Ah, the optimism of 1997.

The article is super focused on the hardware side of things, and to a point, that makes sense. Your hardware has to be able to handle what you're simulating.

But it's not the hardware that's the difficult problem. We're nowhere close to hitting the limits of scaling hardware capability, and every time people declare that we are, they're proven wrong in just a few years, and sometimes even in just a few months.

It's the software. And we're so far away from being able to construct anything that could think like a human being that the beginning of it isn't even in sight.

LLMs are fantastic, but they're not a path to building something more intelligent than a human being, "Superintelligence". I would have a negative amount of surprise if LLMs are an evolutionary dead end as far as building superintelligence goes.

Is modeling neuron interactions the only way to achieve it? No idea. But even doing that for the number of neurons in a human brain is currently in fantasy land and most likely will be for at least a few decades, if not longer.

If I had to characterize the current state of things, we're like Leonardo Da Vinci and his aerial screw. We know what a helicopter could be and have ideas about how it could work, but the supporting things required to make it happen are a long, long way off.

I don't even think it's a software matter...

It's my understanding that we (as a spieces) are far from understanding what intelligence is and how it works in our selves.

How are we going to model an unknown in a way that allows us to write software that logically represents it?

> We're nowhere close to hitting the limits of scaling hardware capability

Would note that we've only recently crossed Bostrom's 10 ^ 17 ops line [1].

To my knowledge, we don't have 10 ^ 14 to 10 ^ 17 ops computing available for whole-brain simulation.

[1] https://www.top500.org/system/180307/

>so far away from being able to construct anything that could think like a human being that the beginning of it isn't even in sight.

To me things like MuZero (learns go etc. without even being told the rules) and the LLMs getting gold in the math olympiad recently suggest we are quite close to something that can think like a human. Not quite there but not a million miles off either.

Both in human terms involve thinking and are beyond what I can do personally. MuZero is already superintelligent in board games but current AI can't do things like tidy your room and fix your plumbing. I think superintelligence will be gradually achieved in different specialities.

>like Leonardo Da Vinci and his aerial screw

that didn't function. Current AI functions quite a lot. I think we are more maybe like people trying to build things that will soar like and eagle but we presently have the Wright bros plane making it 200m.

Sometimes I wonder if AGI/superintelligence/whatever will be like flight, which was not successful until we stopped trying to copy nature’s flapping wings and studied flight at a more fundamental level.

>But it's not the hardware that's the difficult problem

I think the problem is that we're still making the distinction between hardware and software. There isn't any. Or if we insist on it we have to deal with the von Neumann bottleneck.

Hardware-software hasn't been cracked yet. I believe this is a good primer on the issue: https://youtu.be/0UVa7cQo20U

From what I can understand, current hardware and software paradigm is the limiting factor.

I can also just say things