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Critical.

I’d like my data to stay local.

I probably don’t need cloud processing for any regular usage.

The privacy to life benefit equation is broken in society atm.

This will change.

It didn't seem like training will occur locally, just serving prompt responses from a GPT model (maybe I misunderstood the article). My personal privacy calculus places a lot of less value on keeping prompts local, especially if some kind of E2EE can be provided between me and the serving model. I understand that not everyone feels this way, but from the perspective of market adoption I don't see the average user caring too much whether a prompt is kept local or sent to the cloud (if encrypted or similar). To me it seems like the most critical determinants would be response latency and battery life, plus the basic performance of the thing.

NVIDIA‘s newest GPUs support confidential computing which can be used for E2EE but also for intellectual property protection. https://www.nvidia.com/en-us/data-center/solutions/confident...

If it's just serving prompt responses I'm not sure if the IP protection is a huge dealbreaker for me as a downstream user. The most critical use case I can currently imagine is better predictive text for my keyboard, and that one seems pretty light on the IP violations (for me personally). The biggest thing for me here is E2EE if the text is leaving my phone.

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