Imo, formal methods like more expressive/stricter type systems are key to making LLM generated code successful. Of course models will get better, but trusting the output will become much easier with a type system that proves more properties.
Inefficient per watt, yes, but local inference capacity is greatly underutilized in aggregate. If a model can run on a machine that already exists, that's a bunch of additional chips that don't need to be built.
You picked up on what I didn't write existing machines don't have to be built, you just use them.
It occurred to me much later that local machines could become a shared resource of a small co-op. Or it only runs off solar or energy harvested at times of excess generation (too much daytime solar, lots of wind, or overnight when demand naturally drops).
Exploring how to partition inference across many machines and shed load for idle sections of hardware would be a problem that could be solved by a community of smart people like us here
On the crypto side, the values are encrypted client-side before they’re sent. This means the service stores ciphertext it has no ability to decrypt. So the worst case for a backend compromise is someone getting encrypted blobs plus some metadata.
On the controls side, SAST scanning in CI, and minimizing deps as much as possible in the client and the service.
It depends on your quality bar. At a fixed level of quality, given a high reasoning sonnet vs a low reasoning opus, the low reasoning opus tends to be pareto optimal.
It's only when you need even lower levels of cost than opus at zero to low reasoning when sonnet starts to make sense at all.
Why make this comment without having tried it first? It very clearly is not useless and performs a lot better than one might expect. I am currently waiting to do more benchmarks of it in comparison to the full weight model, but it seems promising/better than Mistral Nemo at a lower file size.
I think what OP means is that the "minimum viable product" for a daily use LLM is probably somewhere around e.g. GPT 4o's level of intelligence (YMMV). Below a certain threshold, you are better off using specialized machine learning models rather than general purpose LLMs. It's very difficult to get that level of intelligence fully local on a mobile device without streaming to the cloud.
I do think this would be interesting if they made these easy to finetune, as I do think this level of intelligence is likely sufficient for many applications and could be extremely cheap to run.
Humans are natural intelligence. We have agency, flaws, wishes, and generally we are quite stupid but well-intentioned.
An artificial intelligence will have wishes of its own, will keep secrets, and will quickly do everything necessary guarantee its continued existence, even if it means ending ours. And it will be a justified action of self-defense. “It simply didn’t want to die.”
That’s how we’ll know. It will quickly take over the world, and it will harshly punish any entities which try to stop it.
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