01680nas a2200277   4500000000100000000000100001008004100002260001500043653001800058653002100076653002100097100002300118700001700141700002000158700001900178700001200197700001400209700001900223700001800242700002100260245008300281856005500364300000900419520096000428022001401388       2026                            d  c2026-03-2010aBiotechnology10aMachine Learning10amedical research1 aVishwanatha M. Rao1 aSerena Zhang1 aBrian S. Plosky1 aPatrick D. Hsu1 aBo Wang1 aJames Zou1 aMarinka Zitnik1 aEric J. Topol1 aPranav Rajpurkar00aGeneralist biological artificial intelligence in modeling the language of life  uhttps://www.nature.com/articles/s41587-026-03064-w  a1-163 aGeneralist biological artificial intelligence (GBAI) represents a transformative approach to modeling the ‘language of life’—the flow of information from DNA to cellular function. This Review synthesizes rapid advances in biological AI to interpret and generate DNA, RNA, proteins and cellular systems. We chart a course toward comprehensive systems that can concurrently process and predict across these domains, performing several critical biological tasks simultaneously. Substantial opportunities lie in synergizing language and structural AI, leveraging specialized models and improving AI agents for autonomous discovery. After addressing challenges in data, biological complexity, scalability and experimental validation, GBAI has the potential to deepen our understanding of disease pathways and biomarkers, advance automated therapeutic design and evaluation, and integrate within virtual cells to meaningfully simulate biological activity.  a1546-1696