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Artificial Intelligence Is Stuck

nytimes.com

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Re: Artificial Intelligence Is Stuck

#101

Post by ballenf »

mannykannot wrote: post #65
bhickey wrote: post #58

Earlier quoted context omitted.

I'm riffing on his writing -- > Even Google Translate, which pulls off the neat trick of approximating translations by statistically associating sentences across languages, doesn’t understand a word of what it is translating. This is just another incarnation of "AI is the thing we haven't done." He's parroting Chomsky's disdain for statistical models and John Searle's fundamental misunderstanding of AI. For the forme…

>> Even Google Translate, which pulls off the neat trick of approximating translations by statistically associating sentences across languages, doesn’t understand a word of what it is translating. >This is just another incarnation of "AI is the thing we haven't done." I don't think so - it appears to be an objectively correct assessment of the current state of the art. > Otherwise we're just moving goalposts. The fir…

>>> Even Google Translate, which pulls off the neat trick of approximating translations by statistically associating sentences across languages, doesn’t understand a word of what it is translating. >> This is just another incarnation of "AI is the thing we haven't done." > I don't think so - it appears to be an objectively correct assessment of the current state of the art.

How deep an understanding is required to meet the threshold? The skepticism feels like "no true Scotsman" applied to the definition of understanding.

I observe the following in young children when exposed to a new word:

0. First exposure to totally new word used in a sentence with more familiar words.

1. Brief pause

2. Mimic pronunciation 1-2 times

3. Process for minutes, hours, or days.

4. Use the word in a less than 100% correct way

5a. Maybe hear the phrase repeated back with the error "corrected" (hello internet)

5b. Maybe hear more usage of the word in passing from others (with varying degrees of "correctness")

6. Recurse for life.

At what point did the person understand the word? How is AI translation substantially different?

I'm not sure I understand any word in a way that would satisfy AI skeptics.

Re: Artificial Intelligence Is Stuck

#102

Post by sgt101 »

adamnemecek wrote: post #24
sgt101 wrote: post #23

Earlier quoted context omitted.

I think you are out of date. Rectification is pretty good at removing a lot of the vanishing gradient issues that nn's used to face, and the overwhelming power of modern digital computers (50k cores is common) make this all moot as far as I can see.

Nope, they aren't even in the same category. E.g. Notice that there is a cpu size limit because of heat. Do you know what doesn't overheat? A photonic computer. You can build a cpu the size of a house. Also how does the number of cores constitute "overwhelming power".

:o) well, due to the wavelength of light a photonic cpu has to be 50->100 times the size of a current gen electronic one.

When I were a young 'un we had one core, and it ran at 25Mhz and about 130 of us shared it. Now I have 50,000 cores that run at 2 Ghz and five people share it. Things aren't quite directly comparable but the speed up is at least 100,000x I am overwhelmed by this, things that would have taken 1000 days; approximately 3 years, can be achieved in ten or twenty minutes. In reality the use of these infrastructures has enabled (in neural net land) the development of techniques that improve performance by several more orders of magnitude - so things that would have taken several years are now done in a minute or so. I believe that there is plenty more headroom to be had.

Re: Artificial Intelligence Is Stuck

#103

Post by saltcured »

jesperlang wrote: post #54
bhickey wrote: post #50

The author is just spouting off on a topic he doesn't understand. It's just a rehashing of Chomsky's hatred of statistical NLP. He pulls off the neat trick of approximating knowledge of artificial intelligence by hoodwinking the New York Times, but he doesn’t have insight into the topic he's talking about.

Can you describe what you mean by "he doesn't understand"? His background is in psychology and neuro science so his view on intelligence is probably quite different than person coming from computer science. For me he puts words onto something I've felt recently, that what we're doing is cool and all, but just doesn't feel like the right way to approach it. We're just putting loads of data and computing power into som…

Your concern about "the right way to approach it" is getting closer to the real conflict which is not in the "way" but in what "it" is. In your mind, what is the desired goal or outcome for AI R&D?

If your objectives are in medicine, cognitive science or philosophy of the mind, you might want simulations which are isomorphic to biological minds. You probably hope that AI work will provide illumination into how the mind works, or why it sometimes fails, or how to improve it.

If your goals are in computing and product engineering, you want predictable, reproducible, and adaptive methods for making smarter tools on time and on budget. You may want the product to have behaviors compatible with humans (as a product feature) but you shouldn't care whether the implementation technique in any way resembles an actual human mind. Behaviorism is all that matters for a product evaluation. The design and marketing teams can take care of imbuing the product with intangible properties imagined by consumers.

And honestly, if you want a biological mind, we already have techniques to build them: go find a mate, procreate, and raise your offspring. Nobody tasked to deliver a commercial AI product is actually going to want a solution that behaves like real human minds, where individual units off the same assembly line may require psychotherapy, develop self-destructive habits, or worse slip through QA with an undetected sociopathy or psychopathy which creates a manufacturer liability.

Some of us old school engineering types may harbor a disdain for the current neural net renaissance because it feels a little too black box to us. Deep down, we'd prefer a tool-building tool that had more directly visible logic and rules in it, because we tend to believe (rightfully or not) that such a method is more amenable to engineering practices and iterative designs. But, the risk in this mindset is in forgetting that even complex, logical systems can exhibit emergent properties and chaotic behavior. We probably need to engage in more statistical methods whether we like it or not...

Re: Artificial Intelligence Is Stuck

#104

Post by adamnemecek »

sgt101 wrote: post #102
adamnemecek wrote: post #24

Earlier quoted context omitted.

Nope, they aren't even in the same category. E.g. Notice that there is a cpu size limit because of heat. Do you know what doesn't overheat? A photonic computer. You can build a cpu the size of a house. Also how does the number of cores constitute "overwhelming power".

:o) well, due to the wavelength of light a photonic cpu has to be 50->100 times the size of a current gen electronic one. When I were a young 'un we had one core, and it ran at 25Mhz and about 130 of us shared it. Now I have 50,000 cores that run at 2 Ghz and five people share it. Things aren't quite directly comparable but the speed up is at least 100,000x I am overwhelmed by this, things that would have taken 1000…

Where is that estimate coming from? I mean year there has been progress by why do you think photonic would be even better?

Re: Artificial Intelligence Is Stuck

#105

Post by teabee89 »

I agree that AI is hyped, but I believe the problem is that we absolutely don't care about 50 years of neuroscience research. We know so little about the brain, but already much more than back when "artificial neurons" were modeled. The only company that I believe is on the right track is Numenta, they focus on reverse-engineering the neocortex. They have a living theory that is updated every time there is a research breakthrough.

Re: Artificial Intelligence Is Stuck

#106

Post by amelius »

backpropaganda wrote: post #12

An agent can be intelligent without it learning how to read human language. Look around, most organisms in our world communicate using extremely simple binary language or don't communicate verbally at all. Yet, they are intelligent enough to do very complicated tasks which current robots fail to do. Intelligence is an easier problem than language, and thus should be solved before language. What a sigh of relief to re…

Perhaps we should make a list of increasingly difficult problems to solve. Image recognition is at the front of the list, and we can cross it off. What is next?

Re: Artificial Intelligence Is Stuck

#107

Post by desireco42 »

I didn't read this article for the simple reason that NY Times is not the place to learn any insight about AI like this. They are article churning machine that serves political propaganda and useful local news and analysis. Anything science based, not really their thing.

Re: Artificial Intelligence Is Stuck

#108

Post by ethbro »

rwnspace wrote: post #90
ethbro wrote: post #83

Earlier quoted context omitted.

The person you're largely agreeing with is Rodney Brooks (formerly of MIT CSAIL, http://people.csail.mit.edu/brooks/publications.html ). And to sum it up a bit, the hypothesis is that humanlike AI is as much a product of the experience and reality of being physically (and limitedly!) human as it is any abstract algorithm. You may also know him from a small company called iRobot (aka Roomba).

Thank you very much for the link, and nice summary. This looks very interesting, I'm grateful: my learning habits mean I'm liable to playing with second-hand scraps of ideas, and missing out on sources.

To elaborate a bit, most of the excerpts I've heard have to do with the availability of sensors.

E.g. Task: grasp an egg without cracking it

Physical platform 1: actuators, no pressure sensors

Physical platform 2: actuators, pressure sensors where egg contacts robot

Inarguably, the simplest successful implementation of the task in driving code will be much more concise for platform 2 than platform 1.

... Now generalize the same idea to trying to teach disembodied AI to be human.

Re: Artificial Intelligence Is Stuck

#109

Post by narrator »

bhickey wrote: post #58
jesperlang wrote: post #54

Earlier quoted context omitted.

Can you describe what you mean by "he doesn't understand"? His background is in psychology and neuro science so his view on intelligence is probably quite different than person coming from computer science. For me he puts words onto something I've felt recently, that what we're doing is cool and all, but just doesn't feel like the right way to approach it. We're just putting loads of data and computing power into som…

I'm riffing on his writing -- > Even Google Translate, which pulls off the neat trick of approximating translations by statistically associating sentences across languages, doesn’t understand a word of what it is translating. This is just another incarnation of "AI is the thing we haven't done." He's parroting Chomsky's disdain for statistical models and John Searle's fundamental misunderstanding of AI. For the forme…

I think the thing that bothers people like the author and Chomsky is that deep nets can't explain or justify how they make decisions in a way that a human could fit in their brain. There is no book called "How To Play Go as well as I Do" by AlphaGo. This is something we're going to have to live with : The machines are smarter than we are, so we won't be able to understand them except at the most basic levels where we use inductive proof to extrapolate our understanding of very small models to enormously large ones that are beyond our ability to fit into our brains.

We can understand how individual chemical reactions in Einstein's brain work, but that doesn't make us smarter than him.

Re: Artificial Intelligence Is Stuck

#110

Post by gwern »

rwnspace wrote: post #10

I sense the hand of an editor. Particularly regarding the title. Embodiment seems to be a branch with low-hanging fruit, when it comes to advancing AGI. I think the economic structural problems are important, but it's possible to over-egg the details and for some lab to stumble on an experimental paradigm with features we didn't realise were implicated a priori. When it comes to other AIs, the idea that we are stuck…

> I sense the hand of an editor. Particularly regarding the title.

Gary Marcus is probably fine with the title. He's been talking down deep learning (and talking up his own more old-fashioned Bayesian flavored ideas and startup) for years now, trying to ignore all the successes like Google's knowledge graph and just omitting the actual research, like when he says

> Such systems can neither comprehend what is going on in complex visual scenes (“Who is chasing whom and why?”) nor follow simple instructions (“Read this story and summarize what it means”).

Which deep learning actually... works pretty well on? Look at Facebook and Google's work on visual & textual question answering using approaches like memory networks.

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