John Jumper, who won the Nobel Prize "for protein structure prediction", says he is leaving Google DeepMind after nearly nine years to join Anthropic (John Jumper/@johnjumpersci)
John Jumper / @johnjumpersci : John Jumper, who won the Nobel Prize “for protein structure prediction”, says he is leaving Google DeepMind after nearly nine years to join Anthropic — A bit of news: After nearly 9 years, I have decided to leave Google DeepMind and join Anthropic (after taking some time to recharge). I am incredibly grateful for my time at GDM. @demishassabis took a real chance letting me lead the AlphaFold team just six months after finishing
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Record
| Original publisher | Techmeme |
| Canonical URL | https://www.techmeme.com/260619/p16#a260619p16 |
| Publication time | Fri, 19 Jun 2026 13:00:50 -0400 |
| Retrieval time | 2026-06-19T17:15:36.626Z |
| Last seen | 2026-06-19T17:15:36.626Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher description |
| Excerpt method | Publisher-supplied description / RSS summary field. |
| Summary | None yet |
| Summary source text | description |
| Citation coverage | No WeSearch summary has been generated for this story yet. |
| Cluster | J1c00z-NqmdB |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.