No one knows how far off true AGI is, just like no one in 1940 (or 1910) knew how far off fission weapons were.
EDIT: I quite liked this article from a few years back [0], and the fission weapon prediction example is stolen from there.
This is what happened when it became known nuclear weapons were a viable concept. The technology shifted power to such an extreme degree that it was impossible not to invest in it, and the delay from «likely impossible» to «done» happened too fast for most observers to notice.
We don't have any such understanding, or even a definition, of 'AGI'.
Leo Szilard had more plausible philosophical musings in the early thirties, that did not have root in any workable practical idea. The published theoretical breakthroughs you mention didn’t happen until the late thirties. Nuclear fission, the precursor to the idea of an exponential chain reaction, happened only in 1938, 7 years before Trinity.
He didn't have internal combustion engines, but that's a practicality, other mechanical power sources already existed (Alexander the Great had torsion siege engines). They would never be sufficient for flight, of course, but the principle was understood.
But he could never have even begun to build airfoils, because he didn't have even an inkling of proto-aerodynamics. He saw that birds exist, so he drew a machine with wings that flapped. Look at the wings he drew: https://www.leonardodavinci.net/flyingmachine.jsp
That's an imitation of birds with no understanding behind it. That's the state of strong AI today: we see that humans exist, so we create imitations of human brains, with no understanding behind them.
That lead to machine learning, and after 40 years of research we figured out that if you feed it terabytes of training data, it can actually be "unreasonably effective", which is impressive! How many pictures of giraffes did you have to see before you could instantly recognize them, though? One, probably? Human cognition is clearly qualitatively different.
The danger of machine learning is not that it could lead to strong AI. It's that it is already leading to pervasive surveillance and misinformation. (idlewords is pretty critical of OpenAI, but I actually credit OpenAI with taking this quite seriously, unlike MIRI.)
Nuclear weapons required enriched uranium, and the gaseous diffusion process of the time was insanely power-hungry. Like non-negligable (>1% ?) percentage of the US's entire electrical generation power-hungry.
On the 2nd of December, 1942 he led an experiment at Chicago Pile 1 [1] that initiated the first self-sustaining nuclear reaction. And it was made with Uranium.
In fairness to Fermi, nuclear fission was discovered in 1938 [2] and published in early 1939.
0: https://books.google.com/books?id=aSgFMMNQ6G4C&pg=PA813&lpg=...
1: https://en.wikipedia.org/wiki/Chicago_Pile-1
2: https://en.wikipedia.org/wiki/Nuclear_fission#Discovery_of_n...
You are moving goalposts. You mentioned in the first place "fission weapons" and now you take a quote about "nuclear fission reactor" which is a whole different thing.
A nuclear reactor was also required for the production of Pu-239, which is what 2 of the first 3 bombs were made from.
But the fact that Fermi was doing such a calculation in the first place proves that we knew in principle how a fission weapon could work, even if we didn't know "how far off [they] were". As soon as we figured out the moon was just a rock 240,000 miles away, we knew in principle we could go there, even if we didn't know how far off that would be.
By contrast, we don't know what consciousness or intelligence even is. A child could define what walking on the moon is, and Fermi was able to define a self-sustaining nuclear reaction as soon as he learned what nuclear reactions were. What even is the definition of consciousness?
I am of course not saying you're wrong that "we don't know". We obviously don't know. It's possible, just like it's possible that we could discover cheap free energy (fusion?) tomorrow and then be in a post-scarcity utopia. But that's worth taking about as seriously as the possibility that we'll discover AGI tomorrow and be in a Terminator dystopia, or also a post-scarcity utopia.
More importantly, it's a distraction from the very real, well-past-imminent problems that existing dumb AI has, such as the surveillance economy and misinformation. OpenAI, to their credit, does a good job of taking these existing problems quite seriously. They draw a strong contrast to MIRI's AI alarmism.
Have you ever read idlewords? Best writing I know of on this subject: https://idlewords.com/talks/superintelligence.htm
I have problems agreeing with that specific claim, knowing that both "the rock" and the distance were known to some ancient Greeks around 2200 years ago.
https://en.wikipedia.org/wiki/Hipparchus
Hipparchus estimated the distance to the Moon in the Earth radii to between 62 and 80 (depending on the method he used, as he intentionally used two different). Today's measurements are between 55 and 64.
Once we had Newton's law of gravity though, we knew the distance, radius, mass, and even surface gravity of the moon. Would you say it's fair to say that by then we knew in principle we could go there and walk there?
(P.S. I assume you know this but the way you wrote your comment makes it seem like our measurements of lunar distance are nearly as inaccurate as Hipparchus's, when we actually know it down to the millimeter (thanks to retroreflectors placed by Apollo, actually). The wide variation from 55x to 64x Earth's radius is because it changes over the course of the moon's orbit, due to [edit: primarily its elliptical orbit, and only secondarily] the Sun and Jupiter's gravity.)
I think you’re not only wrong but even Kepler and Newton already knew that better than you:
https://en.m.wikipedia.org/wiki/Elliptic_orbit
“Strictly speaking, both bodies revolve around the same focus of the ellipse, the one closer to the more massive body, but when one body is significantly more massive, such as the sun in relation to the earth, the focus may be contained within the larger massing body, and thus the smaller is said to revolve around it.”
But maybe you have some better information?
> due to its elliptical orbit with varying eccentricity, the instantaneous distance varies with monthly periodicity. Furthermore, the distance is perturbed by the gravitational effects of various astronomical bodies – most significantly the Sun and less so Jupiter
https://en.wikipedia.org/wiki/Lunar_distance_(astronomy)#Per...
> Once we had Newton's law of gravity though, we knew the distance, radius, mass, and even surface gravity of the moon.
I think it was more complicated than what you assume there. Newton published his Principia 1687 but before 1798 we didn't know the gravitational constant:
https://en.wikipedia.org/wiki/Cavendish_experiment
However...
> Would you say it's fair to say that by then we knew in principle we could go there and walk there?
If you mean "we 'could' go if we had something what we were sure we haven't had" then there is indeed a written "fiction" story published even before Newton published his Principia:
https://en.wikipedia.org/wiki/Comical_History_of_the_States_...
It's the discovery of the telescope that allowed people to understand that there are another "worlds" and that one would be able to "walk" there.
Newton's impact was to demonstrate that there is no any "mover" (which many before identified as a deity) that provides the motion of the planets but that their motions simply follow from their properties and the "laws." Before, most expected Aristotle to be relevant:
https://en.wikipedia.org/wiki/Unmoved_mover
"In Metaphysics 12.8, Aristotle opts for both the uniqueness and the plurality of the unmoved celestial movers. Each celestial sphere possesses the unmoved mover of its own—presumably as the object of its striving, see Metaphysics 12.6—whereas the mover of the outermost celestial sphere, which carries with its diurnal rotation the fixed stars, being the first of the series of unmoved movers also guarantees the unity and uniqueness of the universe."
Almost nobody really knows how developed is the state-of-the-art theory / applied technology in confidentials advances that the usual suspects may have already achieved. I.E. deepmind, openai, baidu, nsa, etc.
AGI could have already been achieved - even theoretically - somewhere, and like when Edison got to make work a light bulb, we're still using oil and not knowing anything about electricity, or light bulbs or energy distribution networks / infrastructure.
The actual current - new, mostly unimplemented yet - technology level.
Back then you wouldn't have believed if someone had said you "hey, city nights in ten years won't be dark anymore"
There's no way to disprove it, but given that in the open literature people haven't even found a way to coherently frame the question of general AI, let alone theorize about it, it becomes just another form of magical thinking.
There are several public examples of radically more advanced theory/technology than the publicly known possible at a certain time/year, kept secret by governments / corps for a very long time (decades).
Lockheed achieved the blackbird decades before it was even admitted that a technology like that could even exist. But, looking backwards, it just looks like an "incremental" advance, but it wasn't, the engineering required to make fly the blackbird was revolutionary for the time when it was invented (back in the 50s / 60s ).
The Lockheed F-117 and its tech had a similar path, just somewhat admitted in late 80s (and this was 70s technology, probably based on theoretical concepts from the 60s).
More or less the same could be said about the tech in Blechtley Park: current tech / theory propelled to extraordinary capabilities by radical improvement achieved by new top secret advances in engineering. The hardware, events and advances ocurred in Bletchley Park were kept secret for years (I think just in the 50s they started to be carefully mentioned but not fully admitted, but nothing even close to the details currently found in the Wikipedia).
At any given time there could be a lot of theory/technology jump-aheads being achieved out there, several decades ahead of the publicly published/known, supposedly current, theory/technology.
It was hard to predict when or if such a thing could be made, but everyone knew what was under discussion.
Compare this to AGI, some vaguely emergent property of a complex computer system that no one can define to anyone else's satisfaction. Attempts to be more precise what AGI is, how it would first manifest itself, and why on earth we should be afraid of it, rapidly devolve into nerd ghost stories.
All these things have surged incredibly in less than a decade.
It's always a long way off until it isn't.
Not at all, these are all one-trick poneys and bring you nowhere close to real AGI which is akin to human intelligence.
Extrapolating as you seem to be here, when should I expect to see a total conversion reactor show up? I want 100% of the energy in that Uranium, dammit - not the piddly percentages you get from fission!
Seriously, I think you overestimate how predictable nuclear weapons were. Fission was discovered in 1938.
We haven't even had the AGI equivalent of the Rutherford model of the atom yet: what's the definition of consciousness? What is even the definition of intelligence?
However, we are not getting impressively close to AGI. That's why we need to stop the AGI alarmism and get our act together on the enormous societal ramifications that machine learning is already having.
1932 neutron discovered
1942 first atomic reactor
1945 fission bomb
Now for AI 1897 electron discovered
1940's vacuum tube computers
1970's integrated circuits
1980's first AI wave fails, AI winter begins
2012 AI spring begins
2019 AI can consistently recognize a jpeg of a cat, but still not walk like a cat
???? Human level AGI
It doesn't seem comparable one way or the other, in many ways. But if we do compare them, AI is going much slower and with more failure, backtracking, and uncertainty. 1943 First mathematical neural network model
1958 Learning neural network classifies objects in spy plane photos
1965 Deep learning with multi-layer perceptrons
2010 ImageNet error rate 28%
2011 ImageNet error rate 25%
2012 ImageNet error rate 16%
2013 ImageNet error rate 11%
2017 ImageNet error rate 3%
2019 Pre-AGI