Why Simple Maths Keeps Beating Billion-Parameter AI Cell Models
A run of careful benchmarks shows that huge single-cell foundation models often fail to beat plain linear methods. Here is what the reckoning means for AI in biology.
Bioinformatics
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Your Genome Might Be Training an AI. Can Pipelines Keep Up?
Genome data is feeding AI models faster than privacy rules can follow. See how bioinformatics pipelines, federated learning and secure data access are adapting.
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How a Tiny DNA-Reading AI Beat Models a Thousand Times Its Size
UC Berkeley's GPN-Star, a genomic language model published in Nature, predicts harmful DNA variants better than far larger AI models, and trains in hours not months.
Stanford's SPHERE: A 'Synthetic Twin' to Unlock Sensitive Data for AI
Stanford's SPHERE turns locked biomedical datasets into shareable 'synthetic twins' for AI, and opens an Alzheimer's cohort to prove it. The promise, and the caveats.
