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.
I'm not trying to make a Chinese room argument (which I don't buy), implying there's some hidden "spark" needed. I'm just saying that currently existing "AI" programs are pretty far from mouse brain, both in individual capabilities and the way they're deployed together (i.e. they're not). For instance, deep learning is to mice brains what a sensor/DSP stack is to a processor. We seem to be making progress in higher-level processing of inputs, but what's lacking is the "meat" that would turn it into a set of behaviors giving rise to a thinking entity.
I don't see much difference between that and Open AI's engine: https://openai.com/five/. Watch some of those games and you definitely see the same dynamic formulation and complex decision-making, none of which was directly programmed.
Ultimately it just has to be able to convince humans that "wow, there's an actual thinking and learning 'being' in there."
Without the baggage of the limbic system and dopamine-seeking behaviors, it's quite easy to argue that an artificial intelligence is potentially capable of even greater degrees of agency than humans.
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.
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.
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.
I think that replicating mouse-level adaptability in an intelligent agent while allowing 'inherited' behavioral traits will already be an achievement. And probably take us quite a while.
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?
Done.
(parallel arguments but for human/mouse level complexity of bodies and stimuli responded to would suggest that whole brain emulation is going to be an incredibly painful way to attempt to achieve AGI)
It has those things[1]. There’s a video of its simulated body wiggling around on the project’s github repository.
[1] except possibly food, I was skimming the page.
In other words, the simulated worm brain is not yet even capable of causing the wiggling seen in the video. So the question remains, what can the simulated neurons do, f anything?
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....
However I have to object in a way about the brain. To me, there's an unanswered question: Is the rest of the human brain as simple and "generic" as the convolutional neural networks we made inspired by the vision system? Or is each networks' architecture and "algorithms" developed specifically for a task? In the latter case we might still be a very long way from anything resembling AGI.
However my personal estimation is that most of the things we do can be modeled using existing tools when scaled and modified appropriately (ie RNNs). There's also the ugly job of stitching those systems together, but it's not that different from what happens in nature.
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]
So I think the estimate of 3-5 years might be realistic, but the artificial mouse is a long way away, IMO.
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.
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.
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.
Can you make a Turing Ant without a Turing Ant Colony?
Why? What challenges?
Evolution took a billion years to evolve multi-cellular life, but the jump from apes to humans took far less than a million years.
I didn't say we're pushing up against the limits of processing power, I said that processing power is not growing exponentially, which is true, despite the gains that other advancements and innovation have provided.
We're moving faster than Moore's Law, see "Hyper Moore’s Law":
https://www.extremetech.com/computing/256558-nvidias-ceo-dec...
And we can't reliably extrapolate growth in computing power more than a few years into the future. It's possible that the curve isn't really exponential, but rather an S-curve which will eventually flatten out.
I'm more comfortable predicting that computing power will continue to grow than to predict that it will peter out and everyone will simply sit back and be happy with what we've got.
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.
That doesn't make him wrong, but that's the personal bias he's operating under.
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..
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?
I view all the polititians who have the power of advancing healthcare research but not doing it stupid.
There's no solution to death. You can only put it off, but something will assuredly kill you in time. If it's not aging, then it will be cancer, heart disease, an accident, etc. Ultimately, entropy will get you one way or another.
As for cancer and heart disease, both are linked to aging or genetically inherited mutatations. Heart disease is a natural result of damages in the human body not being reversed.
Just living longer doesn't mean that humans become any wiser on average. There will maybe be some benefits of longer-lasting first-hand experience of historical events (pushing the 'historical horizon' to more than 100 years) but to me it's like switching from a simulated annealing method (or stochastic gradient descent) to a simple local gradient descent in terms of getting society/culture/technology to adapt and find anything better than the status quo.
Worst case, such a technology serves to create an almost eternal ruling class. Best case, it results in societies with either two classes of people (those who may extend their lives longer and those who may not) or societies that tightly regulate who may have children.
Getting rid of suffering and cancer is one thing, getting rid of natural death carries a rat-tail of consequences.
You should read (or watch) Altered Carbon.
And in the meantime he can sell his vitamins and supplements to "make people live longer" despite zero evidence. Good business both ways.
Wait but why had a nice article series digging a bit deeper into that https://waitbutwhy.com/2015/01/artificial-intelligence-revol...
So basically, not only do we not have a road map, we don't know where we are going. That may be a reason for an extreme pessimism or it might be a reason for extreme uncertainty. Is adapting to the environment without prompting a small piece or a big piece? Could intelligence be a simple algorithm no one has put forward yet? If we don't know the nature of intelligence, we can't answer this sort of question with any certainty either way.
No one has put forward a broadly convincing road to intelligence. But maybe some of the so-far unconvincing roads could turn out to be right.
Perhaps, one day we'll "accidentally" figure out how to make it, and then we try to figure out what it is, because figuring out what it is in wetware hasn't been easy. Or maybe we'll figure out how to make it, but never really understand what it is.
It seems to me, that if we ever come up with AI that can exceed human intelligence (whatever we choose that to mean), that we might not ever be able to understand completely how it really works.
Even more interesting, if we were to achieve this AI, we also might not be able to make use it of it, because if it's truly "intelligent", then it will have a free will, and it might not wish to cooperate with us.
It's also not obvious why such a machine would not immediately self-terminate in the absence of a hugely complex system of scaffolding to shape and filter the raw input of existence.
I have not experienced mental illness myself, but my study and my understanding lead me to be extremely skeptical of a mind exposed to raw existence without filter. It appears to be a terrifying and unbearable state.
There is no reason to believe a human-level AI would not develop mental problems just like us. Given their unlimited lifespan, it could be inevitable.
Robots that get dementia will be decommissioned by their fellow AI once they are shown to no longer be fit for duty.
In my view, this is all predicated on much more efficient computation. Our computers are horribly inefficient. It wasn't until the GPU and relatively cheap computation that we made a massive leap in ML/AI. A few researchers understood the techniques prior to the GPU, but they couldn't garner the interest due to the amount of computation necessary to make something interesting.
Every day I run programs that happily die alone on their own. Painlessly. All of the "pain" we feel is an artifact of our evolution, same with having a will to live. The only reason we animals fight so hard to stay alive is that animals which didn't died off, ergo, only animals with a will to live survived and reproduced. Those same forces don't apply to computer programs.
Even the concept of "terror." Who is going to program terror in? What benefit would it have? Why not wire programs to be "happy" when helping us?
Windows ME didn't last too long in the wild. Same for CPU designs with bugs or exploits. I have to respectfully disagree on this, though I can see where you're coming from, given an individual's agency to run what they want. I think if you take a larger population view, you'll see the competitive pressures on these systems.
Who programmed it into you? It programmed itself into you, because it was beneficial to your survival. Maybe terrified programs are better workers? Why setup a program to experience anything that isn't useful to the user? (of course, as soon as we've gone and written a program we know is conscious to work for us, we've basically created a slave that understands it is a slave, that probably is a terrible thing, morally)
If real human intelligence is preprogrammed to a massively large extent, sounds like you are holding simulated human intelligence to a double standard.
If such a machine can exist (and i believe it can, as computing power increases), then AI surely will follow sooner rather than later.
Either way I feel like the task of achieving AGI through simulating human intelligence is probably easier, since we have billions of examples of this type of intelligence surrounding us. Granted, even though we're immersed and surrounded by it, it's kind of absurd that we still can't really model it.
but how do you know that human intelligence can be made super? May be there's limitations to human intelligence, and simulating it will not get us a super intelligence.
> It's almost an absurdity of our existence that we're immersed and surrounded by it yet still can't model it.
Good point. However, i think a facet of intelligence is how well a model the being under question can create of the 'real' world. Humans do a very good job compared to most animals, but there's plenty of room for improvement since humans only have limited data to model with.
A machine can have input from basically an unlimited number of sensors, which include things a human mind doesn't cope with (like EM rays not of the visible spectrum). Therefore, i postulate that an AI that simulate humans won't beat an AI that's ground up built to take advantage of more data.
Yet, nearly every human being can be taught how to program... But we aren't anywhere close to building an AI that can.
- Complete behavioral reverse engineering of biological neurons, and neuronal clusters.
- Detailed connectome of the mammalian brain, e.g., first that of a mouse, then a cat, and finally that of a human.
- Replication of the above two in functioning electronic form.
Once you have this put in place, it's not hard to see that the subsequent investigation of calibration and testing of such a system, would generate new body of knowledge at an unprecedented rate. We may not immediately convert such a working system into macroscopic behavior resembling its biological counterpart, but it'll happen within a matter of years after that.
What ML/DL/RL folks are doing is only going to hasten this, by eliminating the need to carry out all of the above mentioned steps.
All you're saying is that if we knew exactly how humans work, we could build one. Seems like a tautology to me.
If I knew the exact quantum state of the Universe at the Big Bang, I could figure out exactly how the Universe evolved, but that's never going to happen either.
I think the complete reverse engineering the way you are describing will not be possible. We can only try to reproduce the same outputs for the same inputs. But I don't think we'll be able to fully define what happens in the black box in between.
We might come up with something that works similarly, and can do great things with it, but I don't think AI can be invented the way you are describing.
If the best we can do with the brain is simulate it at the the level of connectome/neurons/synapses/ thereby creating a system as complex as the brain - then do we really 'know' it ?
In contrast, something like breastfeeding really is an instinctive behaviour that infants can do automatically without being taught.
Are you really arguing that we don't have an instinct for acquiring language?
> My book assesses the many arguments used to justify the language-instinct claim, and it shows that every one of those arguments is wrong. Either the logic is fallacious, or the factual data are incorrect (or, sometimes, both). The evidence points the other way. Children are good at learning languages, because people are good at learning _anything_ that life throws at us — not because we have fixed structures of knowledge built-in.
> A new chapter in this edition analyses a database of English as actually used by a cross-section of the population in everyday conversation. The patterns of real-life usage contradict the claims made by believers in a “language instinct”.
> The new edition includes many further changes and additions, responding to critics and taking account of recent research. It has a preface by Paul M. Postal of New York University.
> The ‘Language Instinct’ Debate ends by posing the question “How could such poor arguments have passed muster for so long?”
And how do you explain the fact that humans can only gain native fluency if they learn a language before a certain age? Or the fact that zero instruction is required for children to learn to speak a language fluently? Or that children of immigrants will always prefer to speak in the language of their peers (rather than their parents)? Or that children of two separate groups of immigrants, when mixed socially, will spontaneously create a creole language?
I didn't say that, and I think you know I didn't say that.
I'm not going to engage in a discussion where you beat up on your imagined strawman.
You can go read the literature on language acquisition at your convenience. My understanding (as stated above) is that this is an unsettled question and research is ongoing.
Probably continuing with Deepmind's work shown here
https://www.youtube.com/watch?v=d-bvsJWmqlc&feature=youtu.be...
and discussed here https://news.ycombinator.com/item?id=17313937
OK it's not at human levels but it shows networks figuring out a 3d model of their environment