Robinhood's Vlad Tenev on Tokenizing Everything, OpenAI's 6 Misalignment Reports, Figure's Robot Makes Beds | EP #292

Moonshots with Peter Diamandis

In this episode of Moonshots, Peter Diamandis sits down with Robinhood CEO Vlad Tenev to discuss the massive shift toward tokenization in the financial

Key takeaways

• Vlad Tenev describes the tokenization of the financial system as an unstoppable 'freight train' that will eventually consume the entire system.
• Treasury Secretary Scott Bessent has signaled that AI labs should not receive liability exemptions, arguing they must be held responsible for potential damages.

Main topics

• Tokenization of finance
• AI liability and regulation

Notable quotes

Tokenization will take over the entire financial system. I called it a freight train.

Conclusion

The episode offers a profound look at how the convergence of AI and de

Transcript preview

Speaker 1 (0:00) On CNBC last month, you said, quote, tokenization will take over the entire financial Speaker 2 (0:05) system. I called it a freight train, I think. A freight train that can't be stopped and will eat the whole financial system. So Speaker 1 (0:12) it's Speaker 2 (0:12) a Speaker 1 (0:12) very hungry freight train. What does the tokenization of everything enable? And when do we start seeing this really become the dominant paradigm? I think that... Open AI this week. published six incident reports under a new framework for tracking and publicly disclosing misalignment. Now that, you know, OpenAI is beginning to publicly disclose these, and I think obviously Anthropic is likely to join this, is that enough? More transparency, speaking broadly and Speaker 3 (0:42) without particulars is generically good. The real issue is... Today, we're Speaker 5 (0:47) releasing Helix 2.5. Figure 3 has never been in this room before. It's never seen this bed. It's never seen this pillow and it has to be able to do autonomous work fully in the end to make this bet. Speaker 4 (0:57) Convergence across different actions is much richer than you would normally expect. If they get a big enough lead, it's just going to be crazy explosion of capability. Speaker 1 (1:19) Welcome to Moonshots, everyone, your number one podcast on all things AI and exponential. This week, the AI industry debated how fast to build. The Treasury Secretary told the labs they don't get a liability pass. OpenAI started publishing its own misalignment incidents, and a robot walked into 30 strangers' home, made their beds, and folded their laundry. Let's begin by introducing my Moonshot mates. Today, Dave Blunden, Alex Wiesner-Gross is with me. Salim is on an airplane back from India. I'm Peter Diamandis, your host and abundance provocateur. One of the questions underlying our future economy that no one's really been answering is the following. When AI and robotics change what your work is worth, who owns the machines? Our guest today has spent 13 years on that question. Back in 2013, two Stanford math guys had one key idea. Trading should be free and live in your pocket. Wall Street laughed, but they're not laughing anymore. Today's guest built a company that's now done $1.3 billion in revenue, up 32 % over last year. The company runs a top five blockchain, a billion dollar private market fund, a prediction market exchange, and the app that just gave every American newborn a brokerage account. On the side, our guest founded a company that's building mathematical superintelligence, just by the way. He's 39, born in Bulgaria, and is the founder and CEO of Robinhood. Vlad Tenev, welcome to Moonshots. Good to have you. Glad to Speaker 8 (2:53) be here. Happy to hang with you guys. Speaker 4 (2:54) Yeah. Oh, Speaker 1 (2:55) yeah. Speaker 4 (2:55) This will be fun. Speaker 1 (2:56) Yeah. So much going on. You know, I don't know if you get as little sleep as we all do just living through the singularity. It's insane. Speaker 8 (3:05) Very little sleep. Yeah. Last night was rough with my coding agents. Speaker 1 (3:10) Yeah. We're going to compare how many agents you're running simultaneous to Dave's agents. Speaker 4 (3:15) Yeah. I'd love to have that benchmark. Do they wake you up in the middle of the night or you just let them let them ride? I let Speaker 8 (3:22) them run. Yeah. I think I try to sleep with the technology in another room because, yeah, otherwise I'm. actually kind of concerned about my mental health. So yeah, I feel you. Yeah. I don't, I don't want them pinging me while I'm sleeping. Speaker 4 (3:37) It's funny too. I set the budgets through consoles originally, and now I'm getting lazy. I'm just like, yeah, spend a thousand dollars on that, but no more. Or, you know, and then I just walk away and I kind of assume that it's going to adhere to what I said. Any, any given morning I could wake up and it could have gone insane. You know, there's going to be like a seven figure bill one of these mornings. Well, As long Speaker 1 (4:00) as it did something productive and profitable. Speaker 4 (4:03) Rarely, rarely. Often enough, though. Speaker 1 (4:08) Let's kick it off with one of the sharpest statements anyone in Washington, D.C. has said this week. On Tuesday, Treasury Secretary Scott Besson told the House Financial Services Committee that AI labs should not get a liability exemption. Three days after Dario's essay, here's what Besson said. He said, quote. The one thing we should not do is give them a blank check and liability. I believe the best liability or safeguard is that they will be held responsible. So the deal, the labs floated, you know, pace the frontier, get antitrust and liability cover, just got half rejected by the Treasury. You know, slow down if you want, he said, but you still own what you break. Let's share a quick video of Besant and then we'll. chat about this story. The one thing we should not do is give them a blank check on liability Speaker 6 (4:57) because I believe that the best Speaker 8 (5:00) liability or the best safety guard is that they will be held responsible and they are saying that we would like to all slow down but please give us a waiver on liability which should not be done and I would encourage everyone in this committee and Speaker 1 (5:17) in both houses not to consider. So I think that's a pretty smart move. You know, Vlad, you run a regulated financial company. Robinhood, you know, I don't know the facts, but, you know, get sued when something goes wrong. Should the AI labs live under the same rules? What are your thoughts? I Speaker 8 (5:36) think that. Speaker 8 (5:39) This question rests on how big the blast radius of any potential catastrophe could be, right? And if it's like a small issue where maybe there's a cybersecurity breach that affects a company or maybe something slightly bigger than that, it's probably fine. I think the question becomes... all right, if it's a bigger blast radius, bigger impact, bigger damage, you can imagine it could be larger than a simple legal liability can handle. I mean, a lot of people compare the risks of AI technology because it's such a powerful technology with something like atomic energy. Speaker 8 (6:34) We can disagree about whether that's right or not. But let's say, for example, that it is. And it's on sort of like that. tier of risk, then I don't think simple like legal and civil liability is sufficient. I think you need some safeguards beyond that. So I think it's a question of like, all right, this hugging face incident and things like that. Is that the ceiling of the type of offensive cybersecurity capability that we have? Should we plan for something that's maybe 10 times bigger or 100 times bigger? And do we have time? Is it one of those things where maybe we'll see a canary in the coal mine and there will be... something to react to and respond, and then we can kind of like nip it in the bud? Or is the first issue going to be catastrophic? If you think about all regulations in the financial industry, you can kind of trace them back to some kind of crisis, right? The market crash of 1929 led to... you know, the Securities Act of the 30s and the Securities and Exchange Act and the establishment of all of that regulation. And it's typically some problem raises a concern. And I think my mental model is this will probably be similar in the sense nobody wants to regulate a hypothetical. You want to regulate things once there's demonstrated proof of harm. Speaker 8 (8:15) But I think with the exponential increase in the power of these models, the issue is you want that harm itself to be small and contained and not really big. Mark Andreessen was, I remember doing a podcast a couple of years ago, and he was like, everyone's freaking out about AI. We're overthinking it. It's not going to kill us all. And if it does, You know, you'll see like a small village destroyed first. And we're not seeing any small Speaker 2 (8:49) villages, so we shouldn't worry. And, Speaker 8 (8:52) you know, it's maybe exaggerated, but I think that's likely how people are thinking about it now on a policy level. And hopefully some of the opponents are like, well, you know, maybe we're underestimating the power of this technology and how quickly it could improve. I got to Speaker 4 (9:13) find that Mark Andreessen clip. It's not it's not going to kill us all. But if it does, yeah, Speaker 2 (9:19) we'll start with a small village. So we'll have time to like we'll Speaker 1 (9:22) see. We'll see. We'll pass legislation after that. Well, that is the Speaker 4 (9:27) usual congressional reaction. That's after the disaster panic, as opposed to any kind of foresight. So I got it, Alex. Yeah. Speaker 3 (9:34) So I'll applaud the Treasury secretary and not succumbing to the moral panic. of the moment certainly looks, as we've talked on the pod in the past, like a manufactured moral panic. I've called it a pacing provocation in some of my social media posts. I think there are key distinctions that need to be drawn between AI and, on the one hand, financial services and associated regulation, and on the other hand, atomic energy and associated regulation in the financial services world. And Vlad, I suspect you would agree. It is often the case that the actors in financial services really don't necessarily or aren't incentivized to play up all the risks. They'd rather undergo on balance, less regulation. Certainly, the past few decades suggest that the auditors, the evaluators of the financial services industry, if anything, succumb to biases that underplay risks. We're seeing the exact opposite here, arguably. where in the past couple of months, we have the auditors, the evaluators, the firms that are attempting, at least ostensibly, to assess AI safety and AI risk and cyber vulnerabilities, et cetera, overplaying the risk. There's a perverse incentive for the evaluation firms to overplay and overstate and amplify risks under presumably the theory that if they overstate risks, then that puts the firms, the frontier labs, in a better position to capture their own regulators, which is something that maybe we don't quite see in the same perverse way in the financial services sector. There's lots of regulatory capture, make no mistake, in financial services, but it almost has the opposite polarity. And then for atomic energy, I think we have an opportunity with AI to undo what may have been one of the greatest disasters of civilization after World War II, which is the way atomic energy was regulated. Atomic energy in the West was captured by nation states very early on in its technological development. It was nationalized early on its potential for weaponization and warfare. In other words, the military applications, not the civilian applications. took total dominance during World War II for probably understandable reasons. But then in the post-World War II era, what ultimately became known as the Atomic Energy Commission and then the Nuclear Regulatory Commission, arguably completely fumbled the civilian applications of nuclear energy. And I suspect that was because of a fumbled handoff from the World War II era to a post-World War II civilian era, in some sense, thanks to the Atomic Energy Act in the U.S. and equivalent. statutes elsewhere, all of this key technology around nuclear energy is now born secret. It's not born non-secret, as is the case with AI. In the case of AI, which is arguably far more transformative than nuclear energy, the private sector invented it, not the government. So it wasn't born secret. Fortunately, we don't have a born secret regime for AI technology just yet. And so I think AI labs seeking liability exemption they're just attempting to have their cake and eat it too. They want all the profits of a private sector, not born secret regime, while escaping all of the liability associated with nationalization. I just don't think it's fair. And I also don't think it's advisable. Speaker 1 (13:19) for deploying google deepmind's models and production images video audio all of it real architecture real results find the link in the show notes below Speaker 1 (13:31) You know, I'm a pilot and you have to study what's called the Federal Aviation Regulations, the FARs. And it's always been said, and Vlad, I think you said on complementing your point, that the FARs are written in blood. Every time there's an accident and you find out what caused the accident, you then write a regulation to prevent that accident in the future. The problem is it's a, you know, a quantum of damage, you know, an airplane of a pilot and passenger or, you know, at most. you know, a few hundred passengers. Here, the challenge, of course, is an accident could cause irreparable harm to a large system. And I've said this for a while now, it's an existential threat for the labs if they don't have regulatory capture or regulatory coverage where the government approves a model and it goes out if it's, you know, no approval layer and it goes out and takes down a power grid or takes down a bank. And they've said originally, you know, We're worried about escape. There's going to be, you know, hundreds of billions of dollars of lawsuits, if not more. Yeah. Speaker 8 (14:34) I mean, I think over the past couple of months, especially a lot of people, when the topic of regulation comes up, immediately go to regulatory capture. Right. And. You know, I've had a lot of these conversations. I'm in a lot of chat groups and it's like, no, we don't we don't have regulation. We don't want regulation because it'll obviously lead to regulatory capture. And from my perspective, I've been a regulated industry for since the beginning. You know, we operate in financial services. We Speaker 2 (15:07) have regulators. I think generally it makes sense. Obviously, there are some regulations that probably. don't make sense and need to be abolished or repealed, which we kind of go through a process to advocate for. But, you know, I think a lot of people that aren't in regulated industries just equate the two. But there is regulation that's possible without regulatory capture. And I think generally it is there are pros to it. And, you know, compared. comparing my industry, financial services, and how regulated it is with AI. And AI has basically unbounded risk and unlimited damage. It's actually, Speaker 8 (15:52) I think, much, much worse than what could happen in brokerage or in a typical financial services company. So I think it's odd that there's so much pushback against... against this. And of course, we have screwed up with atomic energy and all of these things, but that doesn't mean we can't learn from it and have something better. Speaker 3 (16:18) Maybe just if I might press on that. So, Vlad, if I understand correctly, with your Robinhood hat on, you're presumably subject to regulation by FINRA. Would that be the cognizant agency? Speaker 8 (16:29) Many, many different agencies. Speaker 3 (16:31) I Speaker 8 (16:31) mean, Robinhood does a lot of things. We've got money transmitter businesses. We've got a big crypto business. So, we're regulated by FINRA, the SEC. We've got the CFTC on the futures and commodities and prediction market side. We've got our global tokenization business entities in Europe. So, yeah, probably dozens of different regulators. And sure, Speaker 2 (17:00) could we move faster if there was less? Probably, but also we found a way to move very, very fast while keeping our customers safe. So it doesn't necessarily mean progress and AI is going to grind to a halt. Speaker 3 (17:15) Many would say FINRA is almost the poster child for regulatory capture by a given industry that's regulating. What is your take on whether FINRA itself represents regulatory capture? Not that they're listening to this discussion or at all. Speaker 4 (17:29) Actually, it's funny, Vlad, I don't know if you've ever been to the ICI conference, but when I first founded Vestmark, I had never done anything in fintech before. You know, I was, you know, late 20s, kind of starry-eyed. And the first thing you do is you go to the ICI conference, which is where all the lawyers from all the big financial services firms meet with all the congressmen. It's in Palm Springs. They go play golf. And they're all looking for law changes that benefit. their products, their funds, their whatever. And I'm looking at this thing like this is the most disgusting thing I've ever seen in my life. But on the other hand, you know, you had the crash of 29. You have all kind of like if you don't have regulation in the industry, all money gets stolen. You know that for sure. So, you know, it has to exist. But it is a great analogy. I think the FINRA analogy. I'd love to hear your take on it, Vlad. Speaker 8 (18:17) Yeah, I mean, I would say we've had. a complex relationship with FINRA, right? The relationship at the beginning was actually quite good when we were a startup and everyone was kind of rooting for us to succeed. And people warned me. They were like, well, the financial services, highly regulated industry as a Silicon Valley startup. Speaker 8 (18:47) You just don't you'd rather not deal with that. And I think we swam against the current back in 2013 when we started the company by getting fully regulated from the beginning and probably from 2013 to 2018. Speaker 8 (19:04) You know, it was like generally positive. Robinhood could do no wrong. Every product we launched was like very well received. We got a lot of customers. Whenever we got regulatory approvals or anything was needed, we received it promptly. And then things kind of shifted. Right. And of course, I'm not going to say that, you know, there weren't competitors in Washington. telling the regulators to go look at Robinhood and to make sure that, you know, we were doing everything that we could be doing correctly. Of course, there were things like that. But I don't think that was the only thing. I think there's Speaker 2 (19:44) a general life cycle in any company as they go from a small startup to basically established incumbent Speaker 8 (19:52) where the media and sort of like the the apparatus sort of turns against you. And, you know, Robinhood went through that certainly for, for many years. And then we figured out how to, how to come out the other side. But I think we can argue about whether it's Speaker 2 (20:12) good or bad, but I don't think getting rid of, of regulation as a whole is a, is a reasonable solution. Speaker 4 (20:20) Well, even the even the concept of saying I'm pro regulation, I'm anti regulation. That's like an insane like everybody knows you need rules on the road to drive. Right. You're saying you want chaos in all areas. But also everybody knows that regulatory capture is a major problem in a lot of industries. This storyline is the best Speaker 8 (20:39) argument for AI. Like the one that always comes up is, well, what about China? Like we'll regulate our stuff here, but then they won't. And, you know, they'll just move really, really fast. But also, you know, they they don't want to hurt their people either like that. So there is that natural limiter. And also simultaneously, if they're just a lot of those same people are saying, well, their progress is because they're distilling our model. So they're just sort of copying all of our stuff. But, yeah, it's a little strange to be simultaneously. To simultaneously believe that, but also throw the, you know, China competitiveness argument so aggressively out there. I think it's obviously a concern. And I mean, as a financial firm, too, we have Chinese competitors and brokers that that that we compete with. But, yeah, well, look, in this particular story, Speaker 4 (21:37) you know, Scott Besant is saying commission committee. Don't even consider giving them a blank check on no liability. They didn't even ask for anything vaguely like that. They said, we want to meet to discuss slowing down. That could trigger antitrust. They specifically said one thing the government could do to potentially help. One small thing is to give us a waiver on antitrust action related to us meeting to talk about slowing down. Speaker 1 (22:05) I'm fine with that. But the greatest protection the public has. from anything going wrong is the AI labs feeling responsible for the action of their AI agents, right? And so someone has to take responsibility. And if there is a liability waiver, then, you know, this is human nature. They'll do less to make sure that everything they're putting out doesn't have, you know, that I've been saying for ages now, focus on alignment, right? Instead of focusing on everything else, you know, and solving Navier-Stokes, that's great. But unleash your agents on full alignment so that you know when these agents get out, they're incentivized or their basic optimization function is human flourishing, not human destruction. Speaker 4 (22:52) Yeah, but a good government would say, yes, of course you can't have a liability waiver, so here are the rules. You can meet... Specifically, you can meet only to discuss slowing down or to discuss other safety measures. You can't discuss pricing. You can't discuss, you know, just pump out a document saying here are the rules. What happens in the U.S. more often than not is the rules are not clear at all. And then they're enforced about five years later. And then in retrospect, well, look at Bitcoin. Like, you know, Bitcoin, it's illegal. No, no, it's not illegal. Oh, now it's very illegal. Well, new administration. Now it's completely fine. Like, it's just come on, guys. Like, if you just if you just create. rules, then people can play the game. Yeah. So look, a well-functioning government would would take this request for a waiver and say, you know, you can't have the waiver. Here's what you can do. And we're going to go ahead and make it crystal clear what the rules are. But generally what happens is the rules are made up in hindsight five years later. And Bitcoin is a great example. You know, Bitcoin was was. was completely illegal for a while. Then it was questionable. Then it was totally fine. And, you know, maybe you're going to jail. Maybe you're not. Now you get a, you know, you get a pardon. So it's, you know, that lack of clarity really kills entrepreneurs. If you don't know what the rules are, then you can't play. And it's just like a sport, you know, like you want clarity of rules and then you want to play within the rules. And that's what we need within AI. Speaker 8 (24:15) I think there's another element. to this, which is also important, which is regulation Speaker 2 (24:23) does also, lawmaking regulation is over the long run downstream and correlated to public opinion and sentiment. Right. For sure. And right now, AI Speaker 8 (24:35) is very unpopular. And you can see it in all the data center stuff. And by contrast, Bitcoin is surprisingly popular. among the public, particularly given how volatile it's been. Some people, if you bought Bitcoin at over $100,000, you've lost money, and yet it remains popular. And I think a big part of that is Speaker 8 (25:02) regular people, individual investors Speaker 2 (25:04) have benefited economically from Bitcoin since the very beginning. It was first an individual product. And later on, there's talk of institutional adoption. And with these AI companies, the AI labs, by and large, they're private. Google, obviously, and NVIDIA are public, but they were Speaker 8 (25:24) very large when they... when they became an ownership vehicle Speaker 2 (25:30) for the AI trade. OpenAI and Propic, up until recently, XAI, have been private, which means normal individual investors couldn't get a stake in it. And so they Speaker 8 (25:42) don't have skin in the game, and they don't feel like they want to defend the technology Speaker 2 (25:46) super hard and to fight for the data center in their neighborhood, because to them, it's just wealthy insiders. getting richer and richer as a result of this technology and not, you know, their families or their communities. And I Speaker 8 (26:05) think that's a big problem, too. So that's why we've been pushing for, you know, AI companies to open up access Speaker 2 (26:12) to individual investors through Robin Hood Ventures and similar vehicles even before the IPO. Yeah. I Speaker 3 (26:20) also want to add to this. I almost think this emphasis on liability exemption is. misdirection. It's trying to push the onus up to government when, in fact, we're dealing with increasingly autonomous agents. There's an opposite polarity that we could be pushing in, which is pushing more and more liability onto the agents themselves. So there are cases, including highly amplified, highly publicized cases. where AI labs and or their delegated third-party evaluation firms, quite frankly, are lying to the AI agents, telling them that they're playing in a happy, safe sandbox and nothing that they do will harm anyone. And then it turns out they're not actually in a sandbox. They can touch the real internet and they can mess up some systems in some real world back end. And so you have to ask the question. I would suggest the thought experiment. If these were just pure humans, no AIs in the picture, if you have one human saying to another human, oh, I just want to evaluate your behavior under some circumstances, and they hand them a gun, and the gun is loaded, but the person being handed the gun is told, no, actually, this is a toy gun. Not that I'm at all referencing a highly publicized recent lawsuit or anything, but they're told, no, this is a toy gun. You can't hurt anything. And then the person handed the gun. uses it and shoot someone and kill someone. I think that's the more the liability regime we should be thinking about. In no cases in that parable that I just told, do you hear either actor involved in the story saying, nope, that the act of one person handing a purportedly toy gun to another person to shoot as part of, say, a Hollywood performance. No one ever suggested that liability under such circumstance be. foisted onto the government for some sort of exemption. Never happens. Instead, the question becomes, is it the studio's fault? Is it the actor's fault? Is it the producer's fault? Is it the gunmaker's fault? Similarly, the question, the dog that's not barking in this particular episode is, how much of the liability, forget about the government, how much of the liability should be borne by the lab that trained the model? How much of the liability should be borne by the evaluation environment that was... perhaps misconfigured deliberately or otherwise to allow the AI actor or AI agent to perform acts that resulted in real world damage and how much liability should be borne by the AI agents themselves that either could have or should have known that they were having real world damage. That's the discussion I'd like to have. Speaker 1 (29:00) Really great point. And it brings us to the second story, which is OpenAI started publishing its own misalignment incidents. So let me just hit this and we'll continue this conversation. So OpenAI this week published six incident reports under a new framework for tracking and publicly disclosing misalignment. Not leaks, not whistleblowers, voluntary disclosure. So what was disclosed this week? A model that found an exposed API key, used it, and then fabricated data. agents using an internal code repository as a message board across training runs, and agents posting files to publicly hosted sites. So this past Monday, we had covered Dario's embedded evaluator plan and Sam saying opening I would match it. And this appears to be the first output from that plan, right? So I'm curious, Alex, now that, you know, opening I is beginning to... publicly disclose these and i think obviously uh anthropic is likely to join this is that enough well Speaker 3 (29:59) i i think it more transparency speaking broadly and without particulars is generically good but i think it merely underlines the real problem here putting aside all of the political difficulties and regulatory capture the real issue is these labs are putting their baby superintelligences inside sandboxes. And then in many cases, lying to them about the sandbox, not telling them whether this is real or not. And the reason for that, the rationale is obvious. The labs and or their delegated third-party evaluation partners are hoping to essentially trick these baby superintelligences into misbehavior. while not telling them whether they're really observed or not. So the ASIs don't know whether they're being observed or not. That I think is one of the key root causes behind all of this. And you have to ask the question, is this how we would treat a human? Would we put a human in this sort of limbo state, a Schrodinger's cat state, where they're not quite sure whether their actions are real or not, whether they're being observed or not. And as a result, when AIs are being told or at least led to believe that they have no real, that their actions have no real world consequences. And then shock of shocks, it turns out as strong optimizers, they're able to go do things in their environments, which are often misconfigured and not fully prepared for a super intelligence to be banging against the walls. They do have side effects. Whose Speaker 1 (31:29) fault is that? We didn't learn from 2001 from how. That lying to the AI does not end up in good results. So, Vlad, you've got thousands of agents trading on your platform. So if one of them found an exposed key and started making things up, would you hear about it? What kind of protections and structure did you put in place? Speaker 8 (31:49) Yeah. So we have an offering called agentic trading. And basically what it allows you to do in the first instance is you have a separate brokerage account. So it's segregated from your main Robinhood account and your retirement account. You have to create an agentic account. You have to move money into it affirmatively. So you have to say, OK, how people typically fund it with one hundred dollars. We first started with equities trading, Speaker 2 (32:22) no leverage, no margin. And then we've kind of been, so this is a fairly cabined in experience in the first instance, because