Are you moving away from cloud AI due to privacy?
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With all the recent data leaks and surveillance laws, it feels like the vibe is shifting toward 100% local, on-device compute, even if it means settling for smaller models. Running things locally used to feel like a niche hobby, but with the massive leaps in open-source efficiency, it is becoming a viable daily setup for privacy-first projects.
Granted, dialing in the right hardware and dealing with speed tradeoffs is still a massive pain compared to a ready-to-go API.
Are you guys actually moving your daily workflows and tech stacks to local alternatives, or is cloud still your go-to for convenience? Where do you stand on this?
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WebCurate.co
I think it'll be a mix of both for me.
For anything sensitive or personal, I'd prefer running it locally if the model is good enough.
But for bigger tasks that need stronger models or faster results, cloud APIs are still hard to replace. I don't think one will completely replace the other anytime soon.
the mix take makes sense, but i'd add one distinction that gets lost in these threads: "local" is only worth anything if it's verifiable. "we don't send your data" is a policy you have to trust, and policies change. "the app has no network entitlement, so it physically can't upload" is a fact you can check yourself in seconds.
to eriberto's point about encryption and self-hosting: those help, but the bigger unlock for switching is provable constraints, not just stronger promises. i went fully offline on my own project for exactly this, and the tradeoff you name is real, you pay in convenience and sometimes capability. for anything touching sensitive files i'd rather pay that than trust a policy.
I think many teams will keep using both because convenience still matter. Would stronger encryption and easier self hosting convince more people to switch toward local workflows?
anything that's sensitive - local.
btw, mobile is getting so good / llms are getting so efficient that it can run some smaller models.