AI designed viruses outpace nature - and US biosafety rules don’t cover them
In a lab at Stanford University, researchers watched clear spots spread across a petri dish full of bacteria — the unmistakable sign that something they had built entirely inside a computer had just come to life. The organisms wiping out that bacteria weren’t pulled from nature. They were AI designed viruses, generated by a computational model called Evo and then chemically built from scratch, and the results are now raising questions that go far beyond one Stanford basement lab.
Key takeaways
- Evo, an AI model developed by Stanford University and the Arc Institute, proposed 700,000 possible viral genomes, of which 285 were chemically synthesized and 16 produced viruses able to replicate and kill bacteria.
- Evo was trained first on roughly nine trillion nucleotides from millions of animals, plants, microbes and viruses, then specialized on the 11 genes of the bacteriophage Phi X-174 and about 15,000 related genomes.
- The AI-generated viruses were as robust as natural ones, and some replicated faster than the natural phage Phi X-174 itself.
- Current US National Institutes of Health biosafety rules ban experiments that make pathogens more dangerous, but they don’t clearly cover purely computational virus design unless it involves an “entity of concern.”
- Experts, including Moritz Hanke of the Johns Hopkins Center for Health Security, warn of a growing gap between what AI can now do and the rules meant to police it.
AI Model Evo Designs Novel Viral Genomes for Bacteria
Evo works like a genetic version of a large language model, predicting sequences of DNA the way ChatGPT predicts the next word in a sentence. Instead of language, though, it learned the patterns written into the genetic code of life itself. The team behind it, based at Stanford and the Arc Institute, set out to see whether that kind of pattern recognition could go a step further than designing individual proteins or antibiotics — and actually produce a working virus.
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