Thinking Machines Lab

An American AI start-up that builds tools for adapting existing models to particular uses and, unlike most frontier labsfrontier lab, n.: One of the handful of companies building the most advanced AI models of the moment, spending billions of dollars on computing power to train them., has promised to publish much of its research. Its first product, Tinker (October 2025), is a programming interface that lets researchers fine-tunefine-tuning, n.: Taking an AI model that has already learned a lot and training it a little more on a smaller, focused set of examples so it gets better at one job or behaves a certain way. open-weight modelsopen-weight model, n.: An AI model whose trained internal numbers are published for anyone to download and run on their own computers, even if the data and code used to make it stay private., including with low-rank adaptationlow-rank adaptation, n.: A cheap way to customize a big AI model: instead of changing all its billions of numbers, you train a small add-on of a few million numbers that slightly adjusts how it behaves., while the company runs the distributed training. Its Connectionism blog has published work on making language-model inference deterministic and on when LoRA matches full fine-tuning. In 2026 it released its first open-weight model, Inkling. The lab drew attention for raising one of the largest seed rounds on record and for losing several co-founders to Meta and OpenAI within its first year.