Mira Murati’s Thinking Machines Lab Makes The Technical Case For Human-Centered AI Built On Customizable Model Weights


Thinking Machines Lab published a report to build AI that extends human will and judgment. Most AI in use today is trained in a handful of places, then frozen. The report argues that this design excludes the people a model serves. Instead, the Thinking Machines lab researchers want AI that is distributed, customizable, and shaped by its users.

Thinking Machines Lab’s Proposal

The lab names four technical directions. First, it trains strong models with multimodal interaction and customizability. Second, it builds tools that let people fine-tune and train model weights themselves. Third, it develops interfaces that widen the human-to-machine communication channel. Fourth, it publishes research so more engineers understand how models are made. Together, these directions move both knowledge and alignment closer to users.



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