How AI Learns to Smell
TWIML AI Podcast · rss · 2026-07-09
Osmo founder Alex Wiltschko shared progress on giving computers a sense of smell in a recent podcast.
The team utilized graph neural networks and advanced embedding spaces to map molecular structures to odors, successfully building a foundational model for olfaction. They also created the largest proprietary olfactory dataset from scratch to train their predictive models. In the future, this technology could be applied in fields like disease detection, emotion perception, and consumer devices.
More from Research
- Structural ensembles beat single predictions in TCR:pMHC generalization study — quaidmorris · 2026-07-22
- Structural ensembles, not single predictions, drive robust TCR:pMHC generalization — quaidmorris · 2026-07-22
- enFoldX turns AlphaFold3 ensemble noise into a TCR–peptide–MHC predictor — quaidmorris · 2026-07-22
- RSS launches under OMSF to push structural biology data modeling at scale — MoAlQuraishi · 2026-07-22
- enFoldX tops 8 neoantigen scans and an unseen-peptide benchmark — quaidmorris · 2026-07-22
- enFoldX reaches AUC 0.82 on human VDJdb and transfers to mouse at 0.76 — quaidmorris · 2026-07-22