The Ledger, every show

“Science is as an infinite token generator to train models at scale.”

“That data came from the internet, it was human generated, and we have used it all. You know, as Elia said at NeurIPS last year, We have but one internet. It's the fossil fuel. We fracked. We got every ounce of data that we could out of the internet, but it's g…”

“But what at Lilo we believe is that actually science running the scientific method and using nature and experiments as verifier is like the ultimate version of that. And so what we're building, we'll talk about these things that we call AI science factories. T…”

“Certainly for expression protocols, for some gene editing work that we've done we have tested like the platform's ability to do that versus humans. Model gets like 80% of that zero shot. Humans get zero percent of that zero shot.”

“Some of the suggestions from the model initially were boring, but then transitioned from boring to what he considered to be stupid. These are non-platinum group electrocatalysts for separation of hydrogen and oxygen from water to make hydrogen, and those turns…”

“It actually thinks in latent space, it emits tokens. So, like, the chain of thought is often an unreliable narrator for what the model, the computation of the model is actually doing.”

“So we have assembled this reasoning data set of 10 trillion scientific tokens reasoning traces that are experimentally verified across life sciences, chemistry, and material sciences, and we have seen that this general model often beats the domain-specific mod…”

“So we have developed some monster UTRs, untranslated regions, which flank the protein coding region which dictate those expression properties. Something like Tenex, the references from Moderna and Pfizer. And over the course of six months, got to in vivo data …”

“The reason why U.S. Biotech is losing to Chinese biotech is not because of an innovation problem. There's a regulatory framework too that has to go to enabling like fast clinical trials.”

“But we think that like the lab of the future should not be made for people to easily walk into it. It should feel like a data center where you go and you see the rows of server racks. There's room for like a crash cart behind it to service the nodes. But it sh…”

“The bet is that the sort of like as the model performance improves, the sample efficiency goes up, and therefore like the compound interest that you get from round over round experimentation will outweigh that, that you would get from a big noisy, but broad da…”

“So like we have just seen incredible lift from showing the model that even if we're at like a parameter disadvantage relative to the frontier models, just showing it an experimentally verified reasoning, reasoning trace, you see just immediate lift when we do …”

“Safety is not something you can procrastinate on because capability curves tend to be sigmoid shaped and it can look like everything's fine and then all of a sudden there's something that you didn't Anticipate the model being able to do.”

“The model itself is the thing of value at Lila. So in that sense, we're much more of like a neolab trying to think of a new way to push forward capabilities of a core reasoning LLM based model.”

“And so again, the core bet that we're making is that is true for science. That if the model is trained on an increasingly broad set of data, the amount of data that you need in a given domain, that data requirement is reduced. In some cases will be reduced to …”

“In so many counterfactual worlds, that doctor was not the one treating Emily Whitehead in that case, and CAR-T may have looked like, it may have been yet another gravestone in E-Room's law, you know, for you know, yet another failed drug. So I do think that li…”

“We do think about scaling it In the same way that you would think about scaling a data center, in that it's a multi-level building, occupies millions of square feet, and it's like a lights-out facility, as they say. It's like running 24 seven, generating data …”

“We have not decided to take on pre-training as well, just because the black magic that you have to do is, is insane, and we've been gifted, you know, something like a billion dollars worth of compute in the form of open-weight models. So we start with an open-…”

“I think that, you know, if we called ourselves a biopharma, we probably would have a top three GPU cluster in the world.”

“Well, I think materials are harder. So they have the benefit of like great simulators like that we don't have in bio. Like, in material science, you don't have the, like, mature, high-throughput automation that you have in biology. For me, materials as a subje…”

“Academia has a lot going for it. Access to scaled compute is not one of the things that it has going for it, or scaled resources.”

“So actually, the experimental platform that we're building prioritizes generalizability and flexibility over raw throughput. We want the model to be able to design a new experimental protocol, run the protocol, and receive the feedback, even if that's not an e…”

“We actually have a vision language model controlling a Windows 95 machine. Because that's the only way to automate it.”

“So one of the things that we've developed along the way is a test suite of something like a thousand unique scientific RL environments where you can drop in a frontier model. You can drop in your own model. We drop in our models. So almost surely we're going t…”

“And for reinforcement learning, it's always somewhere, like, around five to, like, six percent. So, said differently, that means that we're getting, like, five percent of the actual GPU computing power that we're paying for.”

“We have a physical transport layer that connects almost every instrument that we have bought at Lila to each other. These are currently planar motor systems where there's an I-A-Six well plate, That magnetically levitates over a track. You have sort of millime…”

“At Lila, the fun thing is that the lab instruments are also tool calls or a series of tool calls for a workflow or but it's all human legible. It's all in English.”

“Because we have written our own custom drivers, our own custom firmware to get sort of low level granular control over a lot of these instruments and make them talk to each other.”