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.
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.
> 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.
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.