Alidoust: Protein AI is past GPT-3 while cell models are at GPT-1
Nima Alidoust · No Priors Ep. 103 | With Vevo Therapeutics and the Arc Institute · Feb 25, 2025 · at 55:50
Nima Alidoust, CEO of Vevo Therapeutics, benchmarks current AI biology milestones against the progression of OpenAI's GPT language model series.
0:00 / 0:12exact quote · 12.1s
▶ Watch the full episode on YouTube → 720p mp4 · rendered on demand · StarZero watermark
“I think in the protein, protein models, we are past GPT-III. when it comes to single cell models and virtual cell models, yeah, I think GPT-I to two right now. I think we're closer to GPT-I than two.”
quote is from the automated transcript, cleaned for reading: filler sounds and stutters are removed, nothing is rephrased. names can be misheard (the analysis reads context, assessments check outside sources). how →
More from Nima Alidoust
Alidoust: Hypothesis-driven biology slowed progress, but falling costs enable unbiased data
“One thing that has been a Has been slowing the progress in bio is the fact that we have always been super hypothesis driven, and I think it has, the reason is that a lot of these experiments are expensive, you know, that they take a lot of time, a lot of resou…”
Alidoust: Single-cell AI performance holds even after 99% data downsampling
“If you actually reduce the number of the sixty million, you down sample it by like, Even 99%. You know, you just use one percent of that data to train your models. Actually, the model's performance doesn't reduce that much. So it means that the information con…”
Alidoust: Tahoe dataset expands public perturbational single-cell data fiftyfold
“I think when you put all of the perturbational data sets in the world together if you're generous, it's like one to two million single cell data points. And this is publicly available data. We don't know as much about, you know, what, what's inside different o…”
Alidoust: Virtual cells will expand AI drug discovery to systems biology
“Virtual cells, in my opinion, are going to allow us to go beyond the language of structural biology and venture into the language of systems biology and understand how how the drug is interacting with the broader biological system.”
Alidoust: Prior public single-cell data totaled only 45M to 60M cells
“Before that, I think the number of human cells that we had, had been collated together it was in the order of 45, fifty million, if you are generous, sixty million single cell data points.”
Alidoust: 100 million single-cell data points equate to 200-300 billion tokens
“Think of it like a cell collection of for this data says 2000 to 5000 genes, and each gene and its expression is basically a token in what we're doing. So 200, like a hundred million single cell data points is akin to around 200 to three hundred billion tokens…”