> But, history says the supercomputer of today will fit in your pocket in a few years.
I don't think this will be true in the same time span anymore. Each miniaturization is costing more and more money.
Perhaps they'll come up with exotic fundamental improvements, but I don't think the rate of improvement of compute/watt will match the previous decades.
Yeah, that's probably true, but we're also seeing that there's still tons of inefficiencies in how LLMs are being run. Seems like every couple months there's some new technique to squeeze more performance out of less hardware. KV caching improvements, fast attention, speculative decoding, dynamic quantization, quantization aware training, etc.
That said, I recently replaced my five year old self-built PC (with a top-of-the-line desktop CPU, chipset, memory, and GPU of the time) with a new everything-the-best build, and while it's clear we're not keeping up with Moore's Law anymore, it's still 4-5 times faster for compute-intensive stuff, especially parallelizable tasks. We're still getting faster/cheaper. So, the time scale is maybe ten years rather than five.
Really the biggest concerns are not computers getting spectacularly faster, but 'intelligence' algorithms getting orders of magnitude better.
Drop the power requirements 1000 fold, and yea you will be able to make your own SOTA model on the cheap. The problem is the person that has a few exaflops of power will still leave you in the dust in the intelligence explosion that would happen after an event like this.
Depends upon the intelligence vs compute scaling law— which I think no one really knows. Pretty likely to be some degree of diminishing returns, but how much? Is it logarithmic, inverse quadratic, …
If training models gets way cheaper, I would expect the diminishing returns to get steeper too.
>Pretty likely to be some degree of diminishing returns
intelligence may be different. If we look at biological brains - do we get diminishing returns or completely opposite scaling law when we compare our brain against say gorilla's ?
Interesting thought to consider in principle but fails because gorilla brains continued to evolve too, just along a different path. They're not snapshots of ancestral species locked in time.
Single clock speed hasn't had much of an upgrade, but the architecture for doing exactly what they are doing? That will improve for at least 5-10 years. There are both huge power gains from Processing in Memory (PIM) chips (70-80% discount in energy), and improvements to engineering to make memory cheaper and cheaper.
Yes, I'm talking about a supercomputer from today in your pocket. That probably requires at least 5000x perf/watt if not even more.
>but I don't think the rate of improvement of compute/watt will match the previous decades.
Unless we invest heavily in research and find new way to do chips. But I think there's not enough motivation and money to do that.
There's literally never been more money being thrown at that problem.