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Is AI Riding a One-Trick Pony?

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Re: Is AI Riding a One-Trick Pony?

#131

Post by justincormack »

TimPC wrote: post #67
gadjo95 wrote: post #50

The most relevant part of the article: David Duvenaud, an assistant professor in the same department as Hinton at the University of Toronto, says deep learning has been somewhat like engineering before physics. “Someone writes a paper and says, ‘I made this bridge and it stood up!’ Another guy has a paper: ‘I made this bridge and it fell down—but then I added pillars, and then it stayed up.’ Then pillars are a hot ne…

Last I checked bridges came before Newtonian Mechanics and it seems strange to argue this wasn't a good thing. Admittedly paper writing wasn't the main mechanism of transmitting knowledge but it's fairly common for human engineering to come before the full theoretical foundations as opposed to after.

Cathedrals regularly fell down, and domes, and no doubt bridges too.

Re: Is AI Riding a One-Trick Pony?

#132

Post by karpathy »

There is a bit of "can't see the forest for the trees" failure in the article. AI is spearheading a paradigm shift in how we write programs. Or rather, we don't write programs. We write much much shorter programs that search the program space for programs that satisfy some desiderata.

The programs we get as the output of the search process are extremely flexible, work very well, are very homogeneous in compute (e.g. conv/relu stacks), and never crash or memory leak. These are huge benefits compared to classical programs.

So sure, backprop (the credit assignment scheme that gives us a good search direction in program space, one of multiple techniques that could do so) is pervasive, but AI is starting to work primarily as a result of a deeper epiphany - that we are not very good at all at writing code.

Re: Is AI Riding a One-Trick Pony?

#133

Post by throwaway90001 »

ridgeguy wrote: post #128
dragontamer wrote: post #87

Earlier quoted context omitted.

> 1) learn how the brain works 2) build a simulator I disagree that step #1 is important. Consider the "Air-foil", which led to flight. In one sense, its an approximation of the wings of birds and other animals. But ultimately, the discovery that the "Air-foil" shape turns sideways blowing wind into an upward force now called "lift" is completely different from how most people understand bird wings. Bird Wings flap,…

Disclaimer: I have no expertise in AI. That said, I agree that learning how the brain works seems unimportant and unnecessary. Evolution doesn't know how a brain works, but it's given us Einstein, Michelangelo, and conversations on HN. It seems really important to learn how to build evolution into attempts at AI, given that evolution is the only known mechanism that leads to what we recognize as intelligence.

> it's given us Einstein, Michelangelo, and conversations on HN

two out of three ain't bad

Re: Is AI Riding a One-Trick Pony?

#134

Post by aroman »

mannykannot wrote: post #84
philipkglass wrote: post #20

I'm encouraged that so much fruitful work has come out of this one trick. If you can use the same basic framework for image labeling, playing Go, and translating natural languages, I'd say it's a powerful tool with broad applications. I think that there's a kernel of insight to "A real intelligence doesn’t break when you slightly change the problem." But human perception and intelligence are pretty brittle. The metho…

Human perception and intelligence are by no means infallible, but neither are they anywhere near being as brittle as current AI. The thing about illusions is that we generally know that we are being subject to an illusion, and we also usually have the depth of understanding to know when we don't understand something about what we are seeing or think we have heard, and we have the depth of understanding to think of ac…

> The thing about illusions is that we generally know that we are being subject to an illusion.

Citation needed? I did my undergrad in cognitive science, and while my knowledge of illusions is very limited, I never came across anything to suggest that we have an innate awareness of when our perceptual system is being tricked.

Re: Is AI Riding a One-Trick Pony?

#135

Post by musage »

hyperpallium wrote: post #29

Real intelligence is whatever computers can't do yet. Some think this is because we have such an impoverished grasp of intelligence, that it's only when we see a computer actually do it that we realize it doesn't really represent intelligence (logical deduction and inference, rudimentary natural language understanding, expert systems, chess, speech recognition, image recognition). Machines and tools that perform bett…

I think it starts even sooner than that, with the confusion of abstractions and reality. Ralph Waldo Emerson described it in "Blight". Another thing that comes to mind is comparing "using science for this stuff" with a drunkard searching for a key near a lamp post because it's dark everywhere else, even though he knows for a fact that's the one spot it's not located. We're already restricting human thought to abstractions more and more, the asylum is already being run by the insane, so I think we're going to meet whatever we'll cook up more than half way comfortably.

Re: Is AI Riding a One-Trick Pony?

#136

Post by graycat »

indescions_2017 wrote: post #119
gadjo95 wrote: post #50

The most relevant part of the article: David Duvenaud, an assistant professor in the same department as Hinton at the University of Toronto, says deep learning has been somewhat like engineering before physics. “Someone writes a paper and says, ‘I made this bridge and it stood up!’ Another guy has a paper: ‘I made this bridge and it fell down—but then I added pillars, and then it stayed up.’ Then pillars are a hot ne…

OTOH, we are merely at circa Year Five into deep reinforcement learning research. It started as a cluster of 16M CPUs having taught itself to recognize a cat 95% of the time after training on 1B google images. And we are now at One-Shot Imitation Learning, "a general system that can turn any demonstrations into robust policies that can accomplish an overwhelming variety of tasks". One Shot Imitation Learning https://…

It's easy to recognize a cat 95% of the time. I can write a program in 30 seconds that will recognize a cat 95% of the time. No, wait, this just in! My program will recognize a cat 100% of the time! The program has just one line:

     Print "It's a cat!"

Re: Is AI Riding a One-Trick Pony?

#137

Post by musage »

hyperpallium wrote: post #72
kevin_thibedeau wrote: post #58

Earlier quoted context omitted.

The Turing test is all a smoke and mirrors game. Q&A interactions say nothing about underlying self-directed initiative. Acting intelligent doesn't make it so just as a thespian doesn't become a real Hamlet by playing the role.

How do you know when you're talking to a real Hamlet? BTW I hadn't heard your Hamlet counter before, and I like it. A similar one might be: just because someone sold you the Brooklyn Bridge doesn't mean you own it. The flaw is there are other ways of checking those; for intelligence, there are none. Behaviour is it (at least, so far... still awaiting a non-behavioural definition of intelligence).

Who you think I am is completely irrelevant to who I am, that is something established by me from the inside if you will. It's done before the question whether an observer exists even arises. So yes, you wouldn't know either way, but that still doesn't make them Hamlet if they're not.

Re: Is AI Riding a One-Trick Pony?

#139

Post by argonaut »

indescions_2017 wrote: post #119
gadjo95 wrote: post #50

The most relevant part of the article: David Duvenaud, an assistant professor in the same department as Hinton at the University of Toronto, says deep learning has been somewhat like engineering before physics. “Someone writes a paper and says, ‘I made this bridge and it stood up!’ Another guy has a paper: ‘I made this bridge and it fell down—but then I added pillars, and then it stayed up.’ Then pillars are a hot ne…

OTOH, we are merely at circa Year Five into deep reinforcement learning research. It started as a cluster of 16M CPUs having taught itself to recognize a cat 95% of the time after training on 1B google images. And we are now at One-Shot Imitation Learning, "a general system that can turn any demonstrations into robust policies that can accomplish an overwhelming variety of tasks". One Shot Imitation Learning https://…

Not really, no. Saying we are at year five of Deep RL is about as informative as saying we are at year five of deep learning. Reinforcement learning as a field goes back decades.

Re: Is AI Riding a One-Trick Pony?

#140

Post by justonepost »

gadjo95 wrote: post #50

The most relevant part of the article: David Duvenaud, an assistant professor in the same department as Hinton at the University of Toronto, says deep learning has been somewhat like engineering before physics. “Someone writes a paper and says, ‘I made this bridge and it stood up!’ Another guy has a paper: ‘I made this bridge and it fell down—but then I added pillars, and then it stayed up.’ Then pillars are a hot ne…

The fundamental problem with AI is the high dimensionality of the solution space. We simply can't understand why the brains we are building can think better than us. We can build smarter brains only by trial and error - at least until error outsmarts us, reproduces and takes over.

Kind of like having kids.

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