Join the GA4GH Cloud Work Stream for a focused session on Federated Learning (FL). FL enables collaborative model training across platforms without sharing raw data, improving privacy and leveraging GA4GH building blocks such as WES, TES, DRS, and Passports and AAI. The session will include a concise overview, a collaborative discussion to prioritise a backlog of follow-up work, and a hackathon to turn one to three high-priority items into prototypes or draft pull requests. Candidate hackathon tasks include an authorisation handoff demo between WES and TES, a compute-and-billing metadata exchange prototype, and a model write-back workflow to DRS with provenance and access control. Expected outcomes are a prioritised action list, potential external collaborators, non-FLWG collaborators, and at least one reproducible artifact or PR or prototype from the hackathon.