Comment by baobun

You could definitely do this E2EE.

Models should run in ephemeral containers where data is only processed in RAM. For active conversation a unique and temporary key-pair is generated. Saved chats are encrypted client side and stored encrypted server side. To resume a conversation[0], decrypt client side, establish connection to container, generate new temporary key-pair, and so on. There's more details and nuances but this is very doable.

How Mullvad handles your data, for some inspiration: https://mullvad.net/en/help/no-logging-data-policy

  > Conversations are kept around because they can be picked up and continued at any point (I use this feature frequently).

I'm not sure why this is a problem. There's no requirement that data at rest needs be unencrypted. Nor is there a requirement that those storing the data need to have the keys to decrypt that data. Encrypted storage is a really common thing...

  > Additionally you can use conversations in their scheduled notification feature, where the conversation is replayed and updates are sent to you, all done on the server.

For this we can use the above scenario, or we can use a multi-key setting if you want to ping multiple devices, or you can have data temporarily decrypted. There is still no need to store the data to disk unencrypted or encrypted with keys OAI owns.

Of course, I also don't see OAI pushing the state of Homomorphic Encryption forward either... But there's definitely a lot of research and more than acceptable solutions that allow data to be processed server side while being encrypted for as long as possible and making access to that data incredibly difficult.

Again, dive deep into how Mullvad does it. It is not possible for them to make all their data encrypted, but they make it as close to impossible to get, including by themselves. There doesn't need to be a perfect solution, but there's no real reason these companies couldn't restrict their own access to that data. There's only 2 reasons they are not doing so. Either 1) they just don't care enough about your privacy or 2) they want it for themselves. Considering how OpenAI pushes the "Scale is All You Need" narrative, and "scale" includes "data", I'm far more inclined to believe the reason is option 2.

[0] Remember, this isn't so much a conversation in the conventional sense. The LLMs don't "remember". You send them the entire chat history in each request. In this sense they are Markovian. It's not like they're tuning a model just to you. And even if they were, well we can store weights encrypted too. Doesn't matter if a whole model, LoRA, embeddings, or whatever. That can be encrypted at rest via keys OAI does not have access to.

This sort of thing is pretty trivial to implement from the start, they just chose not to because they wanted the data themselves