back to article Mything the point: The AI renaissance is simply expensive hardware and PR thrown at an old idea

For the last few years the media has been awash with hyperbole about artificial intelligence (AI) and machine learning technologies. It could be said that never, in the field of computer science, have so many ridiculous things been said by so many people in possession of so little relevant expertise. For anyone engaged in …

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Headmaster

Naysayer sauce but where is the beef?

In other words, there has not been any significant conceptual progress in AI for more than 30 years.

I'm sorry but that is completely wrong.

If nothing else, we have learned that a lot of problems can be semi-successfully attacked by function fitting. and theoretical work is advancing.

Judea Pearl has advanced the causal revolution like a bulldozer, electrifying the field that dogmatic statisticians have kept sterile since the early 1900s.

Rodney Brooks has been working rather well on advancing robotics.

30 years includes work by Hofstaedter too, so GOFAI has had its advances.

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Um, since when has robotics had anything to do with AI outside of Asimov's books and Star Trek ?

Is AI supposed to be some sort of tailor, able to function fit at a whim ?

And I'm very glad that you are so excited about statistics, but that has nothing to do with AI. We have very capable, specialized statistical analysis machines today, that I do not dispute, but we most definitely do not have AI nor are we any closer to getting to it. Especially not with statistics.

If you don't agree, tell me just how much data do you analyze in the morning before turning on your coffee maker.

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Expert Systems

I've been saying for years that these are Expert Systems, not Artificial Intelligence. AI as a term applied to 99.99% of everything over the last few years is akin to calling a Horse and Cart a StarShip. I have no doubt that we will eventually get AI, the same as I believe we will one day travel to the stars (if we survive), but we ain't even close yet.

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Re: Expert Systems

AI is the complete domain. It includes expert systems. Machine learning is a distinct domain (along with others like genetic algorithms) alongside expert systems.

Deep learning is a subset of machine learning.

No one disputes this to be true. If you want to learn more about the machinations that the AI community had thinking about whether an expert system could really be 'sentient' (which doesn't equal AI) - it's worth looking up the Chinese room though example.

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JLV
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Good article, need more

Very well-said. Pattern recognition and trained systems _are_ impressive. Back in the 90s the little we heard about AI had a lot to say how hard it was conceptually to design a computer to recognize objects* (granted, more T-72s & 80s than cats). We seem to be making excellent headway there - and, again this is a significant field. In many ways it has more real world relevance than most of the fledgling real AI work to date.

And the Go-winning computer did have some fairly novel takes on strategy IIRC.

But is not making thinking computers, let alone self-aware ones. That's a subject that is both the perennial 20 years away, always, and not talked about much these days.

I'd be curious to know how much this new found fervour for "fake" AI has impacted funding and researcher uptake on actual AI - the kind where a computer could reliably infer and respond to a new question like "is there water in the fridge?" without scanning millions of dialog transcripts to guess or being an advance-built kitchen/appliance narrow specialist. What's that field up to?

I'll guess it's meant massive brain and $ drain but would welcome a future article.

p.s. old book, but 'Blondie 24' is an accessible and entertaining pop sci take on neural nets. author site: http://www.davidfogel.com/ No affiliations on my part.

p.p.s. re the black-box, can't-explain objection to neural net AI, that's a valid point, but there's no guarantee a "more worthy, traditional" AI system that isn't based on humans pre-entering rules would automatically be transparent by nature.

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Ayup, artificial intelligence and quantum computing may be usable soon after fusion power is realized.

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Thinking Machines

I can still remember Thinking Machines and their marvelous 1024 core computer.

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Bravo

The only intelligence in AI is human intelligence to write a very complex algorithm. However there is an adage about curve fitting: "With enough variables you fit an elephant". So I wonder if 'AI' systems are fitting so many variables that with enough 'training' they can be made to say anything you want.

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Re: Bravo

"With enough variables you fit an elephant".

in the 1500s we called those "epicycles".

Yup, particle physics: if something behaves differently than predicted, there "must" be a new particle. Circles on circles, seen that.

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I appreciate the debunking of hype, but there has been a genuine breakthrough in machine learning that has led to amazing results in image recognition, speech recognition, OCR, and translation.

Geoff Hinton discovered that neural nets could be trained in a greedy, layer-wise fashion (https://www.cs.toronto.edu/~hinton/absps/fastnc.pdf). Neural nets were previously limited to two or three layers, and now they can be deeper. This moved some problems from the realm of "too hard" to merely "hard".

There's a lot of noise and hype and businesses trying to sell crap marketed as "AI". But behind all that, there is something truly amazing. I don't normally comment, but I felt like this piece missed that, and I think it's a shame. The positive thing behind all of this hype is so much more fun than complaining about the hype.

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(Written by Reg staff) Silver badge

"there is something truly amazing"

FWIW it is an opinion piece by Andrew.F. Think of it as an antidote to all the hype.

While there is a hell of a lot of nonsense around AI at the moment, there are some interesting, and some rather crap, research projects and products, which we write about on a daily basis.

C.

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> I appreciate the debunking of hype, but there has been a genuine breakthrough in machine learning that has led to amazing results in image recognition, speech recognition, OCR, and translation.

I fully agree that there's been some amazing results in various fields, as a result of improvements in machine learning.

But the point of the article is that this machine learning isn't generating "intelligence": it's generating a tool (aka expert system) which is very good at a single job presented in a specific way. Change any of the parameters and the tool will shatter.

Personally, I think it's highly debatable as to whether the current approach to neural networks is ever going to be able to produce something more than a tool.

But in the meantime, there's a lot of money to be made from promising the earth, much as happened during the last few "Next Big Thing" waves (3D displays and VR, blockchain, etc).

Some people will get rich, some early adopters and angel investors will lose out and a few interesting things of actual use will emerge. And then the cycle will begin anew!

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Anonymous Coward

Re: "there is something truly amazing"

"there is a hell of a lot of nonsense around AI at the moment, there are some interesting, and some rather crap, research projects and products, which we write about on a daily basis."

So?

El Reg used to cover Captain Cyborg, once or maybe even twice upon a time.

Where did that lead to?

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Captain Cyborg

Those articles — far more than two, AFAICR — about prof. Reading from Warwick University (or was it prof Warwick from Reading University?) certainly lead to a lot of readers being thoroughly entertained, which is no bad thing.

And what this article leads to is, hopefully, that just as many readers will realise that the current state of the art in “AI” is at about the same level of “cyborg” that he represented. How is that not a good thing?

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Excellent - liked the "Or haven't yet."

...and it's that line that drives the current madness.

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Yes, quite so. Technical people who are passionately interested in this stuff, often make some extremely troubling statements about it. Muggles, as one would expect, completely fail to get it.

Artificial Intelligence, as we have it today, is not really intelligence. There's not a soul or a consciousness in there. There's a machine, a computer system and program (s) that do some things one would associate with neural networks, and some to do with fuzzy-logic and some that have to do with dumb statistics.

Dumb statistics... Go buy a book, that teaches you how to play poker, and one major subject will be the odds of getting a pair, or 3 of a kind, or a flush, or a house full. Armed with a little bit of base cunning, and a good working understanding of the betting system, and a splash of cunning human psychology, AND the knowledge of how likely it is anybody else at a 4 hand table, where one has folded, and you hold a king high straight... has a hand that can beat yours...

Dumb statistics don't make you intelligent, but they do provide you with enough help to make decisions, and probably better decisions than most of the roobs you'll be playing against.

A system like this can be trained to play a complex game like Go, or Chess, better than any human player alive. But that doesn't make it intelligent. It can and it does make an extremely useful tool, which can maybe find better choices and strategies than you most of the time.

But that expertise doesn't tell you what to do if you spot a round metallic hole up the sleeve of the player opposite you. "How to win at Poker" doesn't explain Derringers. It doesn't know the house can get a "maid" in to do some housekeeping while you're up, and have her bend over and show you she isn't wearing any.... which is prone to cause some degree of distraction....

Artificial Stupidity doesn't "Understand" anything, the way a human does. It doesn't think.

It can be incredibly good at what it does, but it's nothing like "intelligence" in the way we think of it.

Now that's not to say it's no good. It is good, but it has limits. Like fire, you have to learn to use it. Like a magnet dangling from a thread, it can tell you something you otherwise wouldn't have known... But the fact you've discovered the Compass, doesn't mean you're God, and doesn't mean it's God either.... It is a very useful trick. It does make navigation easier. But, you've still got to row, and bale, and try not to capsize..... It's not the hand of God and it's not the answer to all your problems. It's a tool...

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JLV
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>A system like this can be trained to play a complex game like Go, or Chess,

good point, but to go further the current state of the art is a computer can’t be taught Go and Chess together (other than doing it twice). it really is very single-purpose, there is _no_ generalization involved in the actual learning.

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Anonymous Coward

I agree

I have long disagreed with all these predictions of machines being self aware. We do not yet understand what consciousness is. There is an assumption that its an emergent property that appears once there is a certain level of complexity, but we have abolutely no evidence of this.

There is a HUGE difference between a self learning system and a self aware system. We have made incredibly clever and sophisticated systems but all the fears of Musk and Hawkins etc that current AI is on a path where some kind of super consciousness will emerge is bizarre. None of our neural networks have anything that even hints at any level of consciousness. Even cats and dogs and mice and creatures that are largely instinctual still have a level of consciousness that we can only emulate - we can’t reproduce it.

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Well..

One skill Hassabis certainly seems to have is the ability to be tremendously excited by the work he's doing, and to communicate that excitement to people who might pay him. He's had quite a long history of building emergent systems of various sorts, and promising that each will deliver a unique experience. I'm sure there are interesting and novel components to his work, but casual inspection usually results in devs going "Ah, so he's doing <X>", where <X> is a fairly well known technique, being applied to ever larger data sets.

This seems to be a common theme in AI research, where researchers posit that if the data set is big enough, eventually we'll get something new. It's unfortunate to confuse that with the less impressive flashes of insight into particular systems that fill most press releases. "We discovered that <doing something counter-intuitive> results in <some desired outcome>" sounds like a great leap has been made in understanding, whereas it's usually just the case that dispassionate data analysis has revealed unusual correlations.

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Sigh

Here we have an author who displays a limited understanding of the subject, and an axe (hardware innovation) to grind. Of course the Reg Commentariat, which tends to curmudgeonliness and cynicism (not bad qualities) agrees.

Yes, popular accounts of ML research are overstated, oversimplified, and often incorrect. Yes, they employ vague and misleading metaphors. In what area of research is this not true?

And if you're going to object that ML algorithms don't display "creativity" or other anthropomorphized features, I'd like to see an applicable definition of those features. While we're at it, can Fentem or any of his commentard supporters explain how the human mind is anything other than the effect of a mechanism, and thus anything that is qualitatively different from a computable function?1

And a more specific objection: Fentem's claim "In other words, there has not been any significant conceptual progress in AI for more than 30 years" is bullshit, for any useful definition of "AI". Even a cursory review of several of the many papers on ML in, say, Adrian Colyer's blog shows that there has in fact been considerable conceptual progress in the field. Also, not all ML systems - not even all NN systems - use backpropagation; see the extensive research on gradient-free optimization of ML systems.

I do think that ML is in a bubble right now; that it's oversold and over-applied; that research is already demonstrating that our ML systems are much more fragile and considerably less compelling than they might seem when you just look at the shiny demos. But to claim that the field hasn't advanced in 30 years, or (more egregiously) that only some sort of vague, handwaved hardware approach can produce true innovation, is rubbish.

1 And no, I'm not buying Penrose's appeal to quantum effects. As Thomas Metzinger put it, "For middle-sized objects at 37°C, like the human brain and the human body, determinism is obviously true". I might consider "obviously" a bit strong, but the burden of proof falls to the non-determinists.

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Alien

AI proves Creationism

If there really is any "creativity" here, it is the creativity of DeepMind researchers who devise and manage the processes that train the systems.

Yup, my point exactly. There has to be an Architect (or a pony) somewhere

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Hear hear!

I was into AI as part of a dot-com in the '90s.

Every time I have a conversation with current devotees, it sounds like the same stuff, nothing really new. Actually, we had better, ginormously more efficient code, these kids nowadays cannot do anything low level, it seems. Makes me think on how making a cup of tea can kill the biggest processor ever - just make enough layers of interpretated code, voilà.

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Great article Andrew.

In the early 90s I took backpropagation to some of the limits we see today .. And discovered that I need to do something new and different. (Actually, I had to go back the 1970s and get "caught up!" ) Even now it has taken me over 30 years since working thru cognitive theory after theory (while working for companies on DoD funded AI projects) to find the right mix of sauces. Which I have now worked independently for the last 6 years. And just now only 80% confident that I maybe know what needs to be done to not waste mine and others resources, Now I am at a conundrum. I can go to work for a company (two have offered) that is willing to fund my research but I have to give up rights to my work AND basically working alone?!. What is the point right?

I think if more people understood your article that it is actually true. Maybe we could find opensource funding. Or maybe we could move on to where researchers like us whom maxed out deep learning and started to create the next great thing can continue to develop!

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Where's Kevin?

Surely no article like this is replete without a quote from AI's black sheep Keven Warwick!

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Personal Assistant

For decades products have been marketed as intelligent.

Usually uses an example of booking a flight automatically based on a diary entry.

When Serge Brin sacks his human Personal assistants I will start to take this seriously.

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