Arc Institute

“So Tahoe 100 is the world's biggest single cell RNA sequencing data set, and it enables basically a ton of machine learning applications, including things like the virtual cell, but it also enables a lot of drug discovery applications, and broadly in the conte…”

“We've created something called SC Basecamp and you can almost think of it like the Google crawler and index, so we've built this agent that goes onto the internet, And basically mines public single cell sequenced RNA data, and then curates it in a very sort of…”

“And so this data set, it is basically doubling the size of all the data that's out there cumulatively over the past decade. It covers 50 different cancer models from different patients, so it's cells from 50 different patients. 1200 drug treatments, so it's a …”

“And so I think our belief around the room is the right level of abstraction is at the sort of transcriptomic level because you have these very complex gene pathways. And so whenever a cell is changing to its environment reacting, that it will be reflected and …”

“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,…”

“When it comes to, for example, DNA language models, again, thanks to the field and decades of having sequenced a ton of genomes we are not as much data limited, but Compute and specifically context and how long we can actually consume DNA and what size of inpu…”

“Like, if you look at the EVO II model, we trained it on 9.3 trillion nucleotides, but we didn't tell it anything about DNA. We just like, here's a lot of DNA on the planet across, you know, every single piece of DNA we could get a hold of. And then what di…”