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MTS · 3 min · Oct 20, 2026

AI discoveries need physical labs to become scientific progress

NT

Nenad Tomašev

Senior Staff Research Scientist, Google DeepMind

Theo JaffeeHost · Co-founder & host, MTS
One of the first members of a16z's new media team; earlier hosted the Emergent Ventures-backed Theo Jaffee Podcast.
Sophia DewHost · Host, MTS

About this segment

Tomašev argues that AI can generate hypotheses faster than many fields can test them. Scientific progress also requires investment in experts, laboratories and the wider research ecosystem.

From “AI Science Requires Physical Labs To Scale | Nenad Tomašev”, Oct 20, 2026. Watch the full episode

“you need to have physical laboratories to validate those findings or disprove them, because at the end of the day, some of them will also be false.”

NTNenad Tomaševat 3:59 · MTS3:59

Takeaways

Many scientific findings need physical experiments for validation.
AI can produce more hypotheses than researchers can process.
Invest in labs and scientific expertise alongside AI.

Watch 2:42 from 2:04

In this episode

2:04AI discoveries need physical labs to become scientific progress2:42
11:57AI alignment should leave room for social values to evolve3:39Up next
21:43Agent swarms need structure to stay manageable3:54
3 more moments in the full episode

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

2:06
about yeah totally so um you guys wrote a paper um called agentic ai in the public interest which is a really huge topic right now we had a lot of like philanthropic news come in today a lot a lot of you know this public good public benefit thing is very on the top of our minds so you guys argued here that there's a lack of societal and institutional ai readiness and i'm curious what you guys discovered through writing this paper about some of the things that could mend this.
2:42
Yes, so that paper is a viewpoint. It's a personal viewpoint, but I sort of believe that things are changing very rapidly. You know, we who are in the midst of it are sometimes struggling to keep up with all of the updates. So it should come as no surprise that the broader society also cannot follow every single development to the same extent. so there is some sort of a lag maybe behind the frontier it's very normal it's been the case for every you know single technological revolution but the core premise of that paper is that intelligence while it is an enabler and what we argue for in the paper is in particular that it's an enabler for advancing research opening up all sorts of discoveries whether it's in areas like biomedicine or material science or other domains of science that it needs to be followed by similar investments in the infrastructure to deliver on the promise.
3:37
In particular, you know, we've done lots of work here and lots of work has been done elsewhere in the community on agentic AI to autonomously derive some new hypotheses and insights, many of which can be used to advance discovery in practice. But then for many sciences that are not strictly computational and the strictly computational science, I think. Like mathematics or computational physics, you need to have physical laboratories to validate those findings or disprove them, because at the end of the day, some of them will also be false.
4:10
So if we put all of the investments on the AI side of the equation, we're going to have a world where we have many more hypotheses and conjectures that we can actually process downstream from that. So we're trying to make an argument that one needs to have both. So the broader scientific community needs also to see investment, more people, more experts, more laboratories, just a broader ecosystem. And I think that's one illustration of how actually the entire society can benefit from the progress as it's happening, because the growth should be happening in all sorts of places.