reproducibility

Today in AI for life science: an open, model-agnostic science workbench arrives as a rival to proprietary tools, a real open-vs-closed contest forms over the scientific AI stack, and why the lab’s whole bet is on open.

A framework that makes deep-learning pipelines for microscopy flexible, shareable, and reproducible across computing environments.