Andrew White
Co-founder & Head of Science, FutureHouse · 1 appearance on the record.
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scientistfounderacademicauthor@andrewwhite01 ↗diffuse.one ↗
Andrew White develops artificial intelligence systems and autonomous agents for scientific discovery, having created tools such as ChemCrow, PaperQA, and Kosmos. A former chemical engineering professor at the University of Rochester and GPT-4 red-teamer at OpenAI, he co-founded FutureHouse to automate biological and chemical research.
48statements → 16claims → 10claims resolved → 90%fully supported → 3.65/5average certainty → 2.33/5average debate potential → 1said about them ↓
9 supported 1 partly supported 0 contradicted 2 not yet assessed 4 not checkable as stated how the 16 claims stand · each chip opens the sources
2 predictions · 14 assertions · 11 opinions · 16 insights · 5 disclosures · every statement was checked. The predictions and assertions are the 16 claims: statements the public record can support or contradict. 10 are resolved, 2 are not yet assessed, and 4 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.
The record, in short
What the tape says about how Andrew argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.
Their most notable supported claim
Expressed certainty vs assessment result
weighted support: a fully supported claim counts one, a partly supported claim counts half. Each filled bar is clickable and opens exactly those claims; "none yet" means nothing said at that certainty level has resolved yet
Everything Andrew White said on Latent Space that made the record, most notable first. Filter by type, assessment or year in the ledger →
White: Molecular dynamics and DFT are overrated in materials science
“So, I think molecular dynamics is overrated. And DFT is overrated. In fact, DFT may be even more overrated than like the dynamics.”
White: AI for Science Is Difficult in Academia and Demands Bigger Bets
“AI over science is just, I think, A, difficult to do in academia, and B, so exciting, but I think you can take bigger bets, and I think having a tenured position and writing research grants is maybe not the biggest bet you can take on, on a field.”
White: Existing LLMs Are Already Capable of Automating Much of Science
“We can actually automate so much of the scientific method, because it turns out, especially in a field like biology, which is very empirical limited, you know, the top one percent guesser of, you know, what they think will happen in experiment that, you know, …”
White: AI Science Agents Do Not Require Bespoke Automated Labs
“We don't actually have to hold their hands so much anymore, or like they don't actually need to necessarily have an automated lab. They can like write an email to a CRO or something, or they can like tell you what experiment to do. And you can take a video of …”
White: Simulating biological systems hits fundamental limits; empirical lab measurement is unavoidable
“Basically the best model whatever, Opus seven or GPT 10, like it really can only propose the first experiment, maybe slightly more clever, but at a certain point you just need information, right? Like some little calculations you can do that, like, there's mor…”
Logistics Data Matters More Than Frontier LLM Intelligence in Lab Science
“I think whether GPT, 5.2 codex max or Opus 4.5 is going to do better. It's probably doesn't matter. It's just a matter of like, which one's going to have all the information about what's in the lab and how much will it cost? How long will it take?”
White: RLHF fails on scientific hypotheses by ignoring impact and information gain
“We learned a lot about how bad our LHF is with people, just like people pay really attention to the tone, to the details, to like how many specific facts or figures on the hypothesis, right? Like actionability about like if the experiment is feasible, but what…”
White: Verifiers in the loop provide higher signal than hypothesis rankings
“I have a lot more faith in these, like verifier-in-the-loop kind of scenarios where you have either data analysis, literature search, or you're running a unit test, or whatever, you're going and running the experiment. Anything like that, I think, is going to …”
White: A world model serves as unifying glue for scientific agents
“In cosmos, we basically, we had all the pieces sitting around. We working on world models, we working on data analysis agent, working on literature agent. And then we're working on, you know, we built a platform for scientific agents. So we had things that can…”
White: ML trained on experimental data beat first-principles simulations by a large margin
“Two very well-resourced groups. They both tried different ideas, and the machine learning on experimental data beat out first principles simulation by You know, a very large margin.”
White: Synthesis routes for dangerous compounds are already available on Wikipedia
“You can go find the synthesis route for many dangerous compounds on Wikipedia. People know what are the targets in the human body that, like, are targeted by most biological weapons. It's not really that much of a mystery.”
White: New AI laboratory risk scenarios have become realistic
“To some extent, there was like a first wave that we thought this could unlock a lot of stuff and I don't think it came to pass. I think there's now an emerging sort of second wave of like, there are some actually new scenarios that were just too farfetched to …”
Andrew White: Automating scientific discovery will increase overall demand rather than displace jobs
“In science, I don't think there is a finite appetite or a finite capacity for science. I don't think science is like a scarcity thing. Like there's, you know, 100 more discoveries left to be made and then we'll be done. And so like we're displacing jobs. I thi…”
White: FutureHouse bypassed custom foundation models to focus on scientific agents
“For example, at future house, we took the opinion that scientific agents are the future, and that allows us to skip a lot of steps because a lot of other people were like, we need to build a foundation model for X. Yeah. And we just skipped all that.”
White: ChemCrow paper was presented to U.S. President in 30-minute block
“I ended up visiting the white house. I guess my paper was like the only time a preprint or peer review paper was presented to the president on like their schedule for like a 30 minute block.”
White: Co-Scientist uses LLM ranking while Robin filters with data and literature
“In co-scientists, their filtration process was other LLMs sort of ranking it with rubrics or like personas. And our filtration process was like literature search and data analysis.”
White: LLMs Filter Scientific Hypotheses as Well as Human Domain Experts
“Nowadays, I actually would argue that if you go to an LLM and you ask it to evaluate, you know, hypotheses, including some garbage ones, it will probably do as good of a job as an expert in the field and filtering them out. That's not always the case.”
White: AI hits 60-70% on Bixbench, matching human expert agreement
“We're getting to 60%, 70% correctness on Bixbench, and we found that actually we're at the point where humans disagree at this level. Like, humans only agree 70% of the analysis, and so it's true that, like, when it comes to analyzing data, like, humans do not…”
White: Medicinal chemistry is an AI-resistant field driven by superstition
“You want to know what the real modern dark arts are that like AI resistant area of the world is like a medicinal chemistry that is like, The spot where, like, you know, there's so much superstition.”
White: Simulations model boring things well but fail on interesting phenomena
“So I think this is one of the fundamental, I don't know, dichotomies of the world is that simulations stimulate really boring things really well. They don't simulate interesting things very well.”
White: A good protein folding model can be trained in ~10,000 GPU hours
“I think the numbers are now like 10,000 GPU hours you can train a good protein folding model. It's actually turned out to be barely an inconvenience.”
White: LLMs do not meaningfully accelerate physical CBRN and nuclear threats
“The classical example of nuclear is like, it's a lot of centrifugation, a lot of ultra centrifugation, a lot of high pressure or high RPMs. And so it, It's just, you can maybe get smarter about how to set up, you know, the economy of scale to do that with an L…”
Andrew White: Funding $1M+ Cash Salaries With VC Equity Is Insane
“There are some venture backed companies that are having cash salaries over a million dollars. And it's like insane to me that you would use all of your cash from your equity financing You know, in these insane salaries.”
White: Scientists will remain active producers because they are the primary consumers of science
“I think the enjoyers of science are also scientists. And so I think that it's kind of hard to imagine a scenario when there's not scientists as the consumers of science. And so I think if they're going to be consumers of science, they're also going to be some …”
The other half of the tape: Andrew White's own voice is left out of every number here. Other people bring the name up 1 time in 1 episode on Latent Space. every mention, with the transcript →
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2026 1 mention in 1 episode
Appearances (1)
| Episode | Date | Speaking time |
|---|---|---|
| 🔬 From Red Teaming GPT-4 to Automating Drug Discovery: The Future of AI in Science — Andr | Jan 28, 2026 | 54m |