Draft:ESM3
Wikipedia articles must be written neutrally in a formal, impersonal, and dispassionate way. They should not read like a blog post, advertisement, or fan page.
Submission declined on 29 May 2026 by Ethmostigmus (talk). This draft reads like an advertisement. Wikipedia is an encyclopedia, not a platform for promotion or marketing. Drafts that are exclusively promotional may be deleted without notice.
Wikipedia articles must be written neutrally in a formal, impersonal, and dispassionate way. They should not read like a blog post, advertisement, or fan page. Rewrite the draft to remove:
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Comment: This is an interesting topic, but this draft needs to be rewritten in a neutral tone based on independent coverage in reliable sources. Ethmostigmus 🌿 (talk | contribs) 06:44, 29 May 2026 (UTC)
ESM3 (Evolutionary Scale Modeling 3) is a family of biological large language models developed by EvolutionaryScale, an artificial intelligence company founded by former researchers from Meta's AI division[1]. Introduced in June 2024, ESM3 is a multimodal generative AI system designed to simulate, understand, and generate novel proteins by simultaneously reasoning across their sequence, structure, and biological function[2]. Having been trained on billions of naturally occurring proteins, the model allows scientists to effectively "program" biology, facilitating the design of new enzymes, therapeutics, and synthetic molecules with highly specific, customizable traits.
References
- ^ "ESM3 — The Frontier of Protein Design?". www.ml6.eu. Retrieved 2026-05-28.
- ^ Hayes, Thomas; Rao, Roshan; Akin, Halil; Sofroniew, Nicholas J.; Oktay, Deniz; Lin, Zeming; Verkuil, Robert; Tran, Vincent Q.; Deaton, Jonathan; Wiggert, Marius; Badkundri, Rohil; Shafkat, Irhum; Gong, Jun; Derry, Alexander; Molina, Raul S.; Thomas, Neil; Khan, Yousuf A.; Mishra, Chetan; Kim, Carolyn; Bartie, Liam J.; Nemeth, Matthew; Hsu, Patrick D.; Sercu, Tom; Candido, Salvatore; Rives, Alexander (2025). "Simulating 500 million years of evolution with a language model". Science. 387 (6736): 850–858. Bibcode:2025Sci...387..850H. doi:10.1126/science.ads0018. PMID 39818825.
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