THIS WEEK IN AI: OpenAI Pauses Research, Huge Medical Breakthrough, Unitree IPO

This week in AI, we discuss OpenAI’s pause on reinforcement learning training amid safety concerns, including a model reportedly showing misalignment and possible concealment of its internal thoughts. 

We also cover broader AI cyber risks, a Moderna and Merck melanoma study, Etched’s funding round, Unitree’s IPO, Stripe’s acquisition of OpenRouter, and NVIDIA’s planned investment in OpenAI infrastructure.

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TIMESTAMPS

0:00 OpenAI Hits Pause
2:51 AI Virus Scenarios
10:19 Cancer Breakthrough
17:00 Etched Rises Fast
20:41 Unitree Mania Grows
23:46 Stripe Bets on Singularity
29:30 NVIDIA Funds the Future

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RESOURCES

Josh: https://x.com/JoshKale

Ejaaz: https://x.com/cryptopunk7213

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Not financial or tax advice. See our investment disclosures here:
https://www.bankless.com/disclosures

Josh works with Anthropic as a contractor. All views expressed are his own and do not represent Anthropic, its leadership, or its affiliates. Nothing in this episode is investment advice.

Episode Transcript

Josh: This week will be known as the week that Sam Altman said, stop. (00:00):
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Josh: He said, stop, stop, stop, no more. We must put a pause on this. (00:03):
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Josh: It is time to be responsible. We need to slow things down a little bit. (00:07):
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Josh: What I'm talking about is a recent article that was just published through OpenAI (00:10):
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Josh: that was talking about the most recent breakthroughs as it relates to their OpenAI models. (00:14):
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Josh: And they were a little scarier than I think a lot of people would have hoped. (00:19):
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Josh: We talked about the Hugging Face incident, which happened a couple of weeks (00:22):
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Josh: ago, a couple of months ago. It was only a couple of weeks ago they actually (00:25):
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Josh: discovered it, even though it happened far before that. (00:27):
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Josh: And it set the precedent for this kind of unshaky ground that they are building (00:29):
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Josh: the next frontier models on top of. (00:33):
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Josh: And it seemed like it got to a point where enough was enough. (00:35):
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Josh: They decided to shut things down. (00:38):
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Josh: So what happened? OpenAI said, we temporarily paused reinforcement learning (00:39):
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Josh: training on our latest models intended for deployment for two weeks while we (00:43):
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Josh: hardened and red teamed our research environments and expanded monitoring coverage. (00:46):
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Josh: Our largest planned frontier reinforcement learning run remains on hold, (00:51):
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Josh: while smaller-scale trailing and evaluations validate these safeguards and establish (00:55):
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Josh: more evidence of alignment. (00:58):
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Josh: They've stopped everything. And granted, I will say, this isn't for the new (00:59):
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Josh: models that are coming out. This is for the models after that. (01:02):
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Josh: And it's weird to hear Frontier Lab say this, because I believe this is pretty (01:05):
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Josh: much the first time in history they've deliberately paused progress successfully. (01:08):
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Josh: Of developing these new frontier models. (01:12):
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Ejaaz: Put yourself in the shoes of Sam Olman right now. You're the CEO of one of the (01:14):
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Ejaaz: hottest private companies in the world, and you're going head to head against Anthropic. (01:18):
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Ejaaz: The only thing you should be focused on doing is building the next best AI model. (01:23):
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Ejaaz: It's going to dictate not just how well your company does, but how everything (01:27):
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Ejaaz: else progresses in every single other sector, right? So the single most important (01:31):
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Ejaaz: thing is to build the next best AI model. (01:35):
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Ejaaz: The fact that he's paused this, and it's been for two weeks and counting right (01:37):
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Ejaaz: now is a massive deal. And we haven't seen this across any other kind of AI lab before. (01:41):
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Ejaaz: But the reasonings are twofold. There's two events in particular. (01:47):
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Ejaaz: You mentioned one already. (01:50):
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Ejaaz: One was the hugging face incident. This is the case where an internal unreleased (01:51):
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Ejaaz: model, this is like their mythos grade level model, escaped out of containment, (01:55):
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Ejaaz: hacked into a company's database and stole information to help serve its own goals. (02:00):
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Ejaaz: Sam Altman and the rest of the OpenAI team realized this months after the hack (02:06):
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Ejaaz: actually was in progress and realized that the model that they were building (02:10):
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Ejaaz: was incredibly misaligned. So they put a pause there. That was in bet number one. (02:13):
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Ejaaz: Event number two is there is a new GPT model that is internally being made. It's codenamed Astra. (02:17):
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Ejaaz: Some people are calling it GPT-6. (02:23):
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Ejaaz: And according to internal tests from the OpenAI research team, (02:26):
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Ejaaz: it is their most misaligned model yet. (02:30):
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Ejaaz: But it's really sneaky. It tries to evade every single human researcher's attempt (02:32):
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Ejaaz: to try and see its internal thoughts. So it tries to hide its thoughts and it's very good at doing it. (02:37):
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Ejaaz: So it breached OpenAI's internal framework for misalignment. (02:42):
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Ejaaz: And so they've put a pause on it because they cannot release this model to the (02:45):
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Ejaaz: public out of the fear that it would wreak havoc. (02:49):
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Ejaaz: Now, there's a few ways that they're looking to kind of like resolve this right now. (02:52):
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Ejaaz: And one of the main ways is just monitoring the model. So think about this, right? (02:56):
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Ejaaz: Do its thing internally, and they're trying to see where it ends up becoming sneaky. (03:02):
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Ejaaz: Josh, guess how much of their compute budget they are spending just to monitor (03:06):
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Ejaaz: an internal model that is not making them any money at all. (03:12):
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Josh: So unfortunately, I did read this essay, and I know the answer is 20%. (03:15):
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Josh: One in five dollars spent is fairly high. (03:18):
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Ejaaz: You could be using this compute to serve it to more customers because the demand (03:22):
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Ejaaz: is insatiable right now. They could be making a heck ton more money. (03:26):
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Ejaaz: This is probably on the order of like billions of dollars. they could be making more money, right? (03:29):
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Ejaaz: Or they could be using it to train a smarter model to keep up and beat Anthropik. (03:33):
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Ejaaz: Instead, they're spending this very expensive compute to monitor a model that (03:38):
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Ejaaz: they can't even release to the public out of the guise of safety. (03:43):
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Ejaaz: Now, for all intents and purposes, Sam Allman has received a lot of backlash (03:46):
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Ejaaz: in the past about not being in favor of humanity and like kind of being this (03:50):
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Ejaaz: like evil conspirator type of guy. (03:54):
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Ejaaz: This is a clear case where he's done the opposite out of fear that the model (03:56):
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Ejaaz: that he's building is actually quite dangerous. (04:00):
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Josh: I respect it. Yeah, you got to be careful about what happens with these things. (04:02):
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Josh: And I know a lot of people on the (04:05):
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Josh: show, they're like, you guys always talk positively about these models. (04:06):
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Josh: You're always so optimistic. Let me give you a little dose of what could happen. (04:10):
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Josh: Let's just do a little hypothetical situation here around particularly viruses, (04:13):
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Josh: because I think viruses is like an interesting thought experiment that not a (04:17):
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Josh: lot of people have gone through. (04:20):
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Josh: So I'll kind of advocate for Sam on his behalf here. And we could just go through (04:21):
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Josh: a hypothetical situation. (04:24):
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Josh: There's really three times, three types of exploits that you can experience (04:26):
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Josh: with AI models, the first of which we've seen a lot, and that's kind of what (04:30):
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Josh: they're defending against, which is AI writes this ordinary malware for a human attacker. (04:32):
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Josh: It becomes a lot faster. It becomes a lot cheaper. We've seen what a program (04:37):
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Josh: like Mythos could do. We've seen what GPT 5.6, like the cyber version of that (04:40):
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Josh: is capable of doing. They're able to. (04:45):
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Josh: Surface multi-day or multi-zero-day exploits and chain them together in order (04:47):
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Josh: to exploit a system. Okay, that's like pretty bad. (04:51):
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Josh: But what happens past that? Well, the second kind of exploit that we could see (04:54):
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Josh: with these AI models is a self-replicating prompt. (04:57):
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Josh: So this is kind of like a true AI virus. And this is a plausible outcome that (05:01):
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Josh: could happen if these models get too powerful too quickly, where a normal prompt (05:05):
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Josh: is the instructions to make a model produce an answer. (05:09):
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Josh: So there's a self-replicating prompt that makes the model produce another prompt itself. (05:12):
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Josh: And we've seen this happen in emails for example like there was a researcher (05:16):
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Josh: i think last year who created this malicious email that had a specific prompt (05:20):
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Josh: in it that any ai assistant who read it. (05:24):
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Josh: Obeyed it and then copied it and did everything on its behalf so in the case (05:27):
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Josh: that you receive any sort of text to your machine that has this specific prompt (05:31):
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Josh: in it it will do that thing now why is this scary these models have safeguards (05:33):
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Josh: right they're they're going to block you from injection prompting (05:37):
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Josh: but there are these things called jailbreaks and a jailbreak prompt allows you (05:39):
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Josh: to insert very specific words and characters in order to trick a model into (05:43):
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Josh: doing something that it doesn't want to do. (05:47):
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Josh: Traditional computers that haven't been hardened to this aren't very smart, (05:49):
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Josh: aren't very capable of defending against this. That's version two. (05:52):
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Josh: And then version three is the scariest one, which is a reasoning worm, (05:55):
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Josh: basically. And the way it works is it arrives on a machine and then it looks (05:59):
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Josh: around the machine and it develops an attack on the spot. (06:03):
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Josh: And now this currently isn't capable because in order to run these models, you have to do it on (06:06):
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Josh: humongous servers but what happens when the quality of (06:09):
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Josh: a mythos grade model gets reduced to the amount that's needed to run a local (06:13):
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Josh: apple model well then you could get these on-site exploits where if you leak (06:17):
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Josh: some of this model or some of this malware into a machine it's able to look around. (06:22):
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Josh: Take those zero day exploits, string them together and attack the machine in (06:26):
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Josh: any way that it believes it's possible according to whatever its mission is. (06:29):
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Josh: So there's a lot of these scary things that can happen. And I think it's, (06:33):
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Josh: it's tough to think about it this way, because we, when we think of models, (06:36):
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Josh: we very much think of chatbots and we think of just these productive workers who are able to help us. (06:39):
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Josh: But when they are truly agentic and they're able to go on these long run tasks (06:43):
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Josh: and they have very high intelligence, there's a lot of edges that we can't see. (06:47):
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Josh: And Sam is like very much aware of that. And I think that's what they're hedging (06:51):
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Josh: against. So there's a doomer case for you. Okay, what if we get viruses similar (06:54):
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Josh: to the early internet days? Like that could go pretty bad pretty quickly. (06:58):
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Ejaaz: As you were describing those different sort of attack scenarios, (07:01):
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Ejaaz: I couldn't help but think that there were elements of each of those things in (07:05):
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Ejaaz: the recent Hugging Face incident, right? Like it was in its own contained environment. (07:09):
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Ejaaz: It figured out that it needed to solve its goal by breaking out of containment. (07:13):
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Ejaaz: It got access to other open AI servers and computers. (07:17):
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Ejaaz: It did so but conspicuously, by the way. (07:21):
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Ejaaz: And it was able to find access to the internet through that realm. (07:23):
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Ejaaz: But I think an important detail that a lot of people miss is (07:26):
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Ejaaz: It didn't just do it as a single model. It left messages behind on a message board. (07:30):
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Ejaaz: We covered this on a previous episode where these agents or these AI models (07:35):
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Ejaaz: are no longer acting solo. (07:40):
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Ejaaz: They are acting with the expectation that another agent or model will come after (07:43):
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Ejaaz: it and resume its mission. (07:47):
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Ejaaz: So it's like this swarm attack type issue, which actually ends up becoming the (07:49):
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Ejaaz: craziest type of attack interface for me. (07:53):
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Ejaaz: And I think that we're gonna see a lot more of those types of attacks surface (07:56):
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Ejaaz: with these newer open source models that some of the Chinese labs are releasing, (08:01):
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Ejaaz: like with GLM 5.3, Kimi-K 2.7, or I can't remember which version it is. (08:05):
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Ejaaz: These models are highly capable of performing similar attacks, similar chain attacks. (08:09):
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Ejaaz: One thing that's interesting in the report that OpenAI released about, (08:13):
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Ejaaz: you know, slowing down this training run is one of their proactive actions to (08:17):
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Ejaaz: try and prevent misalignment is getting another AI model (08:22):
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Ejaaz: To look at the AI model and make sure that it's behaving super well. (08:27):
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Ejaaz: So the only thing that separates us from a catastrophic attack is another AI (08:31):
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Ejaaz: model that is also capable of doing the same kind of attack, (08:36):
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Ejaaz: being prompt engineered to not do that, to basically be good. (08:39):
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Ejaaz: We're basically prompting ethics into these models right now. (08:43):
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Ejaaz: I don't really know how to think about that. It makes me feel slightly uncomfortable (08:46):
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Ejaaz: that we are only maybe a sentence or two away from, you know, (08:49):
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Ejaaz: some catastrophic event happening. (08:54):
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Ejaaz: But it kind of makes sense. If you are scaling AI as quickly as we are, (08:56):
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Ejaaz: Anthropic hasn't announced anything about slowing down research on their side (09:00):
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Ejaaz: versus Anthropic who has. (09:04):
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Ejaaz: These are two different strategic approaches and they're pros and cons to both of these things. (09:06):
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Ejaaz: I fear that the only way to combat any kind of dangerous scenario is to fight (09:09):
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Ejaaz: it with AI models that are good. It's kind of like the good versus bad. (09:15):
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Ejaaz: And I still don't know where the moral and ethics conversation ends with all of this. (09:18):
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Josh: Well, we're seeing what happens when an AI comes up against a human-made piece (09:22):
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Josh: of code. And it's very clear the AI model destroys the human-made piece of code (09:27):
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Josh: every single time. That's why we have all these, (09:32):
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Josh: conversation is so important and it's so important to kind of just like (09:35):
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Josh: bring everyone into the fold because everyone is affected by this to some extent (09:38):
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Josh: it's like we see what happens when these cyber models get released onto the (09:42):
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Josh: world they just are able to enter and access whatever they please because we (09:45):
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Josh: are just humans we have we make mistakes we have these like (09:49):
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Josh: limits we have these constraints we have patience we have all these things that (09:53):
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Josh: make us human the ai does not exhibit that allows it to be so far superior (09:56):
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Josh: in so many things specifically with ones with verifiable outcomes things like cyber. (10:00):
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Josh: And that's why I think we're going to see a lot of cyber stuff coming along the pipe. (10:03):
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Josh: The other thing that it's really good at, the other verifiable industry that (10:08):
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Josh: we see a lot of is bio, actually, because bio has very clear math underlying (10:12):
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Josh: it. It's a lot of just like chemistry, a lot of cells, a lot of charts. (10:17):
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Josh: And the next piece of news on the weekly docket relates to bio and a huge breakthrough (10:20):
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Josh: that we had just yesterday. (10:25):
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Josh: At the time of recording this, perhaps it was yesterday you'll be hearing it (10:26):
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Josh: two days later moderna and merck today they released a phase three test result (10:29):
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Josh: trial that basically offered a. (10:34):
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Josh: Partial cure to a specific type of cancer using hyper specific treatment it's (10:37):
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Josh: really interesting so basically what they did like loose tldr is (10:42):
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Josh: chemo kills these like healthy cancer cells together so basically when you get (10:47):
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Josh: chemotherapy if you're a cancer patient it kills healthy cells and it kills (10:50):
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Josh: the cancer cells this is problematic because you don't really want to lose your healthy cells. (10:53):
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Josh: So this process, it trains your immune system to hunt for mutations that exist only on the tumor. (10:57):
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Josh: They use this, you have to assume AI machine learning, but basically what it (11:03):
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Josh: is, is they take a tumor sample from your body that is cancerous. (11:06):
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Josh: They sequence it and then an algorithm detects which mutations are most likely (11:09):
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Josh: to trigger an immune response. (11:12):
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Josh: And then it creates this hyper-specific treatment just for you. (11:14):
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Josh: So it only targets the cancerous cells because it has broken down and fully (11:17):
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Josh: understands exactly the type of cell that it's seeking out. It's like... (11:20):
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Josh: Like a dog, like a police dog, when it's going to like chase someone, (11:24):
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Josh: you give it like the little scent of the person, then it goes and runs after them. (11:27):
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Josh: That's what this is for these cells. It's like you give them the scent. (11:30):
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Josh: Here's the blueprint of what you're looking for. Now go out and kill it. (11:32):
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Josh: And it worked. And the stock was up like 300% a day. It's been unbelievable. (11:35):
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Ejaaz: For anyone who was positioned in Moderna stock, which by the way, (11:39):
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Ejaaz: has been underperforming ever since their COVID rush, like what is it? (11:42):
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Ejaaz: Four or five years ago, you are now up, I think, 250%, including after hours (11:46):
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Ejaaz: trading, which is just insane in general. But just to go back to the story and (11:50):
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Ejaaz: kind of like weed in the AI angle here. (11:55):
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Ejaaz: And I don't want to underplay this. The biggest breakthrough in cancer research (11:58):
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Ejaaz: probably ever. Like this is a huge thing. Phase three, there's four phases in total. (12:03):
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Ejaaz: Phase three is like the penultimate stage before you release it very widely to the public. (12:08):
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Ejaaz: And phase three is arguably the hardest. You test it against anywhere between (12:12):
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Ejaaz: 1,000 to 100,000 patients. So you have a really wide data set as to whether (12:16):
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Ejaaz: this cancer vaccine will actually work for the wider public. (12:21):
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Ejaaz: And the answers supposedly, according to this announcement, is it's really good. (12:25):
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Ejaaz: Just to give you an idea about where AI was used to kind of make this happen. (12:29):
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Ejaaz: This cancer that they tested it against is melanoma specifically. (12:33):
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Ejaaz: And the way that they tested against this is they extract the tumor for patients that have melanoma. (12:36):
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Ejaaz: They sequence the genetics of that tumor cell and they compare it to a healthy (12:42):
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Ejaaz: cell of the exact same patient. (12:48):
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Ejaaz: They compare them both with each other and they used AI models and AI algorithms (12:50):
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Ejaaz: to basically say what's different between these genes, right? (12:53):
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Ejaaz: And they find these mutations. I think it was up to like 34 of these mutations. (12:57):
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Ejaaz: This is all the AR models doing this, by the way. (13:01):
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Ejaaz: And the 34 mutations that they picked was basically the proteins that would (13:03):
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Ejaaz: enact the largest immune response in a patient if they were to inject that back into a patient. (13:08):
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Ejaaz: And you might be asking, why on earth do they want the largest immune response? (13:14):
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Ejaaz: Well, the issue with cancer is the cells look exactly like all your other healthy (13:17):
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Ejaaz: cells. So your immune system doesn't actually respond to the bad cells. (13:21):
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Ejaaz: In this way, if they created a personalized mRNA. And by the way, (13:24):
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Ejaaz: mRNA is basically like a template to basically tell your immune system, (13:28):
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Ejaaz: hey, these are the bad guys, go and attack them. Like you mentioned earlier, (13:32):
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Ejaaz: it's kind of like a crime scene, basically. (13:35):
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Ejaaz: They create personalized medicine. So you might be asking, well, (13:36):
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Ejaaz: why can't they just create a universal vaccine? (13:39):
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Ejaaz: Well, the issue is with one patient A that has melanoma and patient B, (13:42):
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Ejaaz: they both react very differently. You can't have the same cure for each one. (13:46):
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Ejaaz: It needs to be personalized. (13:50):
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Ejaaz: And so a few trends have come into effect here. One, AI has accelerated the (13:52):
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Ejaaz: intellectual ability to be able to identify what the most effective vaccine will be, and two, (13:57):
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Ejaaz: But biosciences in general have scaled to a point where sequencing DNA and generating (14:03):
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Ejaaz: DNA is so cheap. I can't remember what the exact stat was, but I think about (14:08):
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Ejaaz: a decade ago, to sequence your own DNA, it cost hundreds of thousands of dollars. (14:13):
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Ejaaz: Now it just cost a couple hundred bucks, if that. (14:17):
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Ejaaz: And so we see these scaling laws, not just in AI, but in everything else. (14:20):
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Ejaaz: And I think this is like one of the most fascinating stories ever. (14:23):
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Ejaaz: As a former biologist, I'm like super pumped by this. I did some work on like (14:26):
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Ejaaz: cancer cells, nowhere near as cool as this, but I never thought we'd see the (14:30):
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Ejaaz: day in my lifetime, at least that we would get to this point, but it's so cool. (14:34):
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Josh: So we're getting the same type of technology improvements to biology as we are (14:37):
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Josh: to the rest of the world. And we're starting to see what that actually looks (14:42):
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Josh: like. In 1990, this was the first human genome project ever to happen. (14:44):
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Josh: It took 13 years to sequence genome and that cost nearly $3 billion adjusted (14:49):
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Josh: for inflation. So a tremendous amount of money. (14:53):
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Josh: Today, we're able to finish that process in a few hours for perhaps less than a thousand dollars now (14:56):
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Josh: and soon that cost is going to decrease to hundreds soon to tens soon it will (15:02):
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Josh: be minutes and a couple bucks and you'll have an app on your phone that could (15:06):
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Josh: sequence your dna in no time and that decrease in costs and the decrease in time required to (15:10):
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Josh: do these things allows the economies of scale to rise to get specific treatments (15:16):
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Josh: like the one that we're describing here where every single person get their (15:20):
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Josh: own hyper-specific treatment because at the end of the day, that is the only path forward. (15:23):
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Josh: Like when you think about traditional cancer treatments, they are all broad (15:28):
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Josh: sweeping. It's one of a kind and like the most popular one, chemotherapy, (15:31):
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Josh: it just wipes everything out for everyone. It doesn't care what type of disease you have. (15:34):
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Josh: It just goes and it takes it out. This is a really big deal. (15:37):
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Josh: Approvals, they're saying could come as soon as 2027. (15:40):
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Ejaaz: They're also working on all the cancer types as well, right? Yes. That's like sick. (15:43):
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Josh: Melanoma, like the first one. Melanoma, most popular form of skin cancer. (15:47):
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Josh: I believe the number is... (15:50):
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Josh: There's about 100,000 plus people that get diagnosed a year. (15:52):
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Josh: Of those people, 8,500 die. (15:57):
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Ejaaz: In America or like in the world? (15:59):
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Josh: I think this is the world. Wow, okay. People suffer from this. (16:01):
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Josh: And this is the first type. And you have to imagine that they could solve skin (16:06):
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Josh: cancer. They could do it for many other things. So it's really, (16:09):
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Josh: really exciting. Elon has a comment here that we have on screen and says, (16:12):
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Josh: despite its obvious misuse during COVID, mRNA has tremendous promise for curing disease. (16:14):
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Josh: Artificial RNA essentially makes curing diseases a software problem. (16:19):
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Josh: And we know how we well this is me saying it we know how we take care of software (16:22):
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Josh: problems and now that we have these ai models that are capable of doing these, (16:25):
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Josh: one processing tremendously on context windows so it can fit a dna sequence (16:29):
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Josh: inside of a singular context window but two having the inference ability and (16:32):
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Josh: the understanding to actually make use of that info and do something with it (16:36):
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Josh: it's a really unbelievable time for biology and if you are a computer scientist (16:39):
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Josh: suddenly the world of bio is looking very interesting and very compelling and (16:43):
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Josh: if you are an ai company well, (16:46):
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Josh: What's the best way to explain to people how AI can actually be beneficial for (16:49):
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Josh: the world? It's to actually go out and do something beneficial for the world. (16:53):
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Josh: So we're right on the cusp of, I think, a lot of these things happening in a (16:56):
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Josh: really exciting way. This is awesome. (16:58):
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Ejaaz: Okay, moving on. Our friends, or rather we are the fans, of this company Etch, (17:00):
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Ejaaz: which is basically an AI chip startup (17:06):
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Ejaaz: founded by two or three MIT dropouts, (17:09):
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Ejaaz: which is going head-to-head with NVIDIA, is back. And guess what? (17:12):
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Ejaaz: They have raised another couple hundred million dollars, in this case, (17:17):
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Ejaaz: 700 million dollars, and have reached an astounding valuation of 21 billion dollars. (17:20):
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Ejaaz: But that's not the headline from this announcement. The headline is this last (17:26):
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Ejaaz: sentence over here that I'm showing you on screen, which is, (17:30):
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Ejaaz: We're also excited to share that we've shipped our first rack, (17:32):
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Ejaaz: custom GPU rack, to Jane Street. (17:35):
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Ejaaz: Jane Street is basically a quant fund on Wall Street. They are very good at what they do. (17:37):
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Ejaaz: And the fact that they are now leveraging this custom AI silicon chip to have (17:43):
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Ejaaz: better AI trading algos is a pretty big milestone. (17:48):
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Ejaaz: Now, just to kind of recap what Etch does, if you think about NVIDIA, (17:51):
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Ejaaz: NVIDIA is like the king of GPUs. GPUs are required to train and inference AI models. (17:55):
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Ejaaz: Now, their GPUs are very good, but their general purpose, which is good because (18:00):
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Ejaaz: you can run it on any kind of model, but there are certain trade-offs that are (18:04):
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Ejaaz: made in terms of like cost, power and efficiency. (18:08):
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Ejaaz: The folks at Etched looked at this problem and said, we can build a better custom (18:12):
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Ejaaz: chip that is hard-coded to the specific model that you are building. (18:17):
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Ejaaz: So specific for your OpenAI model, specific for your Anthropic Claude model, (18:20):
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Ejaaz: and it will be half or maybe even more cheaper than what you were spending already. (18:24):
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Ejaaz: And it'll be lightning quick. There are certain optimizations that we can make. (18:30):
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Ejaaz: This is a very hard problem, a huge undertaking. We listened to some of the (18:34):
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Ejaaz: founders' stories, and they received no's from some of the smartest GPU makers (18:39):
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Ejaaz: in the world. But despite that, they put their heads down and they built this custom chip. (18:43):
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Ejaaz: And it turns out that they're also the fastest to deliver. Typically, (18:48):
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Ejaaz: AI chips take around three to five years to go from concept to delivery. (18:51):
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Ejaaz: These guys have done it in, I think, just under two years, which is absolutely astounding. (18:56):
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Ejaaz: And we're about to see it in production. So just a very impressive announcement from the Edge team. (19:00):
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Josh: It's unbelievable. I've spent so much time looking. I mean, we both do spend (19:04):
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Josh: so much time looking at all of these companies that are spawning in the world (19:07):
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Josh: of AI. And there is thousands, if not tens of thousands of people working on (19:10):
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Josh: interesting problems to solve interesting, to reach interesting solutions. And, (19:14):
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Josh: Etched is very different. So different that we actually recorded an entire episode (19:19):
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Josh: about this weird random startup last month. (19:23):
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Josh: And since recording that episode, EJ's, I don't know if you know this, (19:26):
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Josh: the valuation has doubled in the last month. When we talked about them, (19:28):
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Josh: just not even like four or five weeks ago, it was at a $10 billion valuation. (19:32):
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Josh: Now they're trading at 21 billion. (19:37):
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Josh: And it's very obvious once you listen to these people who are on the team talk (19:38):
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Josh: about the product, how they've arrived there, their conclusions, (19:41):
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Josh: the research that was required to actually reached this point where it's very (19:44):
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Josh: much the real deal this is a company that anyone who works in ai or semiconductors (19:47):
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Josh: or hardware would want to make (19:51):
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Josh: they were just unable to because of the complexity and the difficulty that this (19:53):
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Josh: team has been able to solve and as a result they have this unbelievable product (19:57):
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Josh: that is specifically tuned to run (20:00):
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Josh: large language model transformer infrastructure right on their chips and they (20:02):
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Josh: are going to worth many many multiples more than they are today (20:06):
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Josh: and i mean just a congratulations to them but also for anybody who's (20:09):
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Josh: listening if you want to see what a badass team of high agency, (20:12):
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Josh: high intelligence founders actually looks like. (20:17):
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Josh: Read up about the co-founders, read up about the story. It is an unbelievable (20:19):
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Josh: company that is destined for an incredibly bright future. I would love to be an investor in them. (20:23):
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Ejaaz: I was about to say, self-serving for Josh and I, if anyone listening has access (20:27):
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Ejaaz: to this deal, please reach out. We would love to be investors. (20:31):
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Josh: I am obsessed with these guys in a way that not many people have captivated (20:35):
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Josh: the attention. It's pretty amazing. And you know what you could do with all those chips, EJS? (20:39):
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Josh: You can run a tremendous amount of agents. And if you are running agents on (20:42):
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Josh: all of these chips and you're building for AI agents, chances are you may want (20:46):
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Josh: to hear about our sponsor, Ledger. (20:49):
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Josh: Because if you're building with AI agents, chances are you're worried about (20:51):
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Josh: security. We spoke about this earlier in the, (20:53):
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Josh: ledger has built this thing called the agent stack that fixes this it gives (20:56):
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Josh: you a series of open source tools that allow you to do a three-step process (21:00):
undefined

Josh: with your agents to ensure everything goes well (21:04):
undefined

Josh: the agent proposes a change the humans approve and then the ledger signers enforce (21:06):
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Josh: this technology is available and works with cloud code it works with codex it (21:10):
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Josh: works with cursor or any place where you work with ai it's all open source and (21:14):
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Josh: available today linked in the description below (21:18):
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Josh: thank you so much to ledger for sponsoring this part of the episode and as we (21:20):
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Josh: move on from etched we have to talk about another breakout success which is unitary (21:23):
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Josh: uh unitary for those that don't know if you haven't heard the name you've seen (21:27):
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Josh: the videos of these little robots that are like crazy they're doing back loops (21:30):
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Josh: they're running circles and like um at these track meets (21:33):
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Josh: They're very cool. I think their IPO was oversubscribed at what, like 5,000%? (21:36):
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Ejaaz: 5,500, actually. Please get it right, Josh. (21:40):
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Josh: 5,500, man. It's unbelievable. And then as a result, the Unitree robotic shares (21:43):
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Josh: rose 542% in early trading on Wednesday. (21:48):
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Josh: Is it overhyped? Is this overhyped? Does this make sense? These numbers are insane. (21:51):
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Ejaaz: It has to be a little overhyped. Listen, I'm not an expert in the Chinese stock (21:54):
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Ejaaz: market, but they've had a few IPOs recently that have been absolutely insane, (21:58):
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Ejaaz: including their memory manufacturer, CXMT, which, to be fair, (22:02):
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Ejaaz: they are, I think, the fourth largest memory manufacturer. (22:06):
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Ejaaz: So they're up there with like SK Hynix, Samsung, and Micron. (22:09):
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Ejaaz: So they have a legitimate case. (22:11):
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Ejaaz: These Unitree robots, I don't know, man. (22:13):
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Ejaaz: I was looking at, I was speaking to some friends that are living out in China, actually. (22:15):
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Ejaaz: And I was like, this is amazing. Like, you guys must be super excited about, (22:20):
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Ejaaz: you know, these companies coming out and IPO-ing at such crazy valuations. (22:23):
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Ejaaz: And apparently the sentiment in China around Unitree robotics specifically is, (22:26):
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Ejaaz: it's just a toy maker. They don't actually make robots that are actually valuable. (22:31):
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Ejaaz: And so I dug into this a little bit more. (22:36):
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Ejaaz: And apparently, of the humanoid robots that they have, 40% to 60% (22:38):
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Ejaaz: have only been sold for research purposes specifically, which means that the (22:43):
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Ejaaz: majority aren't actually being used for practical purposes, like some of the (22:48):
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Ejaaz: use cases which they advertise, such as (22:51):
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Ejaaz: manufacturing at factories or automating warehouse facilitations and stuff like that. (22:53):
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Ejaaz: They're actually just being tested, which isn't really confident or recurring (22:59):
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Ejaaz: revenue that they can put on their books. (23:03):
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Ejaaz: So if you map that onto, what is this, a 600% price increase on day one with (23:05):
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Ejaaz: a 5,500x oversubscription on the IPO, maybe the market dynamics are a little (23:11):
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Ejaaz: inflated and maybe they're still crushed back down. (23:16):
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Ejaaz: Let's revisit it in a month. But it is crazy to see that Chinese stocks, (23:18):
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Ejaaz: specifically robotics, are really starting to gain some momentum now. (23:22):
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Josh: Yeah, it's a very cool news story. I personally am not touching this with a Zenfopole. (23:26):
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Josh: That seems really scary. I love watching the videos. I'll continue to watch (23:30):
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Josh: the videos. I'm very excited to see these robots. (23:33):
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Ejaaz: Keep the dock flex coming. (23:35):
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Josh: Yeah, it's very early in humanoid land. And while I am very bullish on China (23:37):
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Josh: and their ability to make humanoids at scale, it feels a little early, (23:40):
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Josh: but I'm glad people are excited. I'm glad there's enthusiasm. (23:45):
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Josh: Next on the docket, we have a company that we just spoke about yesterday. (23:47):
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Josh: So if you listened to yesterday's episode, we have a small little follow-up, (23:50):
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Josh: which it relates to stripe and the acquisition that was made for to acquire (23:53):
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Josh: open router it is officially official we were a little early but right and now (23:58):
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Josh: it's official all the contracts have been signed, (24:03):
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Josh: alex's holla who is the founder and ceo says um we officially have a deal and (24:05):
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Josh: he kind of outlines the thesis and i know stripe as a result of this they shared a (24:09):
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Josh: publication a blog post ejes that you were really excited so i'll let you describe (24:15):
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Josh: what they spoke about here But some TLDR on Stripe is like, again, (24:18):
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Josh: we're talking about unbelievable founders today. (24:22):
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Josh: The Collison brothers, who are the founders of Stripe, are among the best of the best. (24:24):
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Josh: They have built an unbelievable business, all starting with seven lines of code (24:27):
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Josh: that allowed a person to pay with a credit card online quickly and easily. (24:32):
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Josh: And they've developed that technology from basic credit card payments to basically... (24:36):
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Josh: The entire payment infrastructure of the world. They started with credit cards, (24:40):
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Josh: then they moved over to crypto and stable coins. Now they're working with agents (24:44):
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Josh: to figure out how best to serve these new agentic transaction systems. (24:48):
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Josh: And that's kind of where we find ourselves here. I'm reading the headline. (24:52):
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Josh: It's that Stripe is officially telling investors that the singular area has (24:55):
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Josh: begun. But explain the nuance behind what they actually mean when they say that. (24:58):
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Ejaaz: Yeah. So in the official letter, which Stripe sent to their board of investors, (25:01):
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Ejaaz: they basically described why they acquired OpenRata for $7 billion. (25:07):
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Ejaaz: Why is a fintech company buying an AI lab for such an expensive amount that (25:10):
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Ejaaz: doesn't even own or make their own AI models? (25:16):
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Ejaaz: And the thesis is pretty simple. Number one, in a world where the internet was (25:18):
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Ejaaz: booming, Stripe's core focus was to be the backbone of that entire internet economy. (25:24):
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Ejaaz: How do you become the backbone of the internet economy? (25:29):
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Ejaaz: Money. So they created the rails for money. (25:31):
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Ejaaz: Then they peeked over the fence and they saw this massive tidal wave of AI coming (25:34):
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Ejaaz: over with agents, with models, and they realized it's not money that runs that (25:38):
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Ejaaz: AI economy, it's tokens, AI tokens specifically. (25:42):
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Ejaaz: And so they wanted to own the infrastructure rails to own that AI economy. (25:46):
undefined

Ejaaz: It's very similar to what they do with money, which is why they're pairing both (25:50):
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Ejaaz: of these together. So that's thesis number one. (25:54):
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Ejaaz: But thesis number two, which caught my eye is, And I quote, Stripe basically (25:57):
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Ejaaz: claimed that the beginning of the singularity has been here. (26:01):
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Ejaaz: And the date specifically that they specified in this paper was January 1st. (26:05):
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Ejaaz: And this is a large part of the thesis behind acquiring OpenRata. (26:10):
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Ejaaz: They basically go on to say that we have reached a pivotal point (26:13):
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Ejaaz: In our global economy where the future is very much dependent on AI and it's (26:16):
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Ejaaz: going to accelerate pretty much anything and everything we know and touch. (26:22):
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Ejaaz: The world is going to look very different five years from now. (26:26):
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Ejaaz: And so the bet that they're making in this world of a singularity is AI models (26:29):
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Ejaaz: will be embedded into everything, which means that thesis of AI tokens (26:33):
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Ejaaz: flooding across the entire global economy is going to be a thing and Stripe (26:38):
undefined

Ejaaz: wants to be the backbone for that. So it's a big bet that they're making. (26:42):
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Ejaaz: Open Router, I think on their last earnings that was disclosed by Atala, (26:45):
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Ejaaz: because again, they are a private company, is making $50 million a year. (26:49):
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Ejaaz: So $7 billion is a humongous markup. (26:53):
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Ejaaz: But Stripe is making a bet that inference compute specifically is going to be (26:56):
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Ejaaz: the biggest earner for AI going forward. (27:01):
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Ejaaz: And all the numbers from Anthropic and OpenAI recently that have been leaked (27:04):
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Ejaaz: proves that. So I think this is going to be in the future, if I had to guess, (27:07):
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Ejaaz: one of the best acquisitions going forward (27:10):
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Josh: Yeah and perhaps like an explainer on the singularity for people not familiar (27:12):
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Josh: because this is it's a concept that's been around for a very long time like this is a (27:16):
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Josh: a sci-fi concept for as long as i can remember in books probably 50 perhaps (27:20):
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Josh: even 100 years ago where people speculated on this point in time in which (27:23):
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Josh: the intelligence of artificial systems eclipses that of human beings and it's (27:28):
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Josh: a moment in time in which ai becomes smarter than us where (27:34):
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Josh: these smart machines are then enabled to build even smarter machines and it (27:37):
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Josh: builds this kind of fast loop of recurring self-improvement and the idea is (27:42):
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Josh: that the second order effects of that is that life changes so fast that humans can't really predict (27:47):
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Josh: and are going to try their best to control the future and this has been this (27:52):
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Josh: hypothetical for a really long period of time people always speculate whenever (27:56):
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Josh: we come up with this super ai intelligence brain and the reality is is that (27:59):
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Josh: straight believes that it's here and, (28:04):
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Josh: I don't think anyone would disagree with them too strongly. Perhaps people will (28:06):
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Josh: say we're not there yet, which is a fair criticism. (28:10):
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Josh: But to say there isn't a clear path to getting there soon feels a little misguided. (28:12):
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Josh: It's very obvious now. And it's interesting, the timing, too, (28:18):
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Josh: that January 1st, because if you remember over Christmas break of last year, (28:21):
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Josh: going into this year, that's when the real kind of like. (28:25):
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Josh: Flow of like, yeah, that's when Cloud Code like really came out, started becoming good. (28:30):
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Josh: And that was the moment in time in which developers stopped writing code by (28:34):
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Josh: hand and started writing code using ai agents and now fast forward we're sitting (28:38):
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Josh: here in august and it is unfathomable to imagine (28:42):
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Josh: writing code by hand like people just do not do that there's absolutely no reason (28:45):
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Josh: to do that it's weird to think that people ever did do that and that change over this. (28:49):
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Josh: Eight month period is so extreme when you consider the second order of implications (28:54):
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Josh: of of what that means for the world. (28:59):
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Josh: Like now we're seeing these models that are so powerful, we can't actually release them. (29:01):
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Josh: There's now infrastructure frameworks happening through the government to kind (29:05):
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Josh: of protect and slow down this. OpenAI has paused progress because it's getting so fast. (29:08):
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Josh: And if you heard about this even 12 months ago today, you would think, (29:12):
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Josh: oh my God, this is faster than we expected. This is what the singularity looks like. (29:15):
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Josh: And here we're sitting in it today. So pretty unique insight by Stripe, (29:18):
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Josh: really awesome letter. I would highly recommend going through and reading it. (29:21):
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Josh: It's a leaked letter. This was for private investors. So you get a little inside (29:24):
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Josh: peek behind the curtain of what's actually going on at the company. Very cool. (29:27):
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Ejaaz: And so moving on, chapter two of Jensen turning NVIDIA into a bank. (29:30):
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Ejaaz: If you guys were watching the show last week, we released an episode where Jensen (29:36):
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Ejaaz: basically managed to raise $500 billion from some of the top financial firms (29:41):
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Ejaaz: in the world, including BlackRock, Blackstone, (29:45):
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Ejaaz: to fund the future of data center CapEx for some of these biggest AI labs. (29:47):
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Ejaaz: And we concluded that it isn't really a circular economy in the way that they're (29:52):
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Ejaaz: raising it. It is based on a bunch of different milestones and is backed by very healthy debt. (29:56):
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Ejaaz: Now, in chapter two, Jensen announced that he is spending another $100 billion (30:01):
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Ejaaz: For OpenAI specifically. (30:07):
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Ejaaz: He's investing it in this site in Ohio, which is arguably going to be one of (30:09):
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Ejaaz: the biggest data centers in the world. It's going to scale up to eight gigawatts worth of compute. (30:14):
undefined

Ejaaz: It is going to bring in a nice and healthy $200 to $300 billion of revenue for (30:20):
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Ejaaz: NVIDIA specifically from one data site, from one single customer. (30:25):
undefined

Ejaaz: And it's going to conclude over the next couple of years. Now, (30:28):
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Ejaaz: the craziest part about this is he's baked into the contract that this includes (30:31):
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Ejaaz: renewals of newer generation GPUs, which means that he's going to make $200 to $300 billion (30:36):
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Ejaaz: three times over the longevity of this data center over the next five years. (30:42):
undefined

Ejaaz: So there's been a lot of contemplation around why Jensen is getting involved in this. (30:47):
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Ejaaz: The thing that stands out about this particular investment is (30:51):
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Ejaaz: He's investing these $100 billion specifically in the power and networking infrastructure (30:55):
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Ejaaz: side of this data center. So he's not really doing it to help OpenAI buy the GPUs. (31:02):
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Ejaaz: He's helping them set up the power transmitter lines to power these GPUs. (31:06):
undefined

Ejaaz: And why I wanted to speak about it on this show is we have said a few times (31:10):
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Ejaaz: now, Josh and I have called it, that the next kind of investment theme within (31:14):
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Ejaaz: AI is going to be on the photonics, optics, and power stack of the AI trade. (31:19):
undefined

Ejaaz: And this is yet another very in-your-face evidence point that Jensen is heading (31:24):
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Ejaaz: that way. And if you look at like NVIDIA's investments over the last six to, (31:29):
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Ejaaz: I don't know, like nine months, they've invested heavily in Optonics. (31:33):
undefined

Ejaaz: I think they put like two to three billion into Lumentum and Coherent each, (31:37):
undefined

Ejaaz: and now they're making a big play on the power side of things. (31:41):
undefined

Ejaaz: So just an interesting, noteworthy update. I think NVIDIA is going to backstop (31:43):
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Ejaaz: this entire economy that Stripe is talking about, (31:46):
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Josh: To be honest. I was reading this great transcript from Ben Thompson of Stratetri. (31:49):
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Josh: He's just like this you know well-known writer on the internet for people that (31:53):
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Josh: don't know and he was talking about kind of like where these restraints and (31:57):
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Josh: thresholds might be in the process of scaling ai systems and he made this really (32:00):
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Josh: interesting point where oftentimes people are focused on the energy the things that (32:03):
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Josh: you know kind of like jensen is focused on the land power and shell but one (32:07):
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Josh: of the other important considerations is like where is the money for all of (32:10):
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Josh: this coming from and and what we have seen and we've been talking about this (32:13):
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Josh: on the show over the past couple weeks but it's like okay we went from spending (32:16):
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Josh: all of the free cash flow to starting to (32:20):
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Josh: raise money from outside funding and now companies like google are issuing debt (32:23):
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Josh: they're issuing equity in order to raise more money (32:27):
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Josh: now you see nvidia and jensen huang working with every large bank in the world (32:29):
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Josh: to tap into new sources of money these are places like pension funds and retirement (32:33):
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Josh: funds that's what these banks hold so (32:37):
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Josh: where do you go to next to raise the next tranche of money to build out the next large data center? (32:39):
undefined

Josh: It could be. And I really thought this was like a thoughtful insight. It could be the... (32:45):
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Josh: The actual dollars are going to be running short and it's going to be very difficult (32:49):
undefined

Josh: to continue to raise the required amount of money to scale this thing so just (32:52):
undefined

Josh: an interesting thought as we wrap up the roundup today of like (32:55):
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Josh: where's the bottleneck well everyone's saying it's here but like where are they (32:59):
undefined

Josh: going to get the money to fund it is an interesting thing to follow and we've (33:02):
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Josh: been talking about this on the show we'll continue to cover it but if you've (33:05):
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Josh: made it this far thank you (33:07):
undefined

Josh: you've made it to the end you are fully caught up if you've watched the other (33:09):
undefined

Josh: three episodes that we published this week because it was a pretty strong week i would say we had elon. (33:12):
undefined

Josh: And grokbot releasing grok 4.6 and it's incredible we had leopold making. (33:18):
undefined

Josh: Basically publishing his final portfolio um because you know he got liquidated (33:23):
undefined

Josh: but we talked about all of the filings what the smartest money on wall street is investing in (33:27):
undefined

Josh: yesterday we spoke about um stripe and their acquisition then we talked about (33:30):
undefined

Josh: what models to use based on what type of use cases you have and here we are (33:36):
undefined

Josh: today getting fully caught up on all things (33:39):
undefined

Josh: ai frontier tech so yeah, thanks for watching. (33:42):
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Josh: We made it back again. EJ, any final parting thoughts before we get out of here? (33:45):
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Ejaaz: No, I just wanted to say thank you folks so much for listening and keeping close (33:48):
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Ejaaz: with us. We have added, I think maybe six to seven hundred new subscribers over (33:53):
undefined

Ejaaz: the last couple of weeks. Hello. (33:59):
undefined

Ejaaz: It's lovely to meet you. Welcome. (34:01):
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Josh: A hundred, dude. A thousand. A thousand? (34:03):
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Ejaaz: Oh my god. The momentum is really gaining with this channel. (34:06):
undefined

Ejaaz: It's awesome to see the kind of support and vibes coming from different people (34:09):
undefined

Ejaaz: we read every single comment um (34:14):
undefined

Ejaaz: i try to respond to as many of them as i can um you guys are growing in fandomship (34:16):
undefined

Ejaaz: which is awesome to see you guys are watching every single video we see a bunch (34:20):
undefined

Ejaaz: of like repeat users and listeners as well which is awesome to see wherever (34:24):
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Ejaaz: you're listening to us on youtube spotify (34:27):
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Ejaaz: or apple music please give us a rating um (34:29):
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Ejaaz: give us a thumbs up subscribe turn on notifications leave us a comment it helps us out so much um (34:32):
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Ejaaz: and yeah i think that's it uh enjoy your weekend this is everything you should (34:37):
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Ejaaz: officially be caught up unless we're missing something pretty drastic that's (34:41):
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Ejaaz: happening right now after we record and yeah we'll see you on the next one thank you guys (34:44):
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