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contingenciesyesterday at 6:27 PM3 repliesview on HN

If they can keep up. Unfortunately, we learn from previous technology shifts that the masses will always favor ease of use (to the point of infinite scroll 5 second videos dopamine puddle, or echo chamber social networking in lieu of critical media consumption), which does not bode well for the market for alternative hardware: one which is already expensive.

I fear on-prem AI is likely to become as popular as on-prem servers without Cloudflare using self-hosted email are today: that is to say, people have heard of it but the skillset is almost popularly eviscerated, external policies make it progressively impractical, and anyone who does it is 'niche'. While basic guides will exist, obtaining top-level output will probably require many moons of concerted effort.

Basically: AI is SaaS for thinking.


Replies

jstummbilligyesterday at 6:52 PM

> If they can keep up.

Consider another perspective: They don't have to keep up. Once a model is good enough for a task, the model can stay. A hammer is a hammer and a hammer from 100 years ago still has most of its utility.

Similar to the hammer, it's not unreasonable to think that some classes of work will simply be solved by some model generation and whatever happens at the frontier after that does not matter all that much for work that puny humans do.

Then, of course, there will be a time where all of this is moot: Absolutely no human will want a human to diagnose their medical issues. That is not a skill deterioration issue. We simply will concede that we are not able to do it as well as a more capable system can, and without much fanfare, increasingly delegate, as we have always done.

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mediamanyesterday at 8:05 PM

On-prem versus cloud inference doesn't matter for concentration of power.

Concentration of power exists when the model makers are the same as (or control) the inference providers. Making a model is capital intensive, so there aren't many of them. Providing inference is not: I don't even need to own GPUs; I can rent them from those who do and then sell by the token. B300s cost less than $4 an hour currently.

Cloud can even be more effective at lowering concentration of power than on premise. Asking people to individually buy $20,000 of compute equipment plus power and cooling equipment to run a frontier model is not something they're going to do if they can just pay four-tenths of a cent per output token. If the only cloud inference providers are the big proprietary US titans, that means you're going to get far more power concentration than if open source inference providers are an alternative, because then I can just switch my API endpoint.

analognoiseyesterday at 6:33 PM

Eh, this is our species first contact with that type of technology. A good number of voices see how deleterious these things are, and it’s all still very new. Future humans will tell parables about the evil tech bros and their silly obsessions, and the unequal accumulation of capital. This will be seen as a dark and stupid time, but I think we’ll persevere - the tech bro set is much weaker than they imagine, and certainly than they project.