Nvidia, Sheba Medical Center’s ARC Innovation and the Icahn School of Medicine at Mount Sinai launched a three‑year collaboration to develop a large language model (genomic Foundation Model, gFM) focused on regulatory mechanisms that link genetic variation to disease risk and therapeutic response. The partners will combine clinical genomic datasets, AI expertise, and computational infrastructure to accelerate interpretation of noncoding DNA and regulatory variants. The initiative will leverage Mount Sinai’s Million Health Discoveries Program and Sheba’s datasets with Nvidia’s full‑stack AI tools. The collaborators aim to produce an LLM optimized for genomics tasks—annotating regulatory elements, predicting variant impact, and suggesting mechanistic hypotheses—thereby shortening the gap between genomic signals and drug targets. A genomic foundation model, in this context, is a large AI model trained on genomic and functional datasets to predict regulatory effects and prioritize candidate mechanisms for disease and therapy development.