Self‑serve frontier fine‑tuning

Updated: 2025.10.02 20D ago 1 sources
Thinking Machines Lab’s Tinker abstracts away GPU clusters and distributed‑training plumbing so smaller teams can fine‑tune powerful models with full control over data and algorithms. This turns high‑end customization from a lab‑only task into something more like a managed workflow for researchers, startups, and even hobbyists. — Lowering the cost and expertise needed to shape frontier models accelerates capability diffusion and forces policy to grapple with wider, decentralized access to high‑risk AI.

Sources

Mira Murati's Stealth AI Lab Launches Its First Product
BeauHD 2025.10.02 100% relevant
Mira Murati and John Schulman describe Tinker as automating large‑scale fine‑tuning while exposing the training loop and keeping user control of data/algorithms.
← Back to All Ideas