Exploring Latent Layers of Google’s AI

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Google just ran a three-layer strategy move in one day at their Cloud Next conference. They announced new TPU chips, Chrome is turning into an AI coworker, and a multi-billion-dollar compute deal with Miriam Raddy, the former co-founder of OpenAI, her company, Thinking Machine Labs. I think this is one of the clearest signals from me so far that Google is structurally perhaps ahead of OpenAI and Amazon in the AI stack. Before that, though, I want to talk about the fact that OpenAI is teaming up with Infosys to get ChatGPT into 60-plus countries of enterprise deals. Bloomberg reports an unauthorized group breached Anthropix's new cyber tool, Mythos. And there is a new research lab called Neocognition that has landed $40 million to build agents that actually specialize like humans. So we're going to get into all of that on the show today. Our first story is that 10xScience, this is a Stanford spin out of a Nobel laureate Carolyn Bertozzi's lab. They just closed a $4.8 million seed, which was led by initialized capital. What they're doing that's so fascinating to me is that basically there's this problem where models like DeepMind's protein predictor, they're spitting out thousands of drug candidates. So there's just thousands and thousands of these drug candidates. And there's a huge bottleneck in pharma where it's not just about getting all of these candidates, but it's actually triaging them. It's actually figuring out like which of all the candidates is worth pursuing to try to make medicine or therapeutics. And basically, the standard triage tool is just mass spectrometry. So it's very slow. It's very hard to interpret. It's, you know, domain experts only. 10x science is basically just building a SAS layer on top of that. And they have deterministic chemistry plus AI agents to try and make the analysis traceable and explainable, which basically matters because regulators don't accept a black box answer on what the molecule does. Right. So just because an AI model is like, oh my gosh, we discovered this super cool thing.
Like, this isn't going to fly. Regulators don't want that. There's no we have the black box on the molecules. So we have to be able to fully understand it, fully test it. And knowing which of these which of these chemicals, which of these drugs to test is a big problem. So everyone in the AI biotech conversation is basically talking about the generative side, and almost nobody is building the kind of picks and shovels layer that's underneath of it. And so this is why I think 10xScience is an interesting company. The next thing I want to talk about is NeoCognition. So this is an AI research lab that came out of stealth with about $40 million in their seed round.
Yu Su, an Ohio State professor who runs an AI agent lab there, is the founder. And the round was led by Cambium Capital and Walden Catalyst Ventures, Intel CEO Lit Bu Tang and also Databricks co-founder Ion Stoka. Both wrote angel checks into this. So I think that's really strong signal, right? When you have the CEO of Intel, when you have kind of these high-profile co-founders of something like Databricks, this is phenomenal. But essentially the thesis on this company that I think is important is that the current AI agents succeed maybe 50% of the time because they're basically unreliable generalists. And so what they're arguing is that humans aren't great at doing tasks just because we know everything, we're great because we specialize fast when we're dropped into a new domain. So NeoCognition is trying to build agents that self specialize the same way instead of kind of the current model where you hand, you know, craft a custom agent for every vertical.
I've built enough custom agent workflows to know that kind of this per vertical approach doesn't really scale. You run out of engineers before you run out of use cases. So if NeoCognition can actually ship an agent that learns the rules of a new environment, and if it's doing this on its own, which I think is definitely gonna be the key, I think that is a massive win. Right now, they have only 15 people on their team. It's mostly PhDs. Definitely an early company, but I think this is one that's worth watching. Okay, so we have some bad news for Anthropic today. There is a report from Bloomberg yesterday that an unauthorized group got access to Mythos, which is Anthropic's new exclusive enterprise cyber security AI tool that's gonna take over the world, right? They gave it to a handful of enterprises because it's so dangerous and good at getting, you know, finding security vulnerabilities.
I think this is probably not good news because they, you know, they made a lot of hype about how dangerous it was, and they only gave it to special people, and if it really is getting leaked, that's not great for them.