The ProGen Revolution refers to a major paradigm shift in biotechnology where artificial intelligence treats the genetic code of life as a literal language. Originally developed by Salesforce Research in 2020, ProGen is a family of large language models (LLMs) trained not on English text, but on hundreds of millions of biological sequences.
Instead of predicting the next word in a sentence, ProGen uses next-token prediction to predict the next amino acid in a protein chain. This approach bypasses billions of years of slow natural evolution, allowing scientists to generate entirely new, functional proteins from scratch. How ProGen Decodes the “Language of Life”
The core philosophy behind ProGen is that biological sequences are not random; they possess a distinct “grammar” shaped by evolution. If an organism carries a broken, non-functional protein, it does not survive, meaning nature filters out the “gibberish”.
Massive Scale Pre-training: The initial model was trained on 280 million protein sequences across 19,000 different families. Scaling up, newer iterations like ProGen3 have expanded to 46 billion parameters trained on over 1.5 trillion amino-acid tokens.
Conditional Tags: To control what the AI creates, researchers append specific tags specifying the protein’s desired traits, such as its taxonomic family, cellular location, or function.
Generative Writing: Like an AI writing a custom essay, ProGen reads the instruction tags and types out a brand-new, customized string of amino acids. Real-World Validation: Beating Natural Evolution
AI Proteins: Unlocking the Potential of Protein Generation … – CBIRT
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