AI Experts In High Demand

An anonymous reader writes: The field of artificial intelligence is getting hotter by the moment as Google, Facebook, Amazon, Microsoft and other tech companies snap up experts and pour funding into university research. Commercial uses for AI are still limited. Predictive text and Siri, the iPhone's voice-recognition feature, are early manifestations. But AI's potential has exploded as the cost of computing power drops and as the ability to collect and process data soars. Big tech companies like Facebook and Google now vacuum up the huge amount of data that needs to be processed to help machines make "intelligent" decisions. The relationship between tech giants and academia can be difficult to navigate. Some faculty members complain tech companies aren't doing enough in the many collaborative efforts now under way. One big gripe: Companies aren't willing to share the vast data they are able to collect.

Comments

getting a job though is still tough

[deodiaus2]

Getting a job with AI is still limited. Companies don't trust it. Spooky sounding tech scares managers and business decision makers. Better off calling it a statistic driven predictor

Share the data??

[fustakrakich]

That's like throwing money away!

Stop calling it AI.

[Anonymous Coward]

It's a series of complex rules with some pattern recognition, it's not fucking AI.

Re:Stop calling it AI.

[Anonymous Coward]

It's a series of complex rules with some pattern recognition, it's not fucking AI.

*explains how cognition in human brain works*

Re:Stop calling it AI.

[Anonymous Coward]

And what do you think you are? The more I learn about machine learning, the more impressed I am with natural neural networks and the incredible sophistication of the layered methods which are being applied to achieve complex behaviors.

Also:
http://www.artificial-intelligence.com/comic/7

Re:Stop calling it AI.

[ShanghaiBill]

It's a series of complex rules with some pattern recognition

That is also a pretty good description of what a brain does.

Re:Stop calling it AI.

[Anonymous Coward]

Agreed, relationship between machine learning and AI is AI uses machine learning as one of its input mechanisms. It is not the same as AI and has little to do with what AI includes internally.

Re:Stop calling it AI.

[Anonymous Coward]

AI pretty much is learned pattern recognition. That is also what our brains do.

Re:Stop calling it AI.

[Anonymous Coward]

When one cuts off your leg, does that stop your brain? Machine learning = leg neural network, AI =

Re:Stop calling it AI.

[Okian Warrior]

It's a series of complex rules with some pattern recognition

That is also a pretty good description of what a brain does.

That's a pretty-good description of what an *adult* brain does, but it's not a good description of intelligence - artificial or otherwise. Your adult brain learned the rules from its environment with no assumptions about what those rules were.

Try writing an algorithm that can learn to play either chess or checkers, depending on what game it sees.

Make that same algorithm be able to play asteroids, or drive a car, or OCR.

Make that same algorithm be able to recognize a tune ("row row row your boat") even if it's played in a different key, at a different speed, with variations in tempo, and even variations in key.

Any time you know beforehand what the rules are you are not simulating intelligence - you are simulating the *results* of intelligence. You are just writing down whatever it is that the intelligence in your head has decided.

The intelligence never makes it into the program - it stays in your head.

Re:Stop calling it AI.

[Dutch Gun]

Anyone interested in a good theory on how human intelligence actually works should read Jeff Hawkin's (the guy who invented PalmPilot) On Intelligence. It proposes and describes a rather interesting theory on how our perceptions, reactions, and intelligence all work.

Re:Stop calling it AI.

[Anonymous Coward]

= ??? What?

Yes, there is some evidence of abstraction layers in biological neural networks/compartmentalization of functionality.

You have a number of degrees of freedom associated with your leg. Your brain does the inverse kinematics and motor control functions in the cerebellum to handle the lower level tasks involved with translating those desired outcomes in to muscle controls. Meanwhile your visual cortex is closing the loop between the feedback from the muscles and nerves and the visual feedback zeroing in on the completion of the task.

Muscle memory is the process of taking this cognitive load and converting it to what is essentially a look up table of recorded motions. The more times the motion has been trained, the more extensive and robust the look up tables are able to reference with less and less higher level processing. "If this then this" combinatoric decision trees where the process of repetition trains away error and improves the approximations until fluid motion can be achieved at high speed with almost zero overhead.

Deep learning is exciting because it scales well. We can get computers to benefit from the same brute force approach without an army of interns doing laborious preprocessing of data. Unsupervised learning = capital investments in processing hardware and Mobile App Startups and the meaning can be extracted from the data without the assistance of experts.

Imagine a blackjack dealer who doesn't have to hit on 15 and is allowed to count cards. With enough video footage of professional poker players, you may someday be able to train a machine to call Doyle Brunson's bluffs.

What does that mean for retail investors on Wall St.?

Re:Stop calling it AI.

[ezdiy]

Quite the opposite, strong AI was the previous boom/bust.
This time we're using "sheer brute force" to train NNs in a bid to get emergent intelligence-like patterns, instead of using formal logic constraint solvers.

Re: Stop calling it AI.

[Rich0]

People are not tabla rasa. Evolution has baked in all kinds of assumptions.

Absolutely true. Kids learn to not touch the stove after burning themselves once. They were born with some kind of sense that pain is bad and to be avoided.

I think that if you could figure out the motivation bit, that would be half the battle.

And people aren't universally good at the motivation bit either. They buy lottery tickets, smoke, fail to estimate risk in a sane manner, and do all kinds of dumb stuff where the instincts they were born with basically reduce their chances of having surviving progeny.

Re:Stop calling it AI.

[ceoyoyo]

Many modern AI methods take advantage of unsupervised learning. Not only do they not need to know what the rules are, they don't even need to know the right answer most of the time. There are successful demonstrations of such algorithms learning to play Nintendo from watching people play, and Google's deep learning network learning the concept of "cat" from watching YouTube videos. I also remember a paper looking at recognizing melodies played in different keys.

Your knowledge of AI is a couple of decades out of date.

Re:Stop calling it AI.

[Dixie_Flatline]

If you show a very young child (less than a year old, I think) something 'impossible' happening, they will pay attention to it for longer and find it more interesting. So if you hold a ball in the air and let go, but it doesn't fall, or you throw a ball and it goes through a wall, a baby can recognise that those are weird events, and will stare at them for a long time.

If you then give the baby a choice of toys, amongst which is the ball that did an impossible thing, they will spend more time playing with it, rather than equally spreading their attention around. Moreover, they will conduct small experiments that are related to the impossible thing they saw. They will pick up the ball and drop it repeatedly to make sure gravity works. They will hold the ball and bang it on a surface to make sure that the ball does not arbitrarily pass through things.

The brain has a lot of stuff built into it. There are whole sections of the brain devoted to image processing, or understanding smells and taste. These are not inconsequential starting points.

Re: Stop calling it AI.

[mSparks43]

I find it best to just call everything I do Ai.
that way all the idea thieves have no idea how I do what I do.

Re:Stop calling it AI.

[Livius]

Your adult brain learned the rules from its environment with no assumptions about what those rules were.

So very, very wrong. Well over 90% of what the brain does, even consciously, is either instinctive or a behaviour learned almost entirely from instinctive triggers.

Study someone with autism to see what the brain has to deal with when even a few of the built-in assumptions are missing.

Re:Stop calling it AI.

[gweihir]

Oh? And how do you have knowledge of how that works? Because, you know, the scientific world does not at this time.

Statistics cannot lead to intelligence. If you knew anything about either you would not claim such nonsense.

Re:Stop calling it AI.

[gweihir]

People want to believe that nonsense because people are, on average, deeply stupid. And no, it is not AI at all. The human race is not capable at this time to produce any AI that deserves that name.

Re:Stop calling it AI.

[gweihir]

Ah, a physicalist quasi-religious fanatic. Nice. Your delusion does not cause the world to work like you believe it works.

Re:Stop calling it AI.

[gweihir]

At this time it is still completely unknown what the brain does to manifest intelligence. Have a look at some research before claiming utter nonsense.

Re:Stop calling it AI.

[gweihir]

Excellent explanation. The brain certainly has some automated components that are not intelligent and they are configured by actual intelligence as you describe. What that actual intelligence is, how it works, and why it is only observable together with consciousness is completely unknown at this time.

Unfortunately, this explanation will fly right over the heads of most people here.

Re:Stop calling it AI.

[gweihir]

The formal logic approach is still the only one that has a theoretical possibility of creating some aspects of true intelligence. Unfortunately, in this universe, it fails even at small problems due to limited computing power available. The brute-force approach is good enough to simulate very limited intelligence when an incredible lot of data is available. That has nothing to do with intelligence though, and statistical approaches cannot simulate more complex chains of reasoning. They are always shallow. On the commercial side, even shallow models can work, but calling them AI is just misleading.

The sad fact of the matter is that most people are morons and hence even a shallow, statistics driven system can now be a moron that is just a bit smarter than them (or rather knows more). Hence for many mundane tasks, humans are becoming redundant.

Re:Stop calling it AI.

[Anonymous Coward]

But that's still not strong AI because it doesn't do anything with the information it gains.

Re:Stop calling it AI.

[Anonymous Coward]

You're making muscle memory more complicated than it is. Myelin grows around neurons when they fire. Think of myelin as a wire coating that improves the quality, speed and conductivity of its wire, like a Monster cable if they actually lived up to their ads. Repeating an action uses similar neurons so those neurons gain more and more myelin compared to the others around them. Soon those neurons outperform their neighbors so well, you no longer need to direct your movements. Just a tiny thought to get to the start of that myelinated race track and off the signal goes! The other pathways don't have a chance. The myelinated path is faster and more efficient (less signal loss), so not only does it reach the goal faster (some signal/decision to move) but it's also stronger than other movement messages.

To break muscle memory, you need to make the mental effort to direct the energy through the slower paths. Eventually they build up and the other path breaks down. Myelin doesn't last forever and sadly our ability to regenerate more reduces with age.

I wouldn't call it "if this then that" or look up tables. It's more like following the path of least resistance. Staying on the trail while hiking though the woods since the path is easier to follow.

Re:Stop calling it AI.

[Xest]

Well I'm glad we have you here to arbitrarily define intelligence. It's about time, the human race has been struggling to define it precisely for hundreds of years.

Where have you been all this time of self-declared definer of terms?

But just to clarify, basically, what you're saying, is that intelligence is a form of magic that we have inside us? Where inside us does this magic exist? Where does it come from? Are you saying it's a special undetectable thing? Your comment seems to imply it disappears in adults, but we can't detect it in babies either.

We can't do any of the things you suggest because we don't have computers even remotely as powerful and capable of rapid complex processing as the human brain. I also can't teach a dog to do any of the things you suggest, so are you declaring dogs as being unintelligent? Your examples seem to suggest that intelligence is unique to human beings and nothing else has the capacity for intelligence.

Re:Stop calling it AI.

[ezdiy]

The formal logic approach is still the only one that has a theoretical possibility of creating some aspects of true intelligence.

Sort of. We actually do have fairly robust theorem solvers written in prolog, but thats not enough. Intuitively, "true AI" works like extracting formal logic theorems out of huge set of before/after data fed to a blackbox.

Just like humans do something intuitively at first, with some degree of success, but when they find rational backgrounds (with help of formal logic rigor) behind that intuition, it gives significant accuracy boost. The two work in tandem - formal rigor is toothless when facing the totally unknown, but can explain it after intuitive models are trained and it can feed its hypotheses into them in lieu of farmed data.

Trouble is that layered NN camp ("intuitive") and formal logic camps are still too separated. But corporate interests will force merger to a degree.

This is most visible in speech recognition, and more recently, vision where formal grammar models sit above low level intuition NN, or better said, directs training of layers so it can work with less data and reason about unknown inputs because it actually "understands" what's going on on a formal level.

I'll believe it when...

[grimmjeeper]

... the companies are actually willing to look beyond H1B visa holders and low wages. If they're not yet ready to pay what a real expert costs, they're not really in high demand.

Re:I'll believe it when...

[Anonymous Coward]

I think there are two other fundamentally opposed pieces at work here:

1) Academia: "Give me money so I can do research and publish my results to further the science"
2) Corporations: "I'll give you money to do something specific, but don't tell anyone else about it"

Re:I'll believe it when...

[ezdiy]

It's not that bad, but the gist is similiar.

1) Megacorp allows to run your models on their data, and you can write paper about it
2) But your results are not reproducible, because well, private corporate data

Solution indeed is to put the training sets in the public domain.

What are they looking for?

[__aabppq7737]

to help machines make "intelligent" decisions

IMHO, AI is more than just a way to profit off of individual consumers' weaknesses.

I, and probably a lot of other people out there, would be very interested in knowing how to create a 'vacuum' program that could know it all. This power would be abused within months after creation, but at least it would be in the hands of the people, not in some giant's arms, so abuse wouldn't span too far.

Re:What are they looking for?

[PPH]

know it all

First: Start with training examples extracted from Slashdot posts.

Re:What are they looking for?

[Anonymous Coward]

Uh, are you sure you'd get intelligence from those?

Re:getting a job though is still tough

[Anonymous Coward]

Tech people don't understand it either. Just look at the article in Slashdot the other day about guessing age. It gets it wrong some times. Wow. That's kind of the point. Cars driven by an AI will crash sometimes too. And financial AI systems will make the same kind of mistakes humans make, in addition to the ordinary bugs. The technology has its place. But it isn't something that magically does the right thing.

it's really the easiest way

[Anonymous Coward]

to get a million dollar salary

Err: 'consistency' not in {Corporate America}

[Anonymous Coward]

My last company, a telecommunications giant, paid me a very decent wage for "advanced data-driven modelling" and yet sought at every turn to discard the people I relied on at work in favor of cheaper, significantly-less-adept replacements.

When you have managers, senior managers, directors, executive directors, VPs and Senior VPs in a chain of custody, all striving to differentiate themselves in interesting ways, the concept of internal consistency is just laughable.

So, it could in fact be the case that the demand is going up for good AI people despite your accurate observation, and I hope they will be smart enough to do their research and find out if they will be swimming in a sea of bureaucracy and incompetence before they take the jobs.

But I'm not bitter. :)

The Winner

[Etherwalk]

And what do you think you are? The more I learn about machine learning, the more impressed I am with natural neural networks and the incredible sophistication of the layered methods which are being applied to achieve complex behaviors.

Exactly.

Besides, the first entity that gets a functioning superhuman brain, if it has enough lead time over its competitors and is able to gain enough data and indoctrinate goals, is very likely to win. This applies in every field of human endeavor. Think of the enormous transaction and synchronization costs we have to deal with in the incredibly inefficient networking between your brain and mine, for example. Now network a hundred of those brains together with those costs a few million times smaller...

It won't happen all at once like that until it does, of course.

Yet to see a job post for AI work

[Anonymous Coward]

As an AI software developer, I am yet to see a job opportunity or even a job posting in this field. I see data analytics and optimization software jobs, but I suspect this article is a few years ahead of when this would actually happen. So far, high demand with near 0 job opportunities.

Re:Yet to see a job post for AI work

[ezdiy]

The trend is real. Its not called AI, but "deep learning". Basically Google and Facebook bought few datamining companies and ball got rolling.
Google torch7 for specific stuff.

Re:Yet to see a job post for AI work

[gweihir]

Only problem is that buying companies that already do it does not create any jobs.

Re:Yet to see a job post for AI work

[gmiller123456]

I doubt you'll ever see a job posting for an AI position. All products have a high failure rate of reaching the market, and I imagine the AI product failure rate is astronomical compared even to "regular" products. Large companies tend to buy out small companies that have developed slightly successful products, and they make money by enhancing and marketing them. Very rarely do large companies like Google, MS, etc actually put money into research developing new things. So, I think if you want a job in AI, you're going to have to invent something yourself.

Hey guess what?

[Anonymous Coward]

I don't care about this story.

Re:getting a job though is still tough

[Tablizer]

The technology has its place. But it isn't something that magically does the right thing.

It only has to be slightly less stupid than typical humans, and/or cost less than humans. It may also need more trace-ability, such as knowing why it gave an answer it did. With humans you can ask and usually get an answer such as "we always did it this way", "that way usually works for me", or "because the alternative confuses the sales team", etc.

But career-wise AI has had multiple boom/bust cycles as the usual hype-masters overdo claims and damage AI's cred. Have a Plan B if you go into AI. (No, not a Plan 9.)

Re:getting a job though is still tough

[Dutch Gun]

The term "AI" dropped out of favor a decade ago as a result of a lot of over-promising and under-delivering from the decade before that. Remember "expert systems"? Yeah, that was "AI" in a different guise. It looks like the term "AI" is making a bit of a comeback. I'm not sure that's a good thing, because it never really describes these systems adequately, as "intelligence" has very little to do with it.

They reall don't mean this

[JustNiz]

>> AI Experts In High Demand

What they really mean is business data-mining experts. Unfortunately AI expert just sounds cooler and is easier to say, no matter how far from the truth it is.

Re:They reall don't mean this

[Anonymous Coward]

Yes. This.
AI PhD students here. 3 of us looking for an internship for the summer, plenty of software engineering or "data scientist" positions. Nothing really relevant to AI. CV available if anyone interested. Otherwise we will just default to TA positions... 84@drexel.edu

Re:They reall don't mean this

[ezdiy]

Yes and no. Fun stuff is still done, especially in terms of computer vision and hearing - there are numerous stakeholders.

However zero interest in actual research, it's all engineering.

They do not want code monkeys, as you still do need a PhD-level knownledge to even design this kind of stuff, just like computers in the 60s. Thats why companies are bought and people are hired only if they have something useful to show already in applicable field.

Re:They reall don't mean this

[Anonymous Coward]

Well Siri can be classified as AI, but calling predictive text AI is just ignorance.

Re:They reall don't mean this

[Anonymous Coward]

No, they don't. As someone employed in this field, PhD in AI working at a large tech company, etc, it's as much about building dynamic, heuristic programming models as it is about autonomously classifying data (or, what you casually refer to as 'data-mining'). This includes self-healing software, monitors that write themselves by linking service-level-objectives to performance metric behaviors, and a number of other processes.

Re:They reall don't mean this

[Anonymous Coward]

AI MS grad here. There's AI jobs, but none at the intro level. If you've already got 7 years of demonstrable AI work (schooling doesn't count) then excellent. If not, sorry you don't pass the min job requirements. AI internships are ever harder to find. I was luckily enough to get two, but that didn't give me enough experience for a full-time AI job. You need near their exact tool set they're using too. Companies don't train for specialized fields.

Re:They reall don't mean this

[rtb61]

AI is actually far different to data analysis, it is all about different layers or levels (https://www.youtube.com/watch?v=aQyXeLSL0II ;) ) of decision making. So you start off with very simple solutions and if they are good enough you stop there, if not enough you use those outputs in the next higher or adjacent level or and add more different levels for more outputs, until your arrive at the answer. Not based upon the current level of analysis only but also on all the previous ones, it becomes a composite solution, which readily varies processing time with regard to the complexity of the question and complexity the final solution. The greater the number of possible solutions you can generate, the greater the ability of the artificial intelligence, by using composite outputs from different levels analysis, you greatly increase the number of potential outputs.

Re:They reall don't mean this

[Anonymous Coward]

If you don't understand the relationship between AI and data science then you should probably just give up now.

I suspect there's a reason you're not finding your internships - you've no idea how AI is used in the real world.

I do data science, and AI has had the most profound impact on what I've been able to achieve in this field. Specifically I use a number of AI solutions to classification and clustering problems to detect and prevent fraud using large financial and social datasets.

But I've also worked in the world of mechanical engineering too and was able to apply AI to successfully improve the design process of their systems making them drastically more competitive than the competition.

You rarely get jobs that are advertised as "AI" jobs. You take your AI knowledge and figure out how you can redefine a field with it, but to do this, you need to have a much broader understanding of AI and how it's used than you apparently have currently.

Re:They reall don't mean this

[JustNiz]

Ugh you appear to be one of those many dudes that just do web stuff but try hard to make it sound much cleverer and more important than it really is by using a bunch of crapspeak.

For example self-healing software sounds very AI but its just crapspeak for fault-tolerant, which is pretty much how any _good_ software engineer would intuitively design a system without even thinkng twice about why. I remember when it was just called common sense and experience.

Hey, Paul Graham can get another job, then!

[Rinikusu]

All those 80s era AI LISPers are rejoicing.

Re:Hey, Paul Graham can get another job, then!

[itzly]

I doubt that LISP is useful for modern AI systems.

Re:Hey, Paul Graham can get another job, then!

[Anonymous Coward]

All those 80s era AI LISPers are rejoicing.

LOL, that's exactly what I thought when I read the headline - time to oil up the ol' parenthesis keys!

Re:Hey, Paul Graham can get another job, then!

[Virtucon]

I hear Ruby does LISP really well especially when using systemd to orchestrate it.

Where it's needed isn't where it's useful

[Anonymous Coward]

Where AI is needed and useful:
Medicine

Where AI is needed, but not terribly better than people:
MMORPG's, Spam filters, Bank-fraud detection

Where AI is evil, and only robs investors:
Investment Banks High-Speed-Trading

Comment removed

[account_deleted]

Comment removed based on user account deletion

AI Researchers Wanted

[Anonymous Coward]

CompLImentarY cake and nERve toxiN PROvided freE to all appliCanTs
-GLaDOS

Re:getting a job though is still tough

[Anonymous Coward]

Uh, the term 'expert systems' predates 'AI'.

Re:getting a job though is still tough

[Anonymous Coward]

Uh, the term 'expert systems' predates 'AI'.

I'm not sure where you got this information, but as someone that studied Artificial Intelligence in college (in the 80's), I can assure you that Artificial Intelligence has been around far longer than Expert Systems.

Expert Systems are usually considered one of the first successful forms of AI, becoming of practical use in the 70's, and then proliferating in the 80's.

But Artificial Intelligence as a field has been around since the 1950's.

Here's some links about both of these terms:
http://en.wikipedia.org/wiki/Expert_system
http://en.wikipedia.org/wiki/Artificial_intelligence

Re:getting a job though is still tough

[Dutch Gun]

Uh, the term 'expert systems' predates 'AI'.

Nope. The term "artificial intelligence" was coined in 1955 by John McCarthy. Edward Feigenbaum is considered to be the father of expert systems, and first published a paper about them in 1977.

Siri

[NostalgiaForInfinity]

Predictive text and Siri, the iPhone's voice-recognition feature, are early manifestations.

Just remember that iPhone's voice recognition comes from Nuance, not Apple, and it's been developed over several decades.

http://en.wikipedia.org/wiki/N...

Re:Siri

[NostalgiaForInfinity]

One should add that the other part of Siri, the dialog AI, also didn't come from Apple, it came from SRI (probably related to the overall name).

Drat.. I should have said yes..

[modi123]

Awwww, man! I should have said 'yes' to that Mizzou grad school acceptance and, after ten patient years, pounce and corner it all!

Galactic News Unintelligent species believes it

[Anonymous Coward]

has invented artificial life! See the video in the humor section. Really, we have gods who care about us individually and we kill because other people whom don't respect our gods, their disciples, their prophets, or the mater their words are written on. On a planet where more than half the 'intelligent' population lives in abject misery and poverty, we claim to engineer and judge intelligence. We pump poison into ground water and sell filtered water, we pump poison into oceans and kill off the one environment that is unquestionably the largest contributor to sustenance for all life on earth. 1% controls 'owns' more than half of all the resources on the reachable planet. People, this isn't intelligence. This isn't to say that glimmerings of intelligence don't happen, just that when it happens, it is a million times more likely to be stomped out with passion.

AI is Like Fusion, Always 25 Years Away

[Anonymous Coward]

The field of AI is always falling in and out of vogue with the investor class. Typically they pour money into hiring AI experts or conducting research only to realize, after spending a great deal of time and money, that their investment isn't panning out quite as quickly as they'd hoped. In response, they pull their money and AI falls into disrepute for a decade or so until the next group of investors comes along and repeats the cycle. For example, does anyone else remember those "expert systems" from the early 1980s or the amazing software that will enable your secretary write code? In reality we have 50+ years of research into AI without all that much to show for it compared to what we've put into it. That's been a dirty secret for a long time in CS circles, but it's not as widely known because people are easily fooled by neat toys like Siri or their Roomba vacuum and don't realize that what's behind those "innovations" is basically glorified pattern matching and search.

Re:AI is Like Fusion, Always 25 Years Away

[lucien86]

Not entirely nothing. Computers themselves emerged at least partly from AI research. The real problem with the field is that for decades computers simply didn't have the power needed for Strong AI, even today they only barely do and still hit several near vertical walls - especially with reliability. I'm working on a Strong AI project and the heart of this work today is developing a custom hardware & software platform..

BTW : Nuclear fusion - working reactors do now exist, and they are now getting close to break even, and for power gen the technology is now really 20 or 30 years away. The real crime with fusion is lack of funding, poor planning, and inefficient organisation - otherwise we could already have commercial fusion today..

Obviously...

[tlambert]

Obviously... if it's AI, and it has some real world utility, then we rename it so that it's not AI any more. Then we complain loudly that "AI has never produced anything useful".

Re:getting a job though is still tough

[Anonymous Coward]

AI hasn't underdelivered, on the contrary, it's proven to be one of the most fruitful areas of computer science research. The summary demonstrates the basic misconception of what AI is or does. The idea that AI has failed unless it's producing a strong, human like AI is just stupid and shows a complete ignorance of the subject. The summary states:

"Commercial uses for AI are still limited."

Right. Because no one uses Google search, spell check, adaptive network routing and so on?

But producing actual intelligence is the end goal of AI, not the whole of the subject. AI has no more failed as a subject because we don't yet have sentient robots wandering around doing our bidding than Physics has because we don't yet have a grand unified theory of everything.

To expect that a complex subject can go from conception to perfection in just 40 - 50 years is absurd when we still don't really have a complete grasp of the nature of intelligence itself - it's hard to replicate something you don't yet fully understand and can't yet fully and consistently define.

AI first and foremost is about producing more intelligent systems than we have now, and yes, in the end that will hopefully lead to human like or beyond human like intelligent beings, but for now, I struggle to see how a subject that has led to more intelligent systems that are used day in day out by just about everyone using a computer is a failure.

I don't even really understand the jab at expert systems, they are what they are, they were invented, they're used regularly in businesses across the globe. What's the problem exactly? Were you expecting them to evolve overnight into a robot Arnold Schwarzenegger even though they were never really built with an adaptive and self-evolving component in mind?

So AI's real problem is that it's held to a much higher standard than most other topics, mostly fed by media driven childish impatience towards demanding clever robots to make our lives better. People have this view that if they understand it inside out then it's not intelligent, they attribute some kind of magic to intelligence, but the reality is that even human intelligence is probably just a very complex algorithm running on a very complex bit of circuitry. Once we figure that out it doesn't mean we're no longer intelligent, any more than the fact that because we all understand how to implement adaptive network routing doesn't mean that such routers aren't more intelligent than they were without those adaptive algorithms that came from AI research.

AI hasn't gone anywhere, it hasn't failed or under delivered. Yes, there are people who make absurd claims about what is achievable in what time frames, but even the great Stephen Hawking has failed to achieve some of his claims about what would be possible in a given timeframe in the world of Physics. We can't write off or condemn a subject based on a few overestimations. Objectively, the subject has born fruit. It's efforts have produced results that make every day computing that little bit easier because of slight but incredibly useful advances in machine intelligence. Intelligence doesn't necessitate running round like a human, intelligence sits on a sliding scale from simple emergent the workings of ant colonies which we can now pretty much perfectly replicate, through to the intelligence of humans which we're still a long way away from.

Mostly, the perceived failures in AI come from folks who are over-expecting, and under-crediting. The only thing AI has to do is make systems more intelligent, or at least, appear more intelligent than they once were and it's done this astoundingly well. My car can detect things I can't, my train gets rerouted automatically to avoid disruption and prevent congestion, my search gets correct to find what I actually wanted rather than what I typed, my spelling mistakes get corrected in e-mails, and I can access sites on the internet being automatically routed around disruptions. I get home and my console recognises my face and logs me in,

Re:getting a job though is still tough

[Anonymous Coward]

Judging from their results most people working on AI could be replaced by a toy bird.
Where's my job at Google higher management?

No they are not in high demand.

[Anonymous Coward]

Speaking as an AI expert I can confidently say that no, we are not in high demand. And yes, I am currently looking for work.

Scary AI?

[Anonymous Coward]

And the state of AI can be judged by checking out www.theysay.io's sentiment analysis.

Re:getting a job though is still tough

[lucien86]

Sadly that's absolutely true. I know because I have been developing a Strong AI project for over 20 years. Strong AI is one area where I would definitely NOT bet on university research, and am pretty sure it will only ever be an outsider like me who succeeds..

Re:getting a job though is still tough

[lucien86]

Not sure what they were naming it but AI research dates back at least to the 1930's - for instance in the work of Alan Turing. And a lot earlier if you count the logicians. It was only as the field developed that the search for mechanical intelligence became separated from the field of general computing...