The Ledger, every show

“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…”

“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 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…”

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

“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.”