[{"id":"prov-gigapath","kind":"technology","name":"Prov-GigaPath (Microsoft, Providence)","route":"/technologies/prov-gigapath/","commit":"0bdbdae6c6","date":"2026-09-09","author":"Jude Gomila","message":"Editing pass: every TL;DR and summary stands alone","file":"src/data/foundation-models.ts","type":"changed","fields":[{"field":"summary","before":"\"Nature 2024. Trained on 171,189 slides from 30,000+ Providence patients; uses LongNet dilated attention to model entire slides. Open weights; strong on mutation prediction and cancer subtyping.\"","after":"\"Published in Nature in 2024, Prov-GigaPath was trained on 171,189 slides from 30,000+ Providence patients; uses LongNet dilated attention to model entire slides. Open weights; strong on mutation prediction and cancer..."}]},{"id":"prov-gigapath","kind":"technology","name":"Prov-GigaPath (Microsoft, Providence)","route":"/technologies/prov-gigapath/","commit":"b6e0a0fe48","date":"2026-09-08","author":"Jude Gomila","message":"Add foundation model entities and AI roadmaps","file":"src/data/foundation-models.ts","type":"added","fields":[{"field":"id"},{"field":"name"},{"field":"sections"},{"field":"status"},{"field":"since"},{"field":"tldr"},{"field":"summary"},{"field":"principle"},{"field":"strengths"},{"field":"limitations"},{"field":"links"},{"field":"companies"},{"field":"institutions"},{"field":"technologies"},{"field":"tags"}]}]