Thomson Reuters bets $40M on Qwen-based proprietary AI model
The Decoder · rss · 2026-08-24
Thomson Reuters has launched "Thomson," its own language model built on Alibaba's Qwen, at a cost of about $40 million over two years. Benchmarks show top performance only when the model can tap into the company's proprietary content like Westlaw. CTO Joel Hron emphasizes that the key is not intelligence itself, but knowing which intelligence you need to own.
More from Companies & People
- University of Toronto hiring AI postdoc: builders of interventions, not just benchmarkers, due Oct 30 — ishtiaqueSIA · 2026-10-16
- Fluidstack hires Electrical Engineer for Modular R&D to build frontier AI infrastructure — MxMnr · 2026-10-16
- Databricks engineers land impactful PRs on day 2 with AI dev tools, vs week 3 before — Yuchenj_UW · 2026-10-16
- Jensen Huang joins BG2 podcast: does AI revenue justify capex, '27 bottlenecks — elonmusk · 2026-10-16
- Local media growth via Meta ads: UGC-style creatives win, exclusion targeting matters — TJLarkin23 · 2026-10-16
- Anthropic grants METR employee-like access as independent safety evaluators go public — AnthropicAI · 2026-10-16