This is just marketing nonsense. You don't have to train models to not retain personal information. They simply have no memory. In order to have a chat with an LLM, every time the whole conversation history gets reprocessed - it is not just the last answer / question gets send to the LLM but all preceding back and forth.
But what they do is exfiltrate facts and emotions from your chats to create a profile of you and feed it back into future conversations to make it more engaging and give it a personal feeling. This is intentionally programmed.
> In order to have a chat with an LLM, every time the whole conversation history gets reprocessed - it is not just the last answer / question gets send to the LLM but all preceding back and forth.
Btw, context caching can overcome this, e.g. https://ai.google.dev/gemini-api/docs/caching . However, this means it needs to persist the (large) state in the server side, so it may have costs associated to it.
I think they mean that they trained the tool-calling capabilities to skip personal information in tool call arguments (for RAG), or something like that. You need to intentionally train it to skip certain data.
>every time the whole conversation history gets reprocessed
Unless they're talking about the memory feature, which is some kind of RAG that remembers information between conversations.