Alex Peysakhovich urges AI researchers to shift to biology
Alex Peysakhovich, partner at Sutter Hill Ventures and former Meta FAIR scientist, posted that AI researchers should consider moving into biology. He highlighted large pretraining datasets that enable experiments without heavy cluster optimization and an active post-training phase where lab validation serves as the main benchmark. Existing AI tools have already accelerated biological work. Engineer Bilal reposted the message, while Michelle Lee quoted it and noted that large-scale post-training capabilities will soon become available.
#1106Michelle Lee@MICHELLEARNINGand soon we will provide post training at scale
alex peysakhovich@alex_peysif you’re an ai researcher you should really consider working on bio pretraining is great: data sets are big enough for interesting stuff but not so big you’re spending all your time on weird cluster optimization post training is in the age of research: the lab is the only true validation, but it’s expensive so figuring out the limits of what we can do for evals in silico is still very open question existing stuff kind of works: we have proof of life for the ability of ai to accelerate bio but there is a long way to go it feels a lot like computer vision after imagenet or nlp after the first transformers started really working if your idea works, you might get to help improve the human condition. way cooler to talk about at parties than “we pushed benchmark X for chat model Y up by 3 point”
#1754alex peysakhovich@ALEX_PEYSif you’re an ai researcher you should really consider working on bio
pretraining is great: data sets are big enough for interesting stuff but not so big you’re spending all your time on weird cluster optimization
post training is in the age of research: the lab is the only true validation, but it’s expensive so figuring out the limits of what we can do for evals in silico is still very open question
existing stuff kind of works: we have proof of life for the ability of ai to accelerate bio but there is a long way to go
it feels a lot like computer vision after imagenet or nlp after the first transformers started really working
if your idea works, you might get to help improve the human condition. way cooler to talk about at parties than “we pushed benchmark X for chat model Y up by 3 point”
@jvarga92 just work with a biologist, the whole point of a team is that not everyone can do every role