Imagining that there will be near-human IQ AIs that think orders of magnitude more quickly than humans puts the cart before the horse, as well.
The Actual Intelligence may be the same (or a little higher) considering the Average Intelligence, but the effect the higher speed would likely be a measurable difference.
So when you say, "Here's how we'll get superhuman AI: We'll network together bunches of 80 IQ AI's that think 100x faster than a human," it's kind of assuming its own solution.
I think networks of AI can become super powerful even without being nearly as smart as individual humans. AI will only need to approach certain aspects of humans IQ. It can still be much dumb than us in most ways. Most of human progress has been build up because of vague interactions and feedback loops via markets, religions, and nations.
Adding people to a late project makes it later.
Not all projects are beholden to the rules of the mythical man month.
And even for those that are the primary reason they are is basically the lack of a fast, efficient way to transfer built up institutional knowledge, which may be far less of a factor for AI collaboration.
If I've been working on a project for the past year as the sole developer and I could copy a snapshot of my brain to a portion of your brain that you can access without interrupting me, adding you on as a collaborator is very unlikely to make the project later and very likely to make it go much faster as you could very quickly 'hit the ground running'.
A lot of the problem with the current limits of human intelligence is really bandwidth problems with getting information transferred in and out of our meat brains effectively. Our bandwidth for knowledge import/export is DREADFUL.
AI collaboration (even assuming that bandwidth limitation goes away or is vastly reduced) would still introduce the issue of increased communication requirements, but compared to the initial transfer of acquired knowledge that one isn't as big a deal in my experience and only becomes problematic at great scale.
Perhaps more relevantly, I think there's a more basic questionable assumption - the idea that Church-Turing is the best computational basis for AI.
I strongly suspect this is not true - because even after all this time, our best abstract models of computation are still extremely brittle and fragile.
In a hand-wavey sense, as soon as you start allowing for arbitrary inputs and context awareness, you're no longer dealing with a simple Turing architecture but with something else entirely.
What you are talking about is scientific hypothesis/theory which obviously needs to be tested using experiments to make sure it works. Without experiment there is nothing much you can do in real world.
Dunno, I don't really believe we are that close to building that sort of AI, but it doesn't seem fundamentally impossible, and it does seem like it could do things that to us would look as "more intelligent" than us. It might in the end be better at creating scientific knowledge in the way current computers are better than us at solving arithmetic: faster and capable of holding more in memory, rather than following any qualitatively different process. But even that would be enough.
It's conceivable that someone could construct a special-purpose AI which isn't superhuman but uses advanced ML and NLP algorithms to mine the scientific literature for previously unnoticed implications and relationships between seemingly unrelated articles. But I expect that would only give a suggested starting point for human researchers to formulate hypotheses and design experiments.
Don't get me wrong I think it would be useful, just that the gap from human level AI to 1,000x human AI is simply not that huge. Let's say you moved someone from 2006 to 2016 or even from 1996. Yea sure there is real progress, but not really. We have better drugs in terms of AIDS for example, but we are worse off in terms of antibiotics. Game graphics have improved, but quake is from 1996 so we already had real 3D first person shooters and gameplay is not that different. Hell FTP is arguably worse. Further that's 20 years so we are talking literally millions-man years of effort and trillions of dollars worth of R&D for not much.
In terms of machines the SR-71 is still the fastest manned aircraft, no supersonic passenger aircraft. Tallest building is much taller, but lacks much space on the top floors making it more monument than utility as the sears tower has more useable space and a smaller footprint.
Maxwell's equations were a game changer. So were Newton's laws. So were Relativity and QM.
Church-Turing was also a game changer. But I don't think there's been anything equivalent in computing since.
There's been a lot of application, but no game-changing deep theoretical insights.
Quantum computing may - should? - eventually throw up something new.
It's going to have to. If it doesn't I think we're going to be stuck with much less progress than we're expecting.
Quantity when the difference is large enough becomes quality. The 9 orders of magnitude or so that computers have gone through in storage capacity and speed definitely count as a game-changer.
Human intuition was the major thing getting in the way, and even Einstein's intuition got in the way of his acceptance of quantum mechanics.
Simple artificial life of some kind seems much more likely in the foreseeable future. I've often wondered why no-one has written a virus or worm that is capable of mutation or even cross-over (sexual reproduction of a sort). Under selection pressure it might evolve into something resembling life. The Tierra experiments were a fascinating experiment in this area.
It's the wrong argument entirely. It has nothing to do with intelligence but everything to do with knowledge. Smarts are useless if you have no knowledge. And that's exactly where computers have the edge. Even a 'regular' human level intelligence with all the knowledge that currently exists at its beck and call would be a formidable adversary. Remember: Knowledge is power.
An AI can certainly produce a theory which matches observations, but no matter how powerful it is it won't be able to magically produce only correct useful theories any more than a human can.
We had over 200 years from Newton's laws of motion to produce relativity from pure logic alone, but we didn't manage it. We had to reason from the evidence, and even then we didn't accept relativity as "true" until it had been experimentally verified.
This approach does nothing to convince anyone who believes differently that they are wrong, all it does do is convince them that the "true-believers" are themselves deluded.
This does nothing to advance the understanding of society of the universe around them.
They say "give me evidence", because so far they have an enormous mountain of evidence that SR and GR describe reality well.
That doesn't excuse people being jerks -- science should be welcoming, not alienating -- but it does mean "well, have you considered X" is almost always coming from a place of ignorance, not well informed skepticism. Some impatience with the cranks of the world has to be excused.
I am also looking at a paper that purports to say that Einstein's GR which is used to calculate the precession of Mercury uses a couple of simplifications, which if not used, gives GR calculating the precession of Mercury at twice (or thereabouts what is measured). To test the veracity of the paper, I'll have to do some serious brushing up of my engineering mathematics.
Another example is related to the speed of light c. This value is inversely proportion to the square root of the (electric permittivity of the environment times the magnetic permeability of the environment). The normal assumption is that outside of the atmosphere of the earth, the environment is a perfect vacuum. It is assumed that the speed of light is therefore a constant in a perfect vacuum.
For many areas, this simplifying assumption is adequate, but this assumption may not be true. It is only so assumed. It may turn out that due to variations in both the permittivity and the permeability of the extraterrestrial environments, that this assumption is not inadequate but grossly inadequate.
When doing any experimental work, one should keep in mind and have written down all the base assumptions, otherwise, one may garden path oneself.
This has led to the idea that there has to be additional unseen, unmeasured matter (aka dark matter) and unseen and unmeasured energy (aka dark energy) to explain the anomalous measurements of galactic movement that is not explained by the "gravity is the only significant force" model.
Now, it may be that there is such a beasty. But, I have my serious doubts because electromagnetic fields have more intense effects than gravity, by some orders of magnitude (about 36 orders of magnitude).
In other words, some environments may be completely neutral and gravity is the major effect, in others, the environment may be very electrical and gravity is the least effect.
Our problem is that we can observe only at vast distances and are not able to take direct measurements to confirm our indirect modelling measurements.
Science is no different to any other aspect of people's lives, they will invest great amounts of energy in following their specific model of the world. When challenged, they mostly look at other as imbeciles who are incapable of seeing "the truth". I've seen this occurring in areas like string theory, black holes, dark matter, sub-atomic physics, climate science, immunology and vaccinations, medical surgical techniques, religion, politics, economics, sociology, finance and business, education, archaeology, evolution, etc., etc., etc.
Our models and theories are just that models and theories. We hope and believe they give us insight into the universe around us, but they are not reality. Each has limits and all use simplifying assumptions that are not accurate outside of the limits imposed by those assumptions.
If on the basis of our assumptions, we have to keep adding more and more "strange" entities to make our model fit the observations, then, maybe, we should go back and look at the underpinnings of our models and see if another model will work better (as in the kind of change that eventually occurred when going from the earth-centric epicyclic model to the sun-centred heliocentric model).
The fun is being able to learn more and more about how our universe operates and what we can do within it.
And the idea that all forms of computation, like Turing machines, lambda calculus, etc., etc., also seems pretty darn silly at first glance, too.
> Even if the smartest physicists were 1,000 times smarter than they are now, without a Collider, they will know nothing new.
I'm not a historian but I have read that some scientific discoveries are made through pure logic. Einstein and relativity come to mind as he was not an empiricist. So perhaps there is some hope that ai can lead to scientific discoveries without experimentation
>So the question is, where is the limit of intelligence? We tend to believe that the limit is way beyond us, way “above” us, as we are “above” an ant. Setting aside the recurring problem of a single dimension, what evidence do we have that the limit is not us? Why can’t we be at the maximum? Or maybe the limits are only a short distance away from us? Why do we believe that intelligence is something that can continue to expand forever?
The idea that humans could, just by chance, be pushing the limits of intelligence strikes me as silly