local is best for privacy, but i personally think you don't need to go local.
anthropic, google, openai etc, decided that their consumer ai plans would not be private. partly to collect training data, the other half to employ moderators to review user activity for safety.
we trust that human moderators will not review and flag our icloud docs, onedrive or gmail, or aggregate such documents into training data for llms. it became the norm that an llm is somehow not private. it became a norm that you can't opt out of training, even on paid plans (see meta and google); or if you can opt out of training, you can't opt out of moderation.
cloud models with a zero retention privacy policy are private enough for almost everyone, the subscriptions, google search, ai search engines are either 'buying' your digital life or covering themselves for legal reasons.
you can and should have private cloud services, and if legal agreement is not enough, cryptographic attestation is already used in compute, with AWS nitro enclaves and other providers.
I pay $13/month for Proton’s Lumo+ private chat LLM that contains an excellent built-in web search tool. I use it for everything non-technical, even just simple searching for local businesses, etc.
As an enthusiastic reader of books like Privacy is Power and Surveillance Capitalism, it feels good to have a private tool that is ready at hand.
do you have any provider recommendations? I've experimented with this on runpod serverless, but I've been meaning to dig deeper before I feel comfortable with personal data.
I saw a service named Phala, which claims to be actually no-knowledge to server side (I think). It was significantly more expensive, but interesting to see it's out there. My thought was escaping the data-collection-hungry consumer models was a big win.
> i personally think you don't need to go local.
I personally think everyone should default to using local resources. Cloud resources should only be used for expansion and be relatively bursty rather than the default.