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Current AI agents struggle to reliably rediscover scientific knowledge, with top performers averaging only 21.5 out of a possible score, revealing critical gaps in their research capabilities.
AI can now automatically reverse-engineer and rigorously validate complex biological simulations, pinpointing the key components driving performance with superhuman accuracy.
Virtual cell perturbation prediction gets a 12x speedup in pretraining and a 12% boost in biological fidelity with SCALE, a new foundation model that prioritizes scalable infrastructure and biologically faithful evaluation.
