Comment by nradov
8 years ago
It would be foolish to claim we've made any meaningful progress toward a true AGI that can pass the Turing Test until someone demonstrates a computer as smart as a mouse across the full spectrum of activities.
8 years ago
It would be foolish to claim we've made any meaningful progress toward a true AGI that can pass the Turing Test until someone demonstrates a computer as smart as a mouse across the full spectrum of activities.
Once we get computers as smart as a mouse, we'll be at most 3-5 years or so computers as smart as a human. We will have solved at the major challenges in AGI and it will simply be a scale problem then.
Saying we don't have mouse level AGI is simply saying human AGI is greater than 5 years away, which isn't a remotely contentious statement.
The difference in intelligence between an amoeba and a mouse is enormous compared to a mouse and us. People greatly under appreciate how intelligent and close to human a mouse/bird/pig are in the grand scheme of things. Emotions, behaviors, motivations, goal setting, memory it's all there already. A flat worm, an ant, a fly - those are the large stepping stone accomplishments.
Think about rate of very long distance communication in humans. It took us tens of thousands of years to get to 2.4 kps dial up modems, and only few decades to get to common 300Mbps. The important signal is seeing a 100bps modem, not a 100Mbps connection.
So the real question is how long until we can replicate a worm's intelligence?
> Once we get computers as smart as a mouse, we'll be at most 3-5 years
But how long did it take Nature to get from a mammal with mouse-level intelligence to a human-level brain. I think 200-ish million years [0].
You might be right that a mouse is a good indicator of high-level intelligence and that you don't need human-level intelligence to make a good AI, but there might still be some considerable way to go until we have an AI that can significantly outperform us.
[Edit - I agree that natural selection wasn't aiming or directed, and thus wasn't forced to be as fast as we could be. But a human's higher brain functions might not be simple incremental improvements over a mouse's, and there could still be a long way to go]
[0] https://en.wikipedia.org/wiki/Mammal
Nature wasn’t really aiming. So it’s not a valid basis of time estimates.
How long did it take nature to go from T-Rex to chickens?
There’s no reason to believe human level intelligence to be an inevitable result of evolution. It just happend.
> But how long did it take Nature to get from a mammal with mouse-level intelligence to a human-level brain
Not that I agree with the sentiment in the GP, but it took a relatively short time from the first development of multicellular life until nervous systems developed and an even shorter amount of time to go from small mammal intelligence to human intelligence. However, evolution isn't about "progress" as we understand it. The most we can say with regards to intelligence and evolution is that human intelligence satisfied a niche that existed at a certain place and time.
How long did it take Nature to get from nothing to a mouse? About 20 times as long.
So I think the estimate of 3-5 years might be realistic, but the artificial mouse is a long way away, IMO.
Keep in mind that nature uses a somewhat directional random process. How much of those 200-ish million years were spent waiting on selection pressures to promote bigger brains?
I was thinking about human intelligence today and thought about how anything at the tail end of a normal distribution usually produces quite a perverse result. Then I realized we are at the extreme tail end of the intelligence distribution in the animal kingdom. No wonder we manifest all manner of odd results.
I'm not sure creating an intelligence that even supercedes our own will lead to anything good. If anything I'd expect things to get even more perverse.
You have no rational basis for that 3 - 5 year estimate. That's just picking numbers out of the air.
The basis is the complexity growth trend that we have already observed in computing (and most other human endeavors)
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> Once we get computers as smart as a mouse, we'll be at most 3-5 years or so computers as smart as a human. We will have solved at the major challenges in AGI and it will simply be a scale problem then.
Why? What challenges?
Maybe this isn't what you meant, but I'm curious why you would put a Fly ahead of an Ant in the stepping stones.
Can you make a Turing Ant without a Turing Ant Colony?
mouse, crow, worm, human, all running on neurons. You simulate one you can simulate a berzillion.
> worm's intelligence
Done.
http://openworm.org/
Alas, it's not even close to "done." It's a work in progress and a surprisingly difficult one.
For context, the worm (c. elegans, at least) has a very stereotyped nervous system with 302 neurons. The anatomy, down to the cellular level, is known incredibly well. Their behavioral repertoire is not huge and they're fairly easy to study. Nevertheless, we can't even simulate a worm very accurately. (There was a good twitter thread about why yesterday: https://twitter.com/OdedRechavi/status/1086992699528544256)
The human eyeball has about 120M rods, 6.5M cones, and projects to a brain containing ~86B neurons, which is about 8-9 orders of magnitude more cells. The number of possible interactions scales even faster. In summary, we're not close, not at all....
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Not done. OpenWorm is a project to create a worm simulation. An important distinction.
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I think you're right. I haven't read the article, but I think Kurzweil is perpetually too optimistic about what we can achieve, at least in how fast it will happen. There are cool things happening, and lots of advances being made, but we are nowhere near anything that could really be called AI.
Plus, I think all the marketing use "AI" is giving a very distorted and inflated view to the average person of what software is actually doing, and what it's capable of.
It's a buzzword, full stop.
Kurzweil really, really, really does not want to die. So all of his predictions are always timed just so that the technology needed to live forever will be within his projected natural lifespan.
That doesn't make him wrong, but that's the personal bias he's operating under.
I'm really happy that the world is shifting from billionaires that just want more money to billionaires that understand that it doesn't mean anything if they don't finance solving the problem of dieing.
I view all the polititians who have the power of advancing healthcare research but not doing it stupid.
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Yet die he will.
> That doesn't make him wrong, but that's the personal bias he's operating under.
And in the meantime he can sell his vitamins and supplements to "make people live longer" despite zero evidence. Good business both ways.
> Kurzweil really, really, really does not want to die.
So strange, considering that non-existence is the one thing that every conscious being is guaranteed to never experience. Why run from something that can never catch you?
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> Kurzweil really, really, really does not want to die
What a shit life must that be. And I say this in a very sympathetic way. However, feeling you are almost in reach of eternal life, but not being sure you'll make it in time, being constantly afraid of an accident, or illness, taking that away from you... It's a recipe for anguish and panic.
Dying is not that terrible when you know everybody else will too, sooner or later; but try accepting the idea of being among the last to die..
Isn’t his argument basically that humans suck at estimating exponential growth, tending to be biased towards a linear expectation?
Wait but why had a nice article series digging a bit deeper into that https://waitbutwhy.com/2015/01/artificial-intelligence-revol...
It's kind of funny since I would say the singularity is a result of being bad at estimating exponential growth, since all exponential growth eventually hits some limiting factor and slows down, like a sigmoid.
What does it mean to be as smart as a mouse? If you specify a handful of tasks that demonstrate it, someone will be able to purpose-build an "AI" to do those things well.
Basically it means having "agency." What most people are looking for when they think of "intelligence" is not the ability to master specific tasks, but to choose which tasks to perform using one's own "free will," ultimately leading to behavior that humans find novel and feel they can connect with.
What makes you think a mouse (71M neurons) has agency\free will? Does a cockroach (1M neurons), fruit fly (250K), jellyfish (5k) have agency? I don't think we're gonna get far by relying on a phenomenon that we can't clearly define or even (externally) observe.
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But what does it mean in the context of a mouse? The mouse isn't using it's free will to decide whether to become a computer programmer or a doctor, it's responding to stimulus and environment. If an AI is trained to mimic the responses of a mouse is that intelligent?
Agency in the context of a machine seems purposefully impossible to reach - its decisions are always somehow tied back to how it was programmed to react.
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"Basically it means having 'agency.'"
Well, in these definitions of intelligence, what one often ends up with is some combination of "deal robustly with it's environment" and a bunch of categories defined in terms of each other. That's not to say categories/qualities/term like "agency", "free will", "feel they can connect with", "find novel" and such are unimportant. It's just saying people using the terms mostly couldn't give mathematically/computationally exact definitions of them. And that matters for any complete modeling of these things.
To use machine learning parlance, such a solution would (likely) be overfitting the problem, and not generalize well. If one instead changed the setup to be: 1) Specify a handful of tasks for the AI system to complete 2) Test the performance on a _separate_ (un)related set of tasks
The test set has to be unknown to the system developers.
If the system can realize the unknown tasks without further input from researchers, in the same way that a mouse can, then we have some level of generalizable intelligence.
What is the baseline? How well does a mouse perform when placed in an "unrelated" task for the first time? The mouse also gets an explicit reward function (food, pain, etc) - does the "unrelated" task use the same reward function as what the AI was optimized for?
Also, is it ever really the "first time" for a mouse when behavior has been ingrained and tuned over millions of years of evolution? Is this different than training an algorithm?
My point is just that it's really hard to define these tasks and how to evaluate performance for a machine and a mouse.
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Navigate a forest floor looking for food and avoid predators.
Not even that, mice are very social creatures, they make friends with other animals. They have so many other micro traits
(most humans can't do this task and survive)
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So basically we just need to show a computer can beat PacMan?