The Ledger, every show

“I think in many ways the kind of pitch and the framing of these companies precedes The fundamental research capability breakthroughs.”

“The vast majority of, you know, mechanistic data that's been generated to date is really made to ask very specific, very well scoped questions and just, you know, way more tokens per experiment is, you know, just, it's just going to be the way to do it.”

“I find it helpful to frame these in terms of like GPT one, two, three, four, five capabilities, right? And I think most people would agree we're somewhere between GPT one and two, right?”

“The first is the amount of market cap added to Lilly and Novo based on the, you know, development of GLP ones. It's like over a trillion dollars is, is more, you know, I mean, NOAA stock has decreased a lot. So you know, trillion dollars, let's say, is more th…”

“If we play this out, right? And let's say these AI models work, right? And you can make a trillion binders in silico that will, you know, be exquisite drug matter, right? We still need to make these things physically and test them in animals and hopefully pred…”

“And I would say similarly with a virtual cell model, it may not tell me literally why, just like a alpha fold doesn't tell me literally why did the protein fold this way and how, but it just told me the end state and it was reasonably accurate. I think that wo…”

“People criticize these models for hallucinating, but if you think about it, the process of scientific research just involves hallucination, right? That's what creativity is.”

“We've, we're seeing evidence of scaling laws in biology across proteins, right? That's been shown in the protein language models across DNA, which is what we've shown in our EVO series of models from ARC. We're also seeing inference time scaling laws which in,…”

“I think it's very clear now that basically all dry lab workflows are going to get automated with agents or with co-pilots”

“Our moonshot is really to make virtual cells at Arc and simulate human biology with foundation models, and, you know, we'd like to figure out something that feels useful for experimentalists, people who are skeptical about technology, you know, they just want …”

“Folks have their own incentive structures, right? They need to publish their own papers. They need to do their own thing and, you know, make their own discovery and, You're not really incentivized to work together.”

“Natural language and video modeling is easier than modeling biology.”

“There are going to be different phases of capability where initially they model individual cells, then they model pairs of cells, then they model cells in a tissue, and then in a broader physiologically intact animal environment, and those are length scales an…”

“We weren't just going to be an engineering shop that's just trying to scale single cell perturbation screens, right? That You know, would be interesting, but in three years would feel very dated, I think, right?”

“I think virtual cells, if anything, is actually way more scoped and rigorous than modeling a digital twin or avatar.”

“Obviously, we want to be able to predict drug toxicity. We want to be able to predict aging. We want to be able to predict why a liver cell becomes cirrhotic when you repeatedly challenge it with ethanol molecules or whatever, right? And, you know, the, these …”

“And at ARC in the next, you know, kind of end, like, I don't know, relatively short amount of time, we're going to generate a billion perturbed single cells, right?”

“And then, you know, where there's hype is in Multimodal biological models, whatever that means, right?”

“Previously the virtual biotech was a concept that was very much in fashion, right? Folks found out just In reality, when you try to do this, even though it looks really good on paper, it's incredibly slow, right? So then folks tried the other way, which is let…”

“It's very hard for individual research groups or individual companies to be good at more than two things, right?”

“We have two flagship projects, one trying to find Alzheimer's disease drug targets, the other two make these virtual cells”

“There's heft in anything to do with proteins, right? Obviously protein binding, but increasingly in protein design, right? And I think there's real heft there.”

“I feel like in, you know, I mean, increasingly in just a few years, this will just be a native part of the stack, right? Just like we use You know, the internet and we use phones. We're going to have AI in all parts of the stack, right? And so it's just going …”

“Like, in biology, we ultimately have two ways to study it in high throughput. It's imaging and sequencing, right?”

“I would say the computer use agents will probably trail the coding agents by maybe a year, right?”

“We created our own virtual cell challenge at virtualcellchallenge.org where we have, you know, a 100,000 dollar prizes sponsored by NVIDIA and Tenex Genomics and Ultima and others.”