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Thomson Reuters built its own AI model on Chinese open-source tech to slash AI costs

The company spent $40 million to build Thomson, which is based on an open-source model from Chinese tech giant Alibaba

According to Business Insider, Thomson sits atop Snowdon, an intermediate model that Thomson Reuters built by reworking Qwen, an open-source offering from Chinese tech giant Alibaba. A joint team from Thomson Reuters and Imperial College London adapted Qwen over several months to ensure it was "ethically and politically de-biased and safe to use," Chief Technology Officer Joel Hron said.

Thomson Reuters spent roughly $40 million over two years on personnel and computing, the company said. The final training run cost approximately $450,000, according to SiliconAngle. The company chose to forgo developing a foundation model from the ground up, instead taking an existing open-weight model as its starting point and enriching it with proprietary content, specialized training methods, and domain expertise.

The model was trained on content from Thomson Reuters properties including Westlaw, Practical Law, Checkpoint, and Reuters, the company said. The process drew on hundreds of domain specialists who shaped what the model was meant to learn, supplied sample legal questions, and scored its outputs. So far, less than 10% of the company's total content library has been used in training.