Collective intelligence for AI-assisted chemical synthesis
A new computational framework called MOSAIC has been introduced to assist chemists in chemical synthesis. It utilizes collective knowledge from millions of reaction protocols and has achieved a 71% success rate in experimental validations. This model not only facilitates the realization of new compounds but also aids in discovering new reaction methodologies.
- ▪MOSAIC is built on the Llama-3.1-8B-Instruct architecture and trains 2,498 specialized chemical experts.
- ▪The framework delivers reproducible and executable experimental protocols with confidence metrics for complex syntheses.
- ▪MOSAIC has successfully realized more than 35 new compounds across various fields, including pharmaceuticals and materials.
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| Original publisher | Nature |
| Canonical URL | https://www.nature.com/articles/s41586-026-10131-4 |
| Publication time | Tue, 19 May 2026 15:01:14 +0000 |
| Retrieval time | 2026-05-19T15:14:57.682Z |
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Article Published: 19 January 2026 Collective intelligence for AI-assisted chemical synthesis Haote Li ORCID: orcid.org/0000-0002-8146-50661 na1, Sumon Sarkar1 na1, Wenxin Lu ORCID: orcid.org/0000-0001-6388-77431, Patrick O. Loftus ORCID: orcid.org/0009-0009-5952-10901, Tianyin Qiu ORCID: orcid.org/0000-0002-3490-84691, Yu Shee1, Abbigayle E. Cuomo1, John-Paul Webster1, H. Ray Kelly ORCID: orcid.org/0000-0003-3811-06622, Vidhyadhar Manee2, Sanil Sreekumar2, Frederic G. Buono2, Robert H. Crabtree ORCID: orcid.org/0000-0002-6639-87071, Timothy R. Newhouse ORCID: orcid.org/0000-0001-8741-72361 & …Victor S.
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