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Maybe someone here can help me with this.
What is the bull case, beyond drawing lines on a graph, for AI achieving superhuman, or even human, performance on tasks that are not quickly verifiable?
AI is quite clearly superhuman at self-contained programming problems. I haven't tried Fable, but I suspect that superhuman open ended software engineering is not far away, though I suspect that humans will have a role in architecture and problem setting as opposed to problem solving for some time more. I expect hardware work will also quickly go down this path, at least to some extent, and really anything that can be RLVR'd. That's enough to account for a huge portion of white collar work and carries serious cyber security risks. Both of those will have serious consequences, politically and militarily.
I am not convinced that AI is improving at anything like this rate for things that can't be RLVR'd, I.e. stuff where you can't generate enormous amounts of useful training data with an answer key. Radiologists continue to do just fine for themselves despite repeated promises of doom. I'm sure someone will chime in to say that the radiologists are there for liability reasons, but it's not as if they are now just hitting thumbs up/thumbs down on AI decisions all day.
Partly this is a sample efficiency question - there simply might not be enough data for them to learn this stuff to human level, and architectural advances that improve sample efficiency may lead to huge gains in quality. But it's not clear to me why people expect this to happen.
My simplified argument, as distilled from Lesswrong (i.e. Yud) and other books.
The ceiling of capabilities for what we call 'intelligence' is extraordinarily high. Computation can be done many orders of magnitude more efficiently than you think, in the extreme case.
The floor for something 'superintelligent' (right now, I'm using the definition 'smarter than humanity itself as a collective') is substantially below that.
Human brain architecture is NOT anywhere near the most efficient way to instantiate intelligence. (This follows naturally if you accept 1.)
Humans are capable enough to build electronic hardware that can outperform their own brains in computation efficiency.
Thus, eventually, humanity might stumble into or intentionally build a coherent entity that is superintelligent, and sooner than we 'expect.'
Focus in on 4, too. What specific task do you think human brains can perform that we're MAXIMALLY efficient at, such that no electronic version can beat us?
The conceit is that there is no such task, and so its only a matter of time, and adding capabilities to existing models, until the human capabilities are exceeded on all fronts. If the resulting entity is able to do self-improvement, it by definition will do so faster and more efficiently than humanity can track.
I don't think there's strong evidence against these but I don't think there's strong evidence for these either. Certainly LLMs are not more efficient than the human brain.
Could be. But this isn't an argument for short timelines, which is implicitly what we're discussing here.
Only if, with self-improvement, it actually improves things that aren't suitable for RL environments with massive amounts of data. So far we are very much in the "lumpy capabilities" regime.
At some tasks they undoubtedly are.
The thought experiment that makes it palatable to me is this:
John Von Neumann might be the smartest human who has ever lived. At least that we have good records of. So call him peak human cognitive capacity.
That man, by coordinating with other extremely smart but not quite as smart humans, fully revolutionized multiple fields, and he died relatively early so we don't even know what he might have output over the rest of his life.
We should, in principle, be able to build a simulated Von Neumann that is ~as smart as he was.
Then we should be able to copy that cognitive model.
We should be able to run a bunch of these copies in parallel and have them work together.
With enough hardware... we should be able to speed up these copies arbitrarily.
We could ask these copies (if they don't ask it themselves) how to improve their own speed and efficiency.
With Von Neumann and Co. we were able to move from pure theory to actual nuclear weapons in <10 years. with 10,000 Von Neumanns running at, say, double speed, what could they do in 5 years?
(Yes, I'm handwaving technical details).
In that respect, I consider Von Neumann's existence as evidence of superintelligence being possible. Unless there's something completely ineffable about human cognition that we, as humans, can't ever capture it.
This is basically assuming the conclusion though. Even granting this for the sake of argument, it doesn't mean that we'll be able to build such a simulation in the next 10 years rather than in ten thousand.
My counter is that you're implicitly making a special pleading for how human brains work that is unlikely to be true.
I assume creating a Von Neumann-level intelligence is possible because a Von Neumann level intelligence existed. It has been created, so it could be done again. And repeated.
I'm not saying we clone Von Neumann, scan his brain and build an electronic copy of it. I'm saying even if we can only build a computer program that is approximately as smart as the smartest human ever... the mere fact that we can then copy that program and run it in parallel should result in technological improvement on par with the Manhattan project.
There is NO limiting principle I'm aware of that makes it impossible to build an electronic brain that meets those criteria. Even if we stumble into it rather than intentionally build it, eventually our millions of monkeys slamming away at keyboards can stumble into a viable method.
Evolution was able to stumble into building Von Neumann, after all.
So what I'd ask you, as a full counter to my arguments, what upper limit or barrier is going to appear BEFORE we get to the point we've built something smarter than our whole species?
You are still assuming the conclusion. We have not built a computer program that is as capable as even a sub-median human in all domains, as far as I can tell, unless there is a program that can tie a shoelace and correctly tell me if I should drive to the car wash.
I don't mean this as a gotcha. LLMs are prone to certain cognitive biases that humans are not, and vice versa, and they are highly useful in many fields. But it's clear that the capabilities frontier is not uniform, far from it.
I don't know. All I know is that the current paradigm relies on massive amounts of artificially generated example problems with answers and I don't believe that all of human knowledge is amenable to such treatment. So far I have not seen any reason to believe that actually general, rather than spiky, superintelligence is imminent. And the imminence is, again, really the key question that's motivating all this.
I guess its easy for me to believe that if a largely randomized optimization process (natural selection) was able to eventually get to Von Neumann intelligence, then humans working with a bit more inherent purpose towards the goal of building a Von Neumann level intelligence can probably get there, even if they make some mis-steps and wander around in the dark for a bit.
Especially if we can build some optimization processes that result in sub-Von Neumann intelligences that are nonetheless useful.
Like, the mountain peak we're seeking is visible, poking out above the fog, even if we can't see and specifically plan a route that will get us there, we have flashlights and climbing gear and GPS systems in place to make navigation through the terrain towards the peak much easier. We're not utterly lost with no clue on what we're doing, in that respect.
I don't think this is true. You can imagine it, but you can't see it. If we understood how human intelligence worked it'd be a different story, but we don't.
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