『AI-Designed Viruses』のカバーアート

AI-Designed Viruses

AI-Designed Viruses

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This week we talk about Evo 2, bacteriophages, and antibiotics.We also discuss AI models, medical innovations, and the Red Army.Recommended Book: The Design of Everyday Things by Donald A. NormanTranscriptA bacteriophage, sometimes just called a phage, is a type of virus that only infects bacteria. “Phage” means to devour, and that’s what bacteriophages do—they infect and replicate within bacteria that they target, injecting their own genome into that target’s cytoplasm, which are all the materials contained within the bacteria’s cell membrane.Phages are super-abundant, by some measures more abundant than every living organism, including bacteria, on earth, combined. And they’re interesting in that they range from incredibly simple to quite complex, and have at times been used as alternatives to antibiotics, because they attack and feed on bacteria.The use of phages to counter bacterial infections was all but abandoned in the mid-20th century when antibiotics were discovered and commercialized, their production industrialized and the substances themselves proving a lot easier to mass-produce, and a lot more predictable in their utility than phages. Phages were kinda sorta almost understood, but we didn’t really get what they were doing or why, so their application often felt more like folk remedies than real-deal science, despite the actual science underlying the practice.Also, phages were primarily used as antibiotic treatments by the Red Army, the Soviet Union’s military. So throughout the West, which was rapidly scaling its production of antibiotic treatments, the use of bacteriophages was associated with Stalinist communism, and so the Red-scare, the demonization of anything associated with the Soviet Union, was partially responsible for the shelving of this approach and this realm of research, at least for a while.Much of that existing research was also done in the Soviet Union, and the published documents were thus published in Russian or Georgian languages. And because much of the rest of the scientific publishing world was reorienting around English at this time, that meant these published works were often either ignored or unintelligible to the rest of the scientific community.As with much of our microbiota, the invisibly small viruses, bacteria, archaea, and so on that make up the human microbiome, we have a general sense of how bacteriophages interact with some of what makes us, us, but only a general sense. We know that healthy individuals tend to contain a host of bacteriophages that people who have chronic conditions, like Crohn’s disease or ulcerative colitis are less likely to have, for instance, and there’s a chance that this lack is associated with those conditions—though each person’s body composition is unique, and this facet of biology is still relatively obscure; we really don’t know for certain what does what, because of how complex these interactions are.What I’d like to talk about today is a recent development in the world of bacteriophages, and why the researchers behind it are both celebrating their accomplishment, and warning about potential dangers associated with the same.—Back in 2025, a nonprofit called the Arc Institute, which has a stated goal of accelerating scientific progress and understanding the root causes of complex diseases, announced the release of a new language model, a new AI system, called Evo 2.The Evo family of foundation models—a foundation model being a type of AI model that’s been trained on a huge corpus of data, but which is applicable for all sorts of purposes, including serving as the foundation of large-language models like ChatGPT or Claude—this family of foundation models is open-source and trained on raw genetic sequences, something like nine trillion nucleotides-worth of such sequences, making it distinct from other models in this space that have been trained on descriptions of biological systems, using human language.The initial version of Evo was released in early 2024, and the newest version, Evo 2, which is an upgraded version of the Evo 2 model that is more efficient, so it can be run on less powerful hardware, was released in February of 2026.So while many of the AI systems that non-biologists interact with on a regular basis have been trained on human language-based libraries, showing relationships and interactions between the words we use to communicate, these models have been trained on the fundamental building blocks of life; the nucleotides, Adenine, Thymine, Cytosine, and Guanine, ATCG of DNA, if you remember that from biology class, that are strung together into 64 different possible three-letter combinations. Chains of these nucleotides instruct cells to build proteins out of amino acids, and from that baseline, we get life.We also get non-living things like viruses, which have no cells, metabolism, or independent reproduction, and phages are viruses.And while other AI models have been shown...
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