“One is to have an external set of things that get to look at all of the model's actions and subject them to a symbolic, clearly stated constraint.”
BG
Bill Gates
Decoder with Nilay Patel ·
“You can run much more to inform what do you run next in the experiments… replace experiments… you can run less experiments and still look at a wider set of models”
The AI in Business Podcast · Turning Biological Complexity into R&D Advantage with Virtual Cells - with Giorgio Gaglia of Sanofi & Daniel Veres of Turbine
Play from 27:11
27:11
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What was described
state that virtual cell predictions can reduce the number of in-vitro experiments needed while still covering a wider set of models
Said nearby on the same subject
“If you have that set up, the moment that that happens, you fall back immediately and your users don't experience anything to a different model”
♫
Said on Applied Wizardry
“We trained models on internal data and then predicted on external data… total number of tests … like 13 million across 500 protein targets.”
IQ
Ian Quigley
Latent Space: The AI Engineer Podcast ·
“Selling enough to cover the profit you need ... popular and profitable ... we raised the price, bought feed in bulk, still losing money”
♫
Said on Growing For Market Podcast
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