• eval — A repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.
• open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.
• benchmark — A standard public test set for comparing AI models — the shared scoreboards behind every "model X beats model Y" claim.

Teams building forecasting into products get a permissively licensed, benchmark-verified foundation model deployable zero-shot, avoiding the cost of training a bespoke model per dataset.

• articleReal-Time Intelligence with IBM Time Series Models on Confluenthuggingface.co
• articleGranite 4.2 LLMs: How They're Builthuggingface.co
• postTencent relicenses Hy-MT2 translation weights under Apache 2.0Tencent Hy

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