alt Hacker NewsI can explain how we do it at OpenAI.
In the API, we keep the models fixed. There are tiny caveats like rare bug fixes or models like `chat-latest`, but this is spiritually true. Suspicions of models changing over time are either human hallucinations or bugs on our end.
However, in ChatGPT, we sometimes update models without changing their names. For example, we recently launched an update to GPT-5.6 Sol in ChatGPT (https://openai.com/index/improving-gpt-5-6-sol-in-chatgpt/). Our goal isn't to be opaque or sneaky, but just to not exhaust people trying to keep track of little changes. When the changes are big, we give models a new name so that people know to expect something different.
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That's an good answer to the question when taken in strict terms of a model version = weights.
But, insofar as:
1. "a model" as presented to the user, isn't just its weights, but also anything else happening on the "business layer" (though this maybe applies more to ChatGPT than "direct" model access via the API); and
2. said business layer has any "knowledge base"-type stuff going on in it (i.e. automatic or tool-call-triggered embedding of results from search of some vector-DB into which has been embedded distilled pre-validated trustworthy info — like per-user memory mechanisms, but searching + injecting from global shared data sources); and
3. said "knowledge base" mechanisms are where most of the up-to-date, fast-changing info a model "knows" (without having to do a web search) is actually coming from;
...then do y'all ever update the pinned knowledge-base data snapshot associated with the model version, without updating the weights themselves?
Is there any scaffolding or harness runnning around the model on the cloud/server side? Seems like there's a lot of opportunity to make changes/improvements without making your customers call a different API or change the model parameter.
As an example, S3 team was able to migrate from eventually-consistent, to consistent without making any API changes, a complete re-architecture on the backend with 0 API changes.