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Google AI Ultra

(blog.google)
320 points mfiguiere | 2 comments | | HN request time: 0.039s | source
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Ancapistani ◴[] No.44045423[source]
I've toyed with Gemini 2.5 briefly and was impressed... but I just can't bring myself to see Google as an option as an inference provider. I don't trust them.

Actually, that's not true. I do trust them - I trust them to collect as much data as possible and to exploit those data to the greatest extent they can.

I'm deep enough into AI that what I really want is a personal RAG service that exposes itself to an arbitrary model at runtime. I'd prefer to run inference locally, but that's not yet practical for what I want it to do, so I use privacy-oriented services like Venice.ai where I can. When there's no other reasonable alternative I'll use Anthropic or OpenAI.

I don't trust any of the big providers, but I'm realizing that I have baseline hostility toward Google in 2025.

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1. nowittyusername ◴[] No.44045644[source]
Understanding that no outside provider is going to care about your privacy and will always choose to try and sell you their crappy advertisements and push their agenda on you is the first step in building a solution. In my opinion that solution will come in the form of a personalized local ai agent which is the gatekeeper of all information the user receives and sends to the outside world. A fully context aware agent that has the users interests in mind and so only provides user agreed context to other ai systems and also filters all information coming to the user from spam, agenda manipulation, etc... Basically a very advanced spam blocker of the future that is 100% local and fully user controlled and calibrated. I think we should all be either working on something like this if we want to keep our sanity in this brave new world.
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2. Ancapistani ◴[] No.44045888[source]
Exactly.

To be clear, I don't trust Venice either . It just seems less likely to me that they would both lie about their collection practices and be able to deeply exploit the data.

I definitely want locally-managed data at the very least.