Are embeddings used for RAG considered company data (presumably calculated by OpenAI), or OpenAI’s?
(I don’t know if that’s how RAG actually works)
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Are embeddings used for RAG considered company data (presumably calculated by OpenAI), or OpenAI’s?
(I don’t know if that’s how RAG actually works)
The problem here is that there are companies that focus on this area and keep improving their products, while for OpenAI it's one of dozens of tools they launch, so it's hard to believe they'll keep dedicating adequate resources to make this a mature tool that's worth the investment (in form of time and money) for the clients
[1]: https://www.reuters.com/technology/openai-tells-investor-not...
And in the next episode of "Pointlessly Searching For The Killer App"....
Claude memory was posted 16 hours before this, kinda crazy how fast they churn this stuff out
> It’s powered by a version of GPT‑5 that’s trained to look across multiple sources to give more comprehensive and accurate answers. So another GPT-5 fine-tune. Codex also uses a custom GPT-5 fine-tune. Does fine-tuning make sense now? Or do you have to be OpenAI to fine-tune the models with a mix of existing data and new behaviours?
Look at Tinker for an example of where things might be heading though (https://tinker-docs.thinkingmachines.ai/)
At present though, I get the sense that reinforcement learning at scale is the current battleground (and has been for most of 2025). But we also see over time, the general models adopt the skills taught to the specialized models. Look at how the learning that made codex-1 went into GPT5.