“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 ·
Ian Quigley · Latent Space: The AI Engineer Podcast · Lab-in-the-Loop at Compute Speed - Ian Quigley, Leash Bio
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Assembled a benchmark set of ~13 M molecule-protein pairs covering ~500 targets to compare against the state-of-the-art Boltz model
13 M tests, ~500 protein targets
“We trained models on internal data and then predicted on external data… total number of tests … like 13 million across 500 protein targets.”
“Set up Rate My Clinic where people can get assessments done, find out how they compare on each of those different benchmarks. And importantly, recommendations on how to improve”
“We assembled the largest possible data set… 34 billion proteins… then you’d just use a hidden Markov model and match… Cas9”
“Only 1.6% of Torquay 1930 its triples break this rule, and 0.5% of Lama's, against 9% and 13% for the two base models.”
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