Imagine\u00a0being able to speed up evolution \u2013 hypothetically \u2013 to learn which genes might have a harmful or beneficial effect on human health. Imagine, further, being able to rapidly generate new genetic sequences that could help cure disease or solve environmental challenges. Now, scientists have developed a generative AI tool that can predict the form and function of proteins coded in the DNA of all domains of life, identify molecules that could be useful for bioengineering and medicine, and allow labs to run dozens of other standard experiments with a virtual query \u2013 in minutes or hours instead of years (or millennia).<\/p>\n\n\n\n
The open-source, all-access tool, known as Evo 2, was developed by a multi-institutional team co-led by Stanford\u2019s\u00a0Brian Hie<\/a>, an assistant professor of chemical engineering and a faculty fellow in\u00a0Stanford Data Science<\/a>. Evo 2 was trained on a dataset that includes all known living species, including humans, plants, bacteria, amoebas, and even a few extinct species. Stanford Report talked to Hie about Evo 2\u2019s advanced capabilities, why the scientific world is so eager to get its hands on this new tool, and how Evo 2 could reshape the biological sciences.<\/p>\n\n\n\n Read it all<\/a>.<\/p> Just now: @arcinstitute<\/a> and @nvidia<\/a> release Evo 2, the largest AI model for biology. It is fully open-source.
Evo 2 can predict which mutations in a gene are likely to be pathogenic, or even design entire eukaryotic genomes.
We covered it in @AsimovPress<\/a>! Check it out 🔻 pic.twitter.com\/hBJkrtNVr0<\/a><\/p>— Niko McCarty 🧫 (@NikoMcCarty) February 19, 2025<\/a><\/blockquote>