#241 – Richard Moulange on how now AI codes viable genomes from scratch and outperforms virologists at lab work — what could go wrong?
episodePreviously titled “AI designs genomes from scratch & outperforms virologists at lab work. What could go wrong? | Dr Richard Moulange, CLTR” — renamed by the publisher on Aug 4, 2026
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What is discussed at the start of this section?
I must disagree strongly when people say nature is the world's worst bioterrorist. That is not true. We can do worse than nature. This is true in all aspects of science. There are so many examples where we engineer things better than nature has ever provided. We can make materials that are much stronger than anything in nature. That is not the ceiling. And so we should be deeply concerned about the ability for AI to uplift, say, even the Russian Federation, to build things worse than we have ever seen on Earth.
Today, I'm speaking with Richard Melange. Richard has a PhD in biostatistical machine learning from Cambridge and works as the AI biosecurity policy manager at the Center for Long-Term Resilience. He's one of the world's top experts on biological catastrophes that might be enabled by AI advances and is a scientific contributor on exactly that topic for the International AI Safety Report. Welcome to the show, Richard.
Thank you, Rob. It is absolutely great to be here.
I should say at the outset that, weirdly enough, my wife is a colleague of yours. She is indeed. And I guess she's a co-author on some of the papers that we're going to be talking about today. So I guess a conflict of interest disclaimer. I don't think that will cause me to go any easier on the papers. If anything, probably the opposite. Please do, yes.
I'm ready to hear all the criticisms.
So last September, a paper came out where scientists said they'd used AI to make a genome for a new subspecies of virus, a virus that infects bacteria. They then actually made a bunch of those viruses and found that quite a lot of them were viable. Tell us more about that experiment.
This was some really impressive work and is really a step change, I think, in the AI biosecurity intersection domain. So the model you're talking about is EVO2, and it's made by folks at ARC Institute in the US, which is one of the top places in the world now for making this kind of thing. EVO2 is what we would call a genomic language model. So much like LLMs, ChatGPT, CLAW, take your pick, process natural language. EVO and EVO2 process the language of biology. There are a number of different languages, but the one this one does is literally what are called base pairs, nucleotides, the A's, C's, G's, and T's that make up DNA and RNA that are the language of life. And EVO2 is trained on many hundreds of thousands of genomes across lots of different types of organisms.
So it's not just humans or mammals. There's fungi, there's plants, there's viruses and there are bacteria and a few other more esoteric ones too. And what's... Impressive and a little bit concerning about this result is what the team were able to do was that they had the base EVO2 model and then they fine-tuned it on what are called bacteriophages. So these are viruses that eat, that kill bacteria. fine-tuned it on maybe something like 15,000 of those, and then started prompting it with the beginnings of known bacteriophage genomes to see if they could make new ones. So this is, again, akin to with LLMs. You say, okay, well, write me a story about this kind of topic. You know, I don't know, a murder mystery.
And then you start with, you know, a classic opening sentence and see where the LLM takes you. It's the same kind of thing. And what they did is they discovered the sequences that the model produced are going to be new. They're going to be different than existing genomes. And this is huge because this is the first time that an AI design of a genome has turned out to actually work. be novel. It really is very different than existing bacteriophages, existing viruses. I think the most different one was 7% different than anything that we've seen in nature before. And they work in the lab. And more than that, it didn't just make viable genomes. They worked better. They functioned better than the best bacteriophages that we already know.
So these bacteriophages, they're viruses that kill E. coli, a very common bacterium that you hopefully don't find in your home, but you have to watch out to kill it with bleach, this sort of thing.
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Chapters
8 chapters
1
What is discussed at the start of this section?
0:00–5:32
2
How does AI design genomes for new viruses?
5:32–58:26
3
What does the Virology Capabilities Test reveal about AI and virologists?
58:26–1:13:18
4
How is AI changing the landscape of biological weapons?
1:13:18–1:33:55
5
What are the best practices for AI safeguards against biological misuse?
1:33:55–1:34:19
6
How can AI companies enhance their biosecurity measures?
1:34:19–1:34:35
7
What are the potential advancements in bio-defensive technologies?
1:34:35–1:35:20
8
How can individuals contribute to AI biosecurity efforts?
1:35:20–3:07:50
Speakers
3 identifiedMore from 80,000 Hours Podcast
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