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With AI being more useful with access to more of your data, I can't see myself using cloud AI models for purposes such as personal assistants.

Perhaps with differential privacy or confidential compute...

But ideally these models run locally.

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I'm not sure how useful a personal assistant would be if it doesn't have internet access, and at that point you're vulnerable to the lethal trifecta so I'm not sure local versus cloud model is the most important distinction to index on
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This is just lazy thinking.

E.g. having an agent that alerts you when subscriptions are close to renewal etc - yeah seems easy to understand / see happening on the surface.

Until you get into the implementation details and realise 'yeah errr. not gonna work'.

That openclaw nonsense is an example of this.

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Local model doesn’t mean you have to run it locally. It just means that you aren’t locked into a provider. Nothing stops you from using a hosting service. The point is you get to choose if and who gets access to your data.

Additionally, the only use case for LLM is not fully autonomous agentic harnesses. There’s tons of use cases for LLMs where you would like to avoid a round trip to the internet or perhaps there is no connectivity. We’re only starting to scratch the surface!

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Which implementation details? I very much already have this, today.
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Yes! My main use of very strong models is in writing my own coding harnesses for small local models, tailored for my needs. I also use very strong models to get much smaller skill files and also writing tools for my harnesses.

re: data centers: pump and dump. Wealthy investors will have made their money and walked away, and the corrupt democrat and republican politicians in Washington will, as usual, protect the interests of the ultra wealthy and leave the general public to pay for poor decisions. There will be a government bailout.

Anyway, on a positive note, I am all in for small local models that are augmented by strong hosted models for specific tasks. Use technology to help people, not make billionaires even more money.

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What’s the fundamental difference between a frontier model and a local model anyway?
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Privacy!
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Yes, exactly my point! “Frontier” vs “local” isn’t a useful distinction . “proprietary vs open” is a much more useful distinction. Although I suspect people use “frontier” as shorthand for “way too large to run at home practically”.
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That's effectively what it means. You can run frontier models at home e.g. Kimi K3, but you'd need a large amount of money.
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The data centers are for inference time serving, and as long as the GPUs go better, it shouldn't really matter. Token prices should go down 10-100x over the coming years, and then we will use more, because they have more capacity for the same hardware
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