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“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…”

“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 …”

“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?”

“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?”

“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.”