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The end of AI winter?

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Re: The end of AI winter?

#41

Post by dejb »

enki wrote: post #7

The problem with AI is that people try to call simple heuristics and learning algorithms AI, while what we're actually seeing is an overglorified Eliza. The term Intelligence sets the expectation of "universal learning", not just solving problems we previously thought to be hard. And the research necessary to accomplish that, probably isn't even in the same direction as these fraud AI algorithms. The Biological Compu…

> This overselling soaked up the funding with empty promises and killed more basic longterm research. Lets hope serious researchers find a way to get their research funded again, despite the AI shills.

I think this is uncalled for. What makes those who worked on some of these AI problems any different from the founders of an unsuccessful startup? Both have a belief that a particular idea/plan will work and both seek to convince others to join/fund them.

Nobody really knew that many AI problems would be so tough. The people who worked on them expected success. Only through their failures did we know for sure that the problems where a lot harder than we thought.

Re: The end of AI winter?

#42

Post by kansando »

It seems to me that the core dilemma in the AI community has always been - is intelligence a "systems" problem or is it a "general" problem. It seems people first tried a series of general approaches and did not make much progress. Now that people are taking a series of bottom-up approaches in individual domains they are making a lot more progress. So maybe the AI winter is still on for the "general" approach but the thaw is well on its way for the "systems" approach.

Re: The end of AI winter?

#43

Post by enki »

dejb wrote: post #41
enki wrote: post #7

The problem with AI is that people try to call simple heuristics and learning algorithms AI, while what we're actually seeing is an overglorified Eliza. The term Intelligence sets the expectation of "universal learning", not just solving problems we previously thought to be hard. And the research necessary to accomplish that, probably isn't even in the same direction as these fraud AI algorithms. The Biological Compu…

> This overselling soaked up the funding with empty promises and killed more basic longterm research. Lets hope serious researchers find a way to get their research funded again, despite the AI shills. I think this is uncalled for. What makes those who worked on some of these AI problems any different from the founders of an unsuccessful startup? Both have a belief that a particular idea/plan will work and both seek…

i agree it was worth a shot, but it's still a shame they took away the funding from people with more promising approaches and stigmatized the field for decades.

Re: The end of AI winter?

#44

Post by yummyfajitas »

lliiffee wrote: post #34
WilliamLP wrote: post #27

Earlier quoted context omitted.

The trouble with that argument is that if you'd have asked anyone (anyone!), in any AI related field in 1980, where AI would be in thirty years what would they have said? Surely not "Well, for instance one of the greatest achievements might be that we will work on chess algorithms, and we will see some incremental improvements resulting from tweaking certain heuristics and more intelligent pruning through more specia…

My point is that there IS no serious "pure" AI research these days. Your image of lots of pure AI researchers wasting their time is a fantasy-- those people don't exist. People work on applications.

"Those people don't exist" is a bit of an exaggeration. Eliezer Yudkowsky exists, for example.

http://news.ycombinator.com/user?id=eyudkowsky

His research is in making AGI (artificial general intelligence) not go skynet by building in morals. That seems fairly pure to me.

Re: The end of AI winter?

#45

Post by olefoo »

hegemonicon wrote: post #2

The problem with AI development seems to be the assumption that it's going to be a useful business tool. This is sort of like assuming that an artificial organism created in the lab will make a good secretary.

And 20 years after the introduction of the personal computer into the world of business, hardly anyone has a secretary anymore, although the very elite do have "executive assistants" who may be thought of as doing some of the same work functions.

I'm not being facetious in bringing this up, just attempting to point out that a computerised version of intelligence may not look much like the activities it replaces.

I think Dijkstra said it best "The question of whether computers can think is no more interesting than the question of whether submarines can swim."

Re: The end of AI winter?

#46

Post by dlwh »

WilliamLP wrote: post #21

> machine translation, data mining, industrial robotics, logistics, speech recognition, banking software, medical diagnosis and Google's search engine, to name a few. Do these things really directly descend from pure AI reasearch? Or are they really the result of a bunch of clever, yet extremely specialized algorithms, independently developed, combined with an incredible increase in hardware power? Not to say such th…

Successes in Speech, Machine Translation, medical diagnosis and data mining successes have all descended from sound theoretical research in statistics and information theory.

For instance, Machine Translation (as we know it today) was originally inspired by the "noisy channel" for speech recognition that is based on Bayes Rule. In speech recognition, the probability of some words given some input waveform is proportional to the probability of someone saying those words times the probability of hearing some wave form given those rules. The same model led to statistical machine translation: if I speak to you in French, what I'm really doing is speaking to you in English, but the "channel" is so noisy that it comes out sounding like French.

Today, the parallels are less clear (for instance, German and English have substantially different word order, and in speech you don't usually have reordering in the channel--though there's actually some cool new research in MT to bring it closer in line with modern speech processing!).

Yes, there are huge amounts of specialization and hacks for each of these fields, but they are (mostly) based around core good statistical ideas.

In fact, some people are worried that the AI community is so focused on log-linear models and the like that we're in some kind of local minimum, and that we're unlikely to work our way out any time soon.

That said, Kurzweil is still wildly deluded, as you suggest.

Re: The end of AI winter?

#47

Post by giardini »

WilliamLP wrote: post #21

> machine translation, data mining, industrial robotics, logistics, speech recognition, banking software, medical diagnosis and Google's search engine, to name a few. Do these things really directly descend from pure AI reasearch? Or are they really the result of a bunch of clever, yet extremely specialized algorithms, independently developed, combined with an incredible increase in hardware power? Not to say such th…

You're saying a lot of things here but one of your questions is worth answering:

>Do these things really directly descend from pure AI reasearch(sic)?

With the exception of Google's search engine [with whose internals I am not familiar], I can answer an emphatic "Yes". And so would any knowledgeable current or past researcher in those fields. The early AI researchers did a hell of a lot of good work and much of it remains relevant.

As you demonstrate, many if not most people have no idea of what was actually done back then, much less the lineage of their income-tax software or the control system for their digital camera.

Despite funding cuts AI continued to be an interesting and productive field, and remains so today.

Re: The end of AI winter?

#48

Post by runningdogx »

dhs wrote: post #19
jacquesm wrote: post #12

Earlier quoted context omitted.

I don't see search engines as being 'vaguely related to artificial intelligence' at all.

Apparently Google's Peter Norvig does, e.g. http://video.google.de/videoplay?docid=-6754621605046052935&... (he starts talking about the relationship between Google and AI at 06:40).

I don't think Norvig thinks differently; he's just using the term "AI" differently. "AI" in the context of the OP is "strong AI" or AGI (artificial general intelligence). Dr. Norvig takes the term "AI" to also encompass "machine learning" in the sense of developing algorithms that learn within limited problem domains. When Norvig means AGI, he says it explicitly (see the video at around 7:30 to 8:30), and he also says specifically that Google is not interested in general intelligence.

Re: The end of AI winter?

#49

Post by endtime »

yummyfajitas wrote: post #44
lliiffee wrote: post #34

Earlier quoted context omitted.

My point is that there IS no serious "pure" AI research these days. Your image of lots of pure AI researchers wasting their time is a fantasy-- those people don't exist. People work on applications.

"Those people don't exist" is a bit of an exaggeration. Eliezer Yudkowsky exists, for example. http://news.ycombinator.com/user?id=eyudkowsky His research is in making AGI (artificial general intelligence) not go skynet by building in morals. That seems fairly pure to me.

Yes, "Those people don't exist" isn't technically correct; perhaps it should have been "Those people don't exist in significant numbers."

The point is that people who call themselves AI researches, the vast majority of the time are not working on AGI but on weak AI.

Re: The end of AI winter?

#50

Post by plinkplonk »

WilliamLP wrote: post #21

> machine translation, data mining, industrial robotics, logistics, speech recognition, banking software, medical diagnosis and Google's search engine, to name a few. Do these things really directly descend from pure AI reasearch? Or are they really the result of a bunch of clever, yet extremely specialized algorithms, independently developed, combined with an incredible increase in hardware power? Not to say such th…

"pure AI reasearch? Or are they really the result of a bunch of clever, yet extremely specialized algorithms,"

This presumes a dichotomy between "pure AI research" (whatever that is) and "clever algorithms".

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