why aren't all 7 resolved? a statement only gets an assessment when the public
record can support or contradict it. opinions and what-ifs never can, and 0 checkable
ones are still open, waiting for their date. predictions held up or didn't;
assertions are supported or contradicted. on every card:
▮▮▮▮▮ certainty ·
▮▮▮▮▮ debate potential. speakers are clickable
Assertion Not checkable as stated
Beam: Lila's AI hits 80% zero-shot on gene editing, beating humans' 0%
“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.”
Assertion Not checkable as stated
Beam: Lila's best non-platinum electrocatalysts came from AI ideas experts called stupid
“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…”
Assertion Not checkable as stated
Beam: Lila's 10-trillion-token general science model beats specialized AI
“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…”
Assertion Not checkable as stated
Beam: Lila's in vivo CAR-T data outperformed Capstan in non-human primates
“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 …”
Prediction Not checkable as stated
Beam: Round-over-round experimentation yields more compound value than broad datasets
“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…”
Assertion Not checkable as stated
Beam: Lila Sciences likely holds a top 3 global biopharma GPU cluster
“I think that, you know, if we called ourselves a biopharma, we probably would have a top three GPU cluster in the world.”
Assertion Supported
Beam: Reinforcement learning achieves only 5% to 6% GPU FLOP utilization
“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.”