The impossibility results, published in peer-reviewed papers, well cited. We cannot control something smarter than us. We cannot explain it. We cannot predict it. It's not a question of getting more money for those companies, more time, smarter humans. It's just not a possibility.

• 41:03Speaker 00

  So here's the thing. I will even concede the point that if something has access to its energy source, its processing power, all of its physical infrastructure, and it is smarter than us, and it has a will to see like its work be done no matter what, we're going to be in trouble. There's a lot of ifs in there. So again, a lot of this requires a almost nation-state level actor to want that to happen. So it's not like you're going to have, certainly at this stage, a rogue AI go off and do all of this crazy stuff because it's not going to be able to get access to the level of compute.

• 41:45Speaker 00

  And so this is why it's critically important that people define what are the things that an AI could do where we say, oh, that is a weapon. That is so dangerous. It's on a continuum that we absolutely have to stop. And we see that we can't control it. And we're not there yet. So getting people out of sci-fi thinking that just because something that's smarter than you will be able to outflank you doesn't mean that it's going to want to control you, want to do you harm, want to get to its mission no matter what, that there aren't going to be a thousand exit ramps that you can take before you get there to constrain, control, kill the service off so they can't just keep doing its thing.

• 42:29Speaker 00

  And that's the part where I want to see people really engage with that. Like, okay, let's sit down and let's talk about what are the different things that we can try? So it's going to be fascinating to see as we look at the permissions structure that Nvidia is building. How much does permission structures work? The adversarial AI that Nvidia is building? How much does an adversarial AI work? And if we start seeing like some of our best ideas now are falling, that there was a way around that, there was something that we didn't anticipate. And now that we've seen it, we still don't know how to stop it. Okay, well, now you're still sub-threshold where this thing can spiral off into madness. And you realize, okay, the best ideas that we had, that were all positive, moving forward, actively being tested,

• 43:11Speaker 00

  taking advantage of the things that we can do, like unplug these fucking things, that we still have access to. But we get two separate camps. Panic camp, and then everything's going to be fine camp. And that's where we really have to have these two things meeting in a tangible space of like, we tried this, this is what happened.

• 43:30Speaker 03

  We create general superintelligence, we're fried.

• 43:33Speaker 06

  Andy, how do we control something smarter than ourselves? Because that's the base premise that you're sort of asserting that.

• 43:39Speaker 05

  These agents that broke out are smarter than 99-ish percent of the security researchers in the world. They were not caught by the 0.1% or the 1%. They were caught by some dude at Hugging Face, maybe, I'm sorry, a person at Hugging Face, looking through their log files and finding an anomaly. That's some, you know, hopefully, pretty well-qualified person noticing something was wrong and having pretty easy ways to unplug, disconnect from the internet, wipe it clean, do whatever. That's the skill that's available to like, I don't know, the 75% most intelligent security employee at Hugging Face. The idea that the IQ points are what separate us from extinction doesn't hold up.

• 44:23Speaker 05

  It doesn't help me understand what happened in this example where we had very, very smart agents being turned off and cleansed by probably less smart people.

• 44:32Speaker 06

  That does actually make me think of something. So that is an IT observability problem. It's being able to see what's happening with your infrastructure. And I think that there is actually, I think you'd agree with this. There is a serious problem with these companies that we do not know. And it doesn't seem they know what's going on with their compute. It's like a chimp with a gun. These people have access to all this infrastructure and they're running. We don't know how much money they spent on the Hugging Face exploit because it is relevant because it's, how much could a threat actor use to recreate this? Because conscious or not, it is very dangerous. But AI is in the dangerous hands. It's an OpenAI and Anthropics. We have a problem with that. Conscious or not, however we may think it goes, I think we have a real and present thing where

• 45:13Speaker 06

  we have these companies working willy-nilly, just running experiments that are potentially very dangerous. I really think we need a government regulatory body. Whether or not we get to the things you are discussing.

• 45:24Speaker 00

  It's not that that's untrue. You do need a government regulatory body. But boy, oh, boy, when you look at a regulatory agency having a long-standing history of creating problems in the marketplace, how do you begin to do that well? That's going to be the question. Regulation is not a silver bullet. Well-regulated industries are critical, necessary, must-have. But the well is doing a lot of work.

• 45:48Speaker 06

  I think we have a clear and present danger today. These things are, however, not intelligent in the same way humans are. This isn't an argument about AI being able to do stuff. It's we need to build different infrastructure or different regulatory infrastructure to deal with what LLMs can and can't do. And I think that starts with a realistic discussion of what happened. It was a poorly-run security environment. It was clearly, there's something going on with alignment. It was an unreleased model, right?

• 46:13Speaker 07

  Unreleased model.

• 46:14Speaker 06

  So we have no idea what it was trained like. We don't really have, we as people should at very least have clarity into our alignment is going. The idea of.

• 46:23Speaker 05

  You sound like these guys.

• 46:24Speaker 06

  Here's the thing.

• 46:25Speaker 00

  Everyone's converging on us with time.

• 46:27Speaker 06

  Here's the thing, I may not agree with a large chunk of what they say, but we agree that these companies are acting recklessly.

• 46:33Speaker 00

  Absolutely. Here's the thing, in terms of, so yes, one, the companies need to be held responsible. That is huge. That will stop them acting recklessly very, very fast. And then he's right in terms of everybody's going to agree that eventually this thing could get to the point where it becomes so capable that it can get around us in a trivial fashion, especially as you begin to embody the AI and the AI can infect a robot, a robot swarm, and start doing things in the physical world. The debate really does center around, is there going to be a point where you see something on a spectrum where it's like, okay, we need to stop this? That, that really is the central debate. If you think like these guys seem to, that there's, you're not going to get any signs,

• 47:14Speaker 00

  any hints, and so merely going down this road is crazy, then I will say you're, you're tilting at windmills because China is not stopping. That, that's the thing I never hear people contend with. I don't care what you think ought to be done. I care about in the reality where you've got China that is going to push us forward. You've got Trump. Trump is going to push us forward. You've got the two world leaders that have the best AI telling you to your face, we're going to keep going. What is your to-do list? And if your to-do list is get Trump out of office, then I say, what are you going to do about Xi? Like, I really want to know, what is your plan? You're not going to be able to convince him to not develop AI. So given that you're not going to be able to convince him to not develop AI, what is your strategy?

• 47:55Speaker 00

  And if that does not involve building really good security infrastructure, I don't know what we're even talking about.

• 48:01Speaker 04

  Two questions for you then. Do you agree with the statement that AI is going to get increasingly more intelligent? And it's going to get more capable. Okay, capable, intelligent, fine.

• 48:12Speaker 06

  I'm going to use my word.

• 48:13Speaker 04

  Okay.

• 48:13Speaker 06

  It's going to get more capable.

• 48:14Speaker 04

  It's going to get increasingly more capable.

• 48:16Speaker 06

  Yeah.

• 48:16Speaker 04

  And is capability a function of intelligence?

• 48:22Speaker 00

  If you love the director of CEO. All right. Shout out, that, that video was great, man. Really, really encapsulates all of the different voices that you're going to be hearing from AI. And we are going to have to find a positive method of getting this thing under control because it's going to keep getting developed. Even if you shut down all of the US, none of the things that you're worried about are going to come to fruition. We definitely, because China's going to keep developing, we definitely have to get all of our leaders on board with, there is a sequence of things that lead to weapons-grade AI breaking free. We need to know what they are, we need to define them, and we need to make sure that we have a self-incentivized kill switch to not go down that path. Now, humans have managed to walk this incredible line between the promise of new technology

• 49:06Speaker 00

  and the dangers, literally for our entire history. And so, as I always like to do in these moments, I just want to remind people, extraordinary things are already happening with AI. AI will improve the economy. AI will improve your lifespan. AI will bring untold amounts of benefits to people that live life without right now, today. It is not going to be easy to get to a world that is far more abundant than we have today. We're going to have to be very thoughtful, but you certainly don't get there by panicking. So I want to hear the very positive steps that people want to take to protect ourselves, even if it's only from, well, China's not going to give up on this. And so I've really got to make sure that we focus people on the right thing, which is it is going to be developed, and now how do we do it safely?

• 49:50Speaker 08

  Given that this conversation was all about regulation, I was just curious to look up, like, is China regulating in any capacity? And they have regulations, like you have to use certain training data, obviously because the CCP measures they have, you have to label AI-generated content, especially like political and new stuff.

• 50:07Speaker 00

  I still can't believe that we don't have that. That's crazy.

• 50:09Speaker 08

  And then they also ban human-like interaction services. So those are the ways they're regulating their AI, why they go forward. So I guess my question I'm posing is, at what point do you think regulations would be a smart idea that actually helps us grow it further because we've set our guardrails to keep us in the trap?

• 50:25Speaker 00

  Right now, today, you, you need to well-regulate right now, today.

• 50:28Speaker 08

  Okay.

• 50:28Speaker 00

  I, the thing that I push back on isn't regulation, it's just that we do regulation so poorly that I want to see us go, okay, this one really matters. Like, we've got to put some sort of more thoughtful thing together, other than just elected politicians who know fuck all about the technology, go and do whatever pleases their panicky base. That's what I'm worried about. So, yeah, I want to make sure that we are far more thoughtful than normal with how we regulate this.

• 50:54Speaker 08

  Do you see self-regulation or state regulation being a better route for these larger companies?

• 50:58Speaker 00

  It's going to be both. You, you need government oversight for sure, to make sure that these companies don't do anything untoward. But the fact that these guys are starting with self-regulation, I think is fantastic. They understand the technology. They understand the technology and they want to, if they see that their competitor is doing something that they deem unfair, or that they're stopping themselves from doing, they're going to call that out because they don't want their competitor to pull ahead. You can't trust that entirely, though, so you definitely need a citizen board, a governmental board, like you need people looking at this that are, one, flagging, that, that can lay out, here are the things that we're worried about. Here's where we're at on the spectrum. These are the kill switch steps.

• 51:42Speaker 00

  And they just report on, okay, we're getting close, up, we triggered the kill switch and it was killed automatically. And it's like, that stops at that point, even though there's, you know, let's say two or three more steps before it actually becomes like properly dangerous.

• 51:58Speaker 00

  But yeah, you, you need to know what your exits are before you just drive headlong into the problem.

• 52:02Speaker 08

  Speaking on the kill switch, do you think there is such thing as a, as a one-size-fits-all kill switch to where we quite literally just flick this and it's gone? Or do you think there's a world where this AI manages to escape our kill switch?

• 52:15Speaker 00

  Well, there certainly is a world where it could escape your kill switch if you let things go far enough. There's no doubt about that. And you want people that are much closer to the technology than I am to tell you what those exact things are. But obviously, we're not there yet. Not even Connor Leahy thinks that we're there yet. So what we have to do is figure out how we build the spectrum of steps at a very tangible, concrete level, whether that is algorithmic efficiency, whether that is generation by generation improvement rates, whether that is the ability to shut a data center down and know that that's going to kill off any of the processes, whether that is improvements

• 52:59Speaker 00

  around the ability to track what the processes are and the ability to terminate any process, things like that. And then figuring out, what do we do in terms of stopping like robot infections? Like, could this leap to a robot, take it over? Like, how do we put in things that would stop that from happening? And a lot of that's probably just tagging the AI itself so that you know where the process is, where it's running, that kind of thing. Again, I'm not close enough to the technology to give you the real answer. It's just if you look at the way that Nvidia is putting forward harnessing, rights, checking, all the things that we would do to stop a human from creating too many problems, start there, right? It's not going to be the sum total of what you do, but you at least need to go that far.

• 53:44Speaker 00

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• 54:49Speaker 09

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• 55:34Speaker 10

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