Nothing in the repo details how this addresses privacy concerns of running inference on someone else's LLM. To be isolated from other users of the service is not the same thing as having a private inference engine.
> Private: Built-in guarantees around the privacy of your data and fully isolated from those operated by OpenAI.
So where do you draw the line? No cloud instances, no cloud SQL like Snowflake, no Teams or Office 365, no S3/blob storage? Run everything on-prem like 10 years ago?
It's only going to get more impossible. All that VC money going in at 100x revenue needs a return and they aren't going leave money on the table with full-featured open-source or CentOS type alternatives.
All those data engineering startups, database providers with 'open-source' + cloud hosting, the 'open-source' is going to be just 'open' enough to claim there is some fallback for someone else to pick up the mantle using the community version, if the cloud version gets enshittified beyond reason.
You're not going to even be able to run the full-featured software version on-prem because the economics of cloud are so much better.
Unless you are writing and compiling your own code you are going to be out of luck if your privacy standard is that high. That war has been lost. And Web3 sure ain't gonna save you either.
They should clearly spell out what is and is not "private". As it is we simply have a blurp about some undefined guarantees. And some comments here in thread saying "this is as close as you're going to get to local GPT" are deeply wrong. But then there is easy VC money (just like with ADs ..) and certain "clever" geeks throw social responsibility out the window as usual and are pushing all sorts of deeply invasive applications ("let our proxy for Microsoft hoover your inbox!") based on these undefined "Privacy guarantees".
If we accept this just we accepted the very flawed solutions we were given by corporation regarding social networking and ads, we are going to be stuck with it, suffer the consequences, and there will be no incentive to develop alternatives that actually address issues and work.
Homomorphic Encryption works. It just doesn't work very efficiently right now but that is an intellectual problem that can be solved if we push for actual privacy for this critical technology as it will be fully enmeshed in all parts of our lives.
> Private: Built-in guarantees around the privacy of your data and fully isolated from those operated by OpenAI.
Do tell.