It seems like you are implying that models will follow Moore's law, but as someone working on "agents" I don't see that happening. There is a limitation with how much can be encoded and still produce things that look like coherent responses. Where we would get reliable exponential amounts of training data is another issue. We may get "ai" but it isn't going to be based on llms

If you want to argue in favor of your slop machine, you're going to have to stop making false equivalences, or at least understand how its false. You can't make ground on things that are just tangential.

A computer in 1980 was still a computer, not a chess machine. It did general purpose processing where it followed whatever you guided it to. Neural models don't do that though; they're each highly specialized and take a long time to train. And the issue isn't with neural models in general.

The issue is neural models that are being purported to do things they functionally cannot, because it's not how models work. Computing is complex, code is complex, adding new functionality that operates off of fixed inputs alone is hard. And now we're supposed to buy that something that creates word relationship vector maps is supposed to create new?

For code generation, it's the equivalent of copying and pasting from Stack Overflow with a find/replace, or just copying multiple projects together. It isn't something new, it's kitbashing at best, and that's assuming it all works flawlessly.

With art, it's taking away creation from people and jobs. I like that you ignored literally every point raised except for the one you could dance around with a tangent. But all these CEOs are like "no one likes creating art or music". And no, THEY just don't want to spend time creating themselves nor pay someone who does enjoy it. I love playing with 3D modeling and learning how to make the changes I want consistently, I like learning more about painting when texturing models and taking time to create intentional masks. I like taking time when I'm baking things to learn and create, otherwise I could just go buy a box mix of Duncan Hines and go for something that's fine but not where I can make things when I take time to learn.

And I love learning guitar. I love feeling that slow growth of skill as I find I can play cleaner the more I do. And when I can close my eyes and strum a song, there's a tremendous feeling from making this beautiful instrument sing like that.

Not the same. The underlying tech of llm's has mqssively diminishing returns. You can akready see it, could see it a year ago if you looked. Both in computibg power and required data, and we do jot have enough data, literally have nit created in all of history.

This is not "ai", it's a profoubsly wasteful capitalist party trick.

Please get off the slop and re-build your brain.

Show me the chess machine that caused rolling brown outs and polluted the air and water of a whole city.

I'll wait.

It might, but:

• Current approaches are displaying exponential demands for more resources with barely noticable "improvements", so new approaches will be needed.
• Advances in electronics are getting ever more difficult with increasing drawbacks. In 1980 a processor would likely not even have a heatsink. Now the current edge of that Moore's law essentially is datacenter only and frequently demands it to be hooked up to water for cooling. SDRAM has joined CPUs in needing more active cooling.

Twenty years is a very long time, also "good" is relative. I give it about 2-3 years until we can run a model as powerful as Opus 4.1 on a laptop.

We really need to work out the implications of the fact that Moore's Law is dead, and that technology doesn't necessarily advance on a exponential path like that, anyway. Not in all cases.

The cost per component of an integrated circuit (the original formulation of Moore's Law) is not going down much at all. We're orders of magnitude away from where we "should" be if we start from the Intel 8008 and cut the cost in half every 24 months. Nodes are creating smaller components, but they're not getting cheaper. The fact that it took decades to get to this point is impressive, but it was already an exception in all of human history. Why can't we just be happy that computers we already have are pretty damned neat?

Anyway, AI is not following anything like that path. This might mean a big breakthrough tomorrow, or it could be decades from now. It might even turn out not to be possible; I think there is some way we can do AGI on computers of some kind, but that's not even the consensus among computer scientists. In any case, there's no particular reason to think LLMs will follow anything like the exponential growth path of Moore's Law. They seem to have hit a point of diminishing returns.