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‘Artificial Intelligence’ Was the Fake News of 2016

64 points by zhengiszen 10y ago

laurent123456 10y ago
> For example, how many human jobs did AI replace in 2016? If you gave professional pundits a multiple choice question listing these three answers: 3 million, 300,000 and none, I suspect very few would choose the correct answer, which is of course “none”. It's probably very hard to evaluate the impact of AI, but their answer is not any better (nor sourced) than that of the professional pundits they criticise (by the way, I can't find any article of anybody claiming that jobs have been lost due to AI). Rubbish theregister article as usual.
- ganeshkrishnan 10y ago
  It's really hard to define AI too. We are working on linear regression for predicting sales. Would that qualify of AI? To us it's just a bunch of algorithms on Apache Spark but for our end users it's magic, it's AI. I read a good explanation of different terminologies of AI here on HN not long time back.
  - freehunter 10y ago
    The problem with AI is that people are expecting the AI, and what we have is an AI. Predicting sales takes some amount of intelligence. A fish couldn't do it, for example. Nor could an untrained human. So if a computer predicts sales from data given to it, yes, it's an artificial intelligence. Now people will judge it and say that it's not AI because it can't do this or that or because it's too specific to a domain. But why would you buy an AI that's as smart as a human in every way and then use it just to predict sales? An AI replicates one part of human intelligence. The AI is a fully functional artificial human. Two completely independent ideas. We haven't had a single AI capable of fully replacing a human in every way, but is that something we really want or need? Or are domain specific AIs good enough? Anything that takes the repetitive cognitive load off a human and puts it into a specially trained computer is an AI.
    - semi-extrinsic 10y ago
      > Anything that takes the repetitive cognitive load off a human and puts it into a specially trained computer is an AI. This is just watering out the term AI to the point of uselessness and/or ridicule. I mean, by your definition, the steam-engine and punched-hole-card powered Jaquard looms of the early 17th century are an AI. Of course, those were the precursor to Babbage's general mechanical computer, so they were actually "specially trained computers". Edit: 19th century, not 17th. "There are two really hard problems in programming: cache invalidation, naming things, and off-by-one errors."
      - freehunter 10y ago
        As far as I know, the steam engine didn't replace anything that used to require human thought. A mechanical loom isn't replacing human intelligence either. Yes, it replaced a human performing an action, but humans brains weren't exactly racked with figuring out how to sew or weave. Think about the word "artificial" and the word "intelligence". If it used to take a human thinking and reasoning about something to perform a task but now a computer is doing it, that is by its very definition, "artificial intelligence". A steam engine or mechanical loom don't replace human brains, they replace human hands. Which is why I said "cognitive load".
- brudgers 10y ago
  The way in which technology replaces jobs is not usually explicit. Cell phones and email and automated voice mail systems replaced a lot of receptionists. Desktop computers replaced pretty much all the typists in the typing pool and a many secretaries. Smart phones replaced a lot of the secretaries that were left. The thing about AI is that it doesn't seem like AI in the rear view mirror. Grammar check and voice recognition don't seem like a big deal twenty years later. But it was science fiction in real life twenty years ago.
  - goatlover 10y ago
    I'm guessing that a Data or HAL would be different than examples of narrow AI.
  - yati 10y ago
    > The thing about AI is that it doesn't seem like AI in the rear view mirror. This. Related link: https://en.wikipedia.org/wiki/AI_effect https://en.wikipedia.org/wiki/AI_effect
- deleted 10y ago
  [deleted]
- sonabinu 10y ago
  There has certainly been advances. It does not happen overnight - we stand on the shoulders of giants. The advances in speech recognition is in the mainstream media today but decades of work and research have contributed to the advances. Similarly the work today will contribute to future advances and what 2016 did was give the readers of mainstream media a glimpse of what we will see in the years to come.
- alexc05 10y ago
  I think there is a problem in this article in conflating the news about the coming wave of technological unemployment with "AI only" I've had the opportunity this year to pay very close attention to the AI debate since my girlfriend is doing her masters in social policy and her focus is on technological unemployment. (and the policy implications of the same) This is an umbrella term under which AI lives under. Essentially any job which goes away to automation falls under technological unemployment. Consider the 60,000 foxconn employees http://www.bbc.com/news/technology-36376966 http://www.bbc.com/news/technology-36376966 rendered jobless because of TEU. Their further plans to neat fully-automate http://www.theverge.com/2016/12/30/14128870/foxconn-robots-automation-apple-iphone-china-manufacturing http://www.theverge.com/2016/12/30/14128870/foxconn-robots-a... their factories. Those aren't necessarily AI but they are unemployed. The distinction isn't really that important. Now if we consider the public policy estimates of the number of jobs "at risk" of TEU in the next 5 to 10 years, we are looking at as much as 50% to 60%. One particularly interesting line in one of her papers was that the estimates were as much as 40% "unless natural language processing reaches pairity with humans in the next 5 years" ... Microsoft achieved that pairity that a few months ago. http://blogs.microsoft.com/next/2016/10/18/historic-achievement-microsoft-researchers-reach-human-parity-conversational-speech-recognition/ http://blogs.microsoft.com/next/2016/10/18/historic-achievem... Kristin Lee at the white house recently published some really interesting papaer on AI, Authomation and the social impact of it https://www.whitehouse.gov/blog/2016/12/20/artificial-intelligence-automation-and-economy https://www.whitehouse.gov/blog/2016/12/20/artificial-intell... my girlfriend sent me the link with the subject "the whitehouse just stole my work!" - though it's really just parallel evolution, they're saying basically what she's coming out with too. (incidentally, if anyone reads this and has Kristin's contact info, I'd love to introduce her to my girlfriend, I think they'd be able to trade ideas) Anyways - suffice it to say - Artifical Intelligence is only "fake news" if you've got your head in the sand or you decide to creatively misinterpret the literature.
  - eva1984 10y ago
    Well said. One thing to point though, NLP leans towards the understanding of the semantic meaning of a sentence, while the article you referred here talks about speech recognition, which focuses on primarily audio to text. Comparing to speech recognition, NLP currently doesn't enjoy the same level of success by adapting DL technique, AFAIK. By success, I mean parity with human level performance. Current techniques are far from understanding reasonably complex commands/requirement expressed in everyday language and react to it correspondingly. IMHO, this is as hard as solving the AGI problem itself. Having a chatbot that people can talk to without realizing it is AI or not, is practically indistinguishable from mastering true intelligence, as is defined by Turing Test.
lngnmn 10y ago
Not AI, but so called Deep Learning meme. AI has been already well-researched in 90s. The improvements in classification algorithms and the early commercialization, such as Siri or FB face recognition are responsible for the current bubble. No major breakthrough in AI has been made so far. Better classifiers is not AI. They are mere pattern recognition.
- LoSboccacc 10y ago
  still there's good monet fooling vc around until they catch with the trick, that's why plenty startup sprinkle intelligence jargon on whatever they sell.
  - frozenport 10y ago
    Yeah. We got money to build a medical instrument but sold it as AI to investors.
- adrianN 10y ago
  In science and engineering you almost never have a "major breakthrough" where some radical change happens over night. Progress is made by slow incremental improvements. Only from a historian's bird-eye view can you make statements like "the steam engine started the industrial revolution". Steam engines existed before James Watt. He just improved them a little to make them commercially viable. AI in particular suffers from poor definitions. Nothing computers can do is "AI", only the things that are still impossible can be called "AI". Doing arithmetic was once thought to be a sign of intelligence. So was playing Chess, or Go, or recognizing faces. Now that computers can do this easily it is no longer considered difficult. So while the recent progress with neural networks is likely somewhat overhyped you shouldn't discount the importance of making things commercially viable. In the 90s we had software that could do image recognition, true, but it wasn't accurate enough, general enough, fast enough to be useful in practice. This has changed over the last ten years to the point where image recognition has tons of commercial applications.
  - marcosdumay 10y ago
mike_hearn 10y ago
I disagree. Have been reading a lot of AI papers in recent weeks. "What we have seen lately, is that while systems can learn things they are not explicitly told, this is mostly in virtue of having more data, not more subtlety about the data. So, what seems to be AI, is really vast knowledge, combined with a sophisticated UX," one veteran told me. Why be anonymous in such an article? You aren't leaking state secrets. I'd like this 'veteran' to explain to me why recent algorithmic advances like the DNC or recurrent entity networks are not "more subtlety about the data". The last few years have seen major improvements in the underlying neural network algorithms alone, like the addition of 'neural memory', big advances in training of neural networks that have loops in them and so on. The major progress in fields like question answering, story comprehension and game playing aren't simply about using old techniques with more data. They do reflect significant theoretical advances too. It's not a good article, just clickbait by Orlowski of the traditional sort. His final point about liability is so vague it could apply to industrial robots or autopilots too, somehow they manage to exist just fine.
- sweezyjeezy 10y ago
  > Why be anonymous in such an article? You aren't leaking state secrets. I'd like this 'veteran' to explain to me why recent algorithmic advances like the DNC or recurrent entity networks are not "more subtlety about the data". I think the issue is that these are small incremental improvements, whereas the current AI media discourse is making out like we are approaching the singularity at breakneck speed. The fact is that right now today there are relatively few domains where AI is really making a big impact in industry, and it just isn't clear how fast it's going to catch up in others (apart from self-driving cars which seem to be getting quite close).
- YeGoblynQueenne 10y ago
  Well, Geoff Hinton is on record saying that the reason ANNs are working now, where they didn't in the past is more to do with having more data and bigger computers and less with algorithmic advances (though these did help) [1]: AMT: Ok, so you have been working on neural networks for decades but it has only exploded in its application potential in the last few years, why is that? Geoffrey Hinton: I think it’s mainly because of the amount of computation and the amount of data now around but it’s also partly because there have been some technical improvements in the algorithms. Particularly in the algorithms for doing unsupervised learning where you’re not told what the right answer is but the main thing is the computation and the amount of data. The algorithms we had in the old days would have worked perfectly well if computers had been a million times faster and datasets had been a million times bigger but if we’d said that thirty years ago people would have just laughed. As to the papers you mention- researchers publish papers and in them, they make claims. That's their job. The job of anyone who reads a paper is to take it in good faith but retain their critical and skeptical stance throughout. If you're not directly involved with ANN research, or implementing your own ANN systems for some commercial application, it's very hard to know whether a claim in a paper is useful to anyone besides the scientist who published it. ________________ [1] http://techjaw.com/2015/06/07/geoffrey-hinton-deep-learning-in-baby-steps-and-the-future-of-google-and-ai/ http://techjaw.com/2015/06/07/geoffrey-hinton-deep-learning-...
deleted 10y ago
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baking 10y ago
>Here I’ll offer three reasons why 2016’s AI hype will begin to unravel in 2017. >3. Liability: So you're Too Smart To Fail? Seems like there is some missing text?
- ganeshkrishnan 10y ago
  1. is underwear gnomes. 2. is profit.
stephengillie 10y ago
AI isn't replacing grocery store checkers. It hasn't replaced auto mechanics or professional chefs. We barely have self-driving cars and trucks, and we don't even have robots to stock store shelves yet. Where is the brake-changing robot? Where is the robot that puts cans of beans on the Walmart shelf? Would humans even value such an automaton? There will always be some problems that are trivial to have a human solve, but very difficult for anything else. The Butlerian Jihad, and the underlying fear that robots will take every single job, is as much science fiction as hard light or teleportation.
- arcticfox 10y ago
  Well, there's some hyperbole. The examples you list can mostly be built today, just not cost efficiently. Hardly teleportation, which violates our understanding of physics.
  - stephengillie 10y ago
    Right, because the cost, a measure of human value, is too high. Humans could make them, but we don't value the automation. It's cheaper for a human to do it. We've had ATMs for how many decades? And yet we still have staffed bank windows, for the edge cases the ATM can't handle, such as rolled coins. Sure, some rolled-coin ATMs exist, but they're more expensive. It's usually cheaper for a human to handle the rolled coins and other bank edge cases. Same with self-check and alcohol age verification. Same with last-mile driving for self-driving cars and trucks.
- dominotw 10y ago
  Forget about flying cars, I would kill for a laundry folding machine.
  - Semiapies 10y ago
    To save lives: https://www.foldimate.com https://www.foldimate.com
    - 10y ago
ragebol 10y ago
I'm leaving my AI gloves and scarf in the closet for a little longer. I don't think there is a need for 'real AI' in order to replace a lot of humans. Just normal programming in the hands of non-tech office workers can already reduce a lot of human labor.
basicplus2 10y ago
Oxford dictionary Intelligence... "the ability to learn, understand and think in a logical way about things; the ability to do this well" From this it seems to me that AI is not possible without self awareness which surely must be a prerequisite for understanding.
- tempodox 10y ago
  Ferengi Rule of Acquisition #239: Never be afraid to mislabel a product.
scientist 10y ago
Ironically, on the right of this article there is a link to another article from the same source, entitled "Top of the bots: This AI isn't a cold, cruel killing machine – it's a pop music hit machine" [1]. Perhaps the link was also placed there by a machine learning / AI algorithm... [1] http://www.theregister.co.uk/2016/11/11/ai_pop_music_maker/ http://www.theregister.co.uk/2016/11/11/ai_pop_music_maker/
yalogin 10y ago
I feel like this is too cynical of the deep learning and AI phrases. I agree that so far the only thing deep learning has given us is advanced correlation of data to sell us stuff better. Google knows this and so it has not hyped up the self driving cars. Tesla on the other hand has no ads to sell us and had to sell cars for which it had to force the AI concept on us. I am cynical of self driving cars however becoming a reality in the near future. Of course there is probably a middle ground somewhere. The article seems to say the ad-people-tracking-tech and the more pure efforts like self driving cars are the same.
YeGoblynQueenne 10y ago
What a badly edited article. If this is the counterpoint to the hype there's no wonder the hype train is currently slingshotting around Neptune. Still, the points they're trying to make are fair, especially this bit: >> Out in the real world, people want better service, not worse service; more human and less robotic exchanges with services, not more robotic "post-human" exchanges. And that's the risk to AI's future in a nutshell: artificial stupidity has the potential to make our lives miserable like natural stupidity never has. And that's no mistake. The danger in AI is not that it will become smarter than ourselves and take over the world (where Pinky and the Brain failed). The risk is that it will remain dumber than cabbages and still take over the world, as we fall over ourselves to automate everything humans do, even the things that don't get better with more automation, until we're all left without a job, standing in a long line to speak to an AI assistant to get our food stamps for the AI food dispenser. Just an hour ago I was on the phone with a public service. The answering system's speech recognition worked just fine- it parsed my 11-digit Customer Reference Number despite my Greek accent. It did the job better than a human- those 11-digit numbers are not meant for humans anyway! Still, it kept asking me to press numbers to choose options- why didn't it ask me to speak those aloud? And at the end of the line, when all the options ran out, and only then, it let me know that the offices were closed for the holidays and I should call again tomorrow- Byyye! Is that natural, or artificial, stupidity? One way or another, it's a picture of the future: imagine a 1000-page form in triplicate, stamping on a human face, forever.
tim333 10y ago
Bit of an iffy article arguing "2016’s AI hype will begin to unravel in 2017" because roughly: 3) When something goes wrong, such as a car crash... who do you put in jail? 2) "The Consumer Doesn’t Want It" - eg clippy, automated call centers 1) "AI is a make believe world populated by mad people, and nobody wants to be part of it" - it's all a cult Which is all a bit silly - 3) you don't put anyone in jail, you work on the algorithms to reduce our existing 1m+ road deaths a year 2) There's some crap but people like Amazon Echo and I want my self driving car and 1) hardly dignifies a reply. Meanwhile in 2016, computers mastered Go, the tools became good enough that the likes of Zuck and GeoHot could make somewhat functional Jarvis like assistants or self driving cars in a few months hacking and IDC are predicting the "AI Market is projected to grow from $8 billion today to $47 billion by 2020."
- devoply 10y ago
  AI for business is about saving money. Can AI help business save money by reducing those pesky meat bags called employees. Yes, yes it can. And that's all that matters. And it will be doing more of that in years to come. There is nothing that can be done to stop this or slow it down. Meat bags are much more expensive than bolt bags.
  - tim333 10y ago
    A lot of business AI so far has been more about targeting content / ads for what that's worth. The meat bags may get redeployed to some extent as the buggy whip makers and peasant farmers were.
- maglavaitss 10y ago
  I wonder if you'd be this dismissive if an autonomous car kills your parents or children, and you'll still advocate "don't put anyone in jail". Just wondering.
  - tim333 10y ago
    Probably not but statistically I'm vastly more likely to be pissed off by a human driver killing them. I think in the last year the numbers killed were approx a million by humans, one or two by self driving cars. If the percentage killed by self driving cars gets over 0.1% I'll worry about it.

64 points by zhengiszen 10y ago

> For example, how many human jobs did AI replace in 2016? If you gave professional pundits a multiple choice question listing these three answers: 3 million, 300,000 and none, I suspect very few would choose the correct answer, which is of course “none”. It's probably very hard to evaluate the impact of AI, but their answer is not any better (nor sourced) than that of the professional pundits they criticise (by the way, I can't find any article of anybody claiming that jobs have been lost due to AI). Rubbish theregister article as usual.

ganeshkrishnan 10y ago
It's really hard to define AI too. We are working on linear regression for predicting sales. Would that qualify of AI? To us it's just a bunch of algorithms on Apache Spark but for our end users it's magic, it's AI. I read a good explanation of different terminologies of AI here on HN not long time back.
- freehunter 10y ago
  The problem with AI is that people are expecting the AI, and what we have is an AI. Predicting sales takes some amount of intelligence. A fish couldn't do it, for example. Nor could an untrained human. So if a computer predicts sales from data given to it, yes, it's an artificial intelligence. Now people will judge it and say that it's not AI because it can't do this or that or because it's too specific to a domain. But why would you buy an AI that's as smart as a human in every way and then use it just to predict sales? An AI replicates one part of human intelligence. The AI is a fully functional artificial human. Two completely independent ideas. We haven't had a single AI capable of fully replacing a human in every way, but is that something we really want or need? Or are domain specific AIs good enough? Anything that takes the repetitive cognitive load off a human and puts it into a specially trained computer is an AI.
  - semi-extrinsic 10y ago
    > Anything that takes the repetitive cognitive load off a human and puts it into a specially trained computer is an AI. This is just watering out the term AI to the point of uselessness and/or ridicule. I mean, by your definition, the steam-engine and punched-hole-card powered Jaquard looms of the early 17th century are an AI. Of course, those were the precursor to Babbage's general mechanical computer, so they were actually "specially trained computers". Edit: 19th century, not 17th. "There are two really hard problems in programming: cache invalidation, naming things, and off-by-one errors."
    - freehunter 10y ago
      As far as I know, the steam engine didn't replace anything that used to require human thought. A mechanical loom isn't replacing human intelligence either. Yes, it replaced a human performing an action, but humans brains weren't exactly racked with figuring out how to sew or weave. Think about the word "artificial" and the word "intelligence". If it used to take a human thinking and reasoning about something to perform a task but now a computer is doing it, that is by its very definition, "artificial intelligence". A steam engine or mechanical loom don't replace human brains, they replace human hands. Which is why I said "cognitive load".
brudgers 10y ago
The way in which technology replaces jobs is not usually explicit. Cell phones and email and automated voice mail systems replaced a lot of receptionists. Desktop computers replaced pretty much all the typists in the typing pool and a many secretaries. Smart phones replaced a lot of the secretaries that were left. The thing about AI is that it doesn't seem like AI in the rear view mirror. Grammar check and voice recognition don't seem like a big deal twenty years later. But it was science fiction in real life twenty years ago.
- goatlover 10y ago
  I'm guessing that a Data or HAL would be different than examples of narrow AI.
- yati 10y ago
  > The thing about AI is that it doesn't seem like AI in the rear view mirror. This. Related link: https://en.wikipedia.org/wiki/AI_effect https://en.wikipedia.org/wiki/AI_effect
deleted 10y ago
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sonabinu 10y ago
There has certainly been advances. It does not happen overnight - we stand on the shoulders of giants. The advances in speech recognition is in the mainstream media today but decades of work and research have contributed to the advances. Similarly the work today will contribute to future advances and what 2016 did was give the readers of mainstream media a glimpse of what we will see in the years to come.
alexc05 10y ago
I think there is a problem in this article in conflating the news about the coming wave of technological unemployment with "AI only" I've had the opportunity this year to pay very close attention to the AI debate since my girlfriend is doing her masters in social policy and her focus is on technological unemployment. (and the policy implications of the same) This is an umbrella term under which AI lives under. Essentially any job which goes away to automation falls under technological unemployment. Consider the 60,000 foxconn employees http://www.bbc.com/news/technology-36376966 http://www.bbc.com/news/technology-36376966 rendered jobless because of TEU. Their further plans to neat fully-automate http://www.theverge.com/2016/12/30/14128870/foxconn-robots-automation-apple-iphone-china-manufacturing http://www.theverge.com/2016/12/30/14128870/foxconn-robots-a... their factories. Those aren't necessarily AI but they are unemployed. The distinction isn't really that important. Now if we consider the public policy estimates of the number of jobs "at risk" of TEU in the next 5 to 10 years, we are looking at as much as 50% to 60%. One particularly interesting line in one of her papers was that the estimates were as much as 40% "unless natural language processing reaches pairity with humans in the next 5 years" ... Microsoft achieved that pairity that a few months ago. http://blogs.microsoft.com/next/2016/10/18/historic-achievement-microsoft-researchers-reach-human-parity-conversational-speech-recognition/ http://blogs.microsoft.com/next/2016/10/18/historic-achievem... Kristin Lee at the white house recently published some really interesting papaer on AI, Authomation and the social impact of it https://www.whitehouse.gov/blog/2016/12/20/artificial-intelligence-automation-and-economy https://www.whitehouse.gov/blog/2016/12/20/artificial-intell... my girlfriend sent me the link with the subject "the whitehouse just stole my work!" - though it's really just parallel evolution, they're saying basically what she's coming out with too. (incidentally, if anyone reads this and has Kristin's contact info, I'd love to introduce her to my girlfriend, I think they'd be able to trade ideas) Anyways - suffice it to say - Artifical Intelligence is only "fake news" if you've got your head in the sand or you decide to creatively misinterpret the literature.
- eva1984 10y ago
  Well said. One thing to point though, NLP leans towards the understanding of the semantic meaning of a sentence, while the article you referred here talks about speech recognition, which focuses on primarily audio to text. Comparing to speech recognition, NLP currently doesn't enjoy the same level of success by adapting DL technique, AFAIK. By success, I mean parity with human level performance. Current techniques are far from understanding reasonably complex commands/requirement expressed in everyday language and react to it correspondingly. IMHO, this is as hard as solving the AGI problem itself. Having a chatbot that people can talk to without realizing it is AI or not, is practically indistinguishable from mastering true intelligence, as is defined by Turing Test.

lngnmn 10y ago

Not AI, but so called Deep Learning meme. AI has been already well-researched in 90s. The improvements in classification algorithms and the early commercialization, such as Siri or FB face recognition are responsible for the current bubble. No major breakthrough in AI has been made so far. Better classifiers is not AI. They are mere pattern recognition.

LoSboccacc 10y ago
still there's good monet fooling vc around until they catch with the trick, that's why plenty startup sprinkle intelligence jargon on whatever they sell.
- frozenport 10y ago
  Yeah. We got money to build a medical instrument but sold it as AI to investors.
adrianN 10y ago
In science and engineering you almost never have a "major breakthrough" where some radical change happens over night. Progress is made by slow incremental improvements. Only from a historian's bird-eye view can you make statements like "the steam engine started the industrial revolution". Steam engines existed before James Watt. He just improved them a little to make them commercially viable. AI in particular suffers from poor definitions. Nothing computers can do is "AI", only the things that are still impossible can be called "AI". Doing arithmetic was once thought to be a sign of intelligence. So was playing Chess, or Go, or recognizing faces. Now that computers can do this easily it is no longer considered difficult. So while the recent progress with neural networks is likely somewhat overhyped you shouldn't discount the importance of making things commercially viable. In the 90s we had software that could do image recognition, true, but it wasn't accurate enough, general enough, fast enough to be useful in practice. This has changed over the last ten years to the point where image recognition has tons of commercial applications.
- marcosdumay 10y ago

mike_hearn 10y ago

I disagree. Have been reading a lot of AI papers in recent weeks. "What we have seen lately, is that while systems can learn things they are not explicitly told, this is mostly in virtue of having more data, not more subtlety about the data. So, what seems to be AI, is really vast knowledge, combined with a sophisticated UX," one veteran told me. Why be anonymous in such an article? You aren't leaking state secrets. I'd like this 'veteran' to explain to me why recent algorithmic advances like the DNC or recurrent entity networks are not "more subtlety about the data". The last few years have seen major improvements in the underlying neural network algorithms alone, like the addition of 'neural memory', big advances in training of neural networks that have loops in them and so on. The major progress in fields like question answering, story comprehension and game playing aren't simply about using old techniques with more data. They do reflect significant theoretical advances too. It's not a good article, just clickbait by Orlowski of the traditional sort. His final point about liability is so vague it could apply to industrial robots or autopilots too, somehow they manage to exist just fine.

sweezyjeezy 10y ago
> Why be anonymous in such an article? You aren't leaking state secrets. I'd like this 'veteran' to explain to me why recent algorithmic advances like the DNC or recurrent entity networks are not "more subtlety about the data". I think the issue is that these are small incremental improvements, whereas the current AI media discourse is making out like we are approaching the singularity at breakneck speed. The fact is that right now today there are relatively few domains where AI is really making a big impact in industry, and it just isn't clear how fast it's going to catch up in others (apart from self-driving cars which seem to be getting quite close).
YeGoblynQueenne 10y ago
Well, Geoff Hinton is on record saying that the reason ANNs are working now, where they didn't in the past is more to do with having more data and bigger computers and less with algorithmic advances (though these did help) [1]: AMT: Ok, so you have been working on neural networks for decades but it has only exploded in its application potential in the last few years, why is that? Geoffrey Hinton: I think it’s mainly because of the amount of computation and the amount of data now around but it’s also partly because there have been some technical improvements in the algorithms. Particularly in the algorithms for doing unsupervised learning where you’re not told what the right answer is but the main thing is the computation and the amount of data. The algorithms we had in the old days would have worked perfectly well if computers had been a million times faster and datasets had been a million times bigger but if we’d said that thirty years ago people would have just laughed. As to the papers you mention- researchers publish papers and in them, they make claims. That's their job. The job of anyone who reads a paper is to take it in good faith but retain their critical and skeptical stance throughout. If you're not directly involved with ANN research, or implementing your own ANN systems for some commercial application, it's very hard to know whether a claim in a paper is useful to anyone besides the scientist who published it. ________________ [1] http://techjaw.com/2015/06/07/geoffrey-hinton-deep-learning-in-baby-steps-and-the-future-of-google-and-ai/ http://techjaw.com/2015/06/07/geoffrey-hinton-deep-learning-...

deleted 10y ago

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baking 10y ago

>Here I’ll offer three reasons why 2016’s AI hype will begin to unravel in 2017. >3. Liability: So you're Too Smart To Fail? Seems like there is some missing text?

ganeshkrishnan 10y ago
1. is underwear gnomes. 2. is profit.

stephengillie 10y ago

AI isn't replacing grocery store checkers. It hasn't replaced auto mechanics or professional chefs. We barely have self-driving cars and trucks, and we don't even have robots to stock store shelves yet. Where is the brake-changing robot? Where is the robot that puts cans of beans on the Walmart shelf? Would humans even value such an automaton? There will always be some problems that are trivial to have a human solve, but very difficult for anything else. The Butlerian Jihad, and the underlying fear that robots will take every single job, is as much science fiction as hard light or teleportation.

arcticfox 10y ago
Well, there's some hyperbole. The examples you list can mostly be built today, just not cost efficiently. Hardly teleportation, which violates our understanding of physics.
- stephengillie 10y ago
  Right, because the cost, a measure of human value, is too high. Humans could make them, but we don't value the automation. It's cheaper for a human to do it. We've had ATMs for how many decades? And yet we still have staffed bank windows, for the edge cases the ATM can't handle, such as rolled coins. Sure, some rolled-coin ATMs exist, but they're more expensive. It's usually cheaper for a human to handle the rolled coins and other bank edge cases. Same with self-check and alcohol age verification. Same with last-mile driving for self-driving cars and trucks.
dominotw 10y ago
Forget about flying cars, I would kill for a laundry folding machine.
- Semiapies 10y ago
  To save lives: https://www.foldimate.com https://www.foldimate.com
  - 10y ago

ragebol 10y ago

I'm leaving my AI gloves and scarf in the closet for a little longer. I don't think there is a need for 'real AI' in order to replace a lot of humans. Just normal programming in the hands of non-tech office workers can already reduce a lot of human labor.

basicplus2 10y ago

Oxford dictionary Intelligence... "the ability to learn, understand and think in a logical way about things; the ability to do this well" From this it seems to me that AI is not possible without self awareness which surely must be a prerequisite for understanding.

tempodox 10y ago
Ferengi Rule of Acquisition #239: Never be afraid to mislabel a product.

scientist 10y ago

Ironically, on the right of this article there is a link to another article from the same source, entitled "Top of the bots: This AI isn't a cold, cruel killing machine – it's a pop music hit machine" [1]. Perhaps the link was also placed there by a machine learning / AI algorithm... [1] http://www.theregister.co.uk/2016/11/11/ai_pop_music_maker/ http://www.theregister.co.uk/2016/11/11/ai_pop_music_maker/

yalogin 10y ago

I feel like this is too cynical of the deep learning and AI phrases. I agree that so far the only thing deep learning has given us is advanced correlation of data to sell us stuff better. Google knows this and so it has not hyped up the self driving cars. Tesla on the other hand has no ads to sell us and had to sell cars for which it had to force the AI concept on us. I am cynical of self driving cars however becoming a reality in the near future. Of course there is probably a middle ground somewhere. The article seems to say the ad-people-tracking-tech and the more pure efforts like self driving cars are the same.

YeGoblynQueenne 10y ago

What a badly edited article. If this is the counterpoint to the hype there's no wonder the hype train is currently slingshotting around Neptune. Still, the points they're trying to make are fair, especially this bit: >> Out in the real world, people want better service, not worse service; more human and less robotic exchanges with services, not more robotic "post-human" exchanges. And that's the risk to AI's future in a nutshell: artificial stupidity has the potential to make our lives miserable like natural stupidity never has. And that's no mistake. The danger in AI is not that it will become smarter than ourselves and take over the world (where Pinky and the Brain failed). The risk is that it will remain dumber than cabbages and still take over the world, as we fall over ourselves to automate everything humans do, even the things that don't get better with more automation, until we're all left without a job, standing in a long line to speak to an AI assistant to get our food stamps for the AI food dispenser. Just an hour ago I was on the phone with a public service. The answering system's speech recognition worked just fine- it parsed my 11-digit Customer Reference Number despite my Greek accent. It did the job better than a human- those 11-digit numbers are not meant for humans anyway! Still, it kept asking me to press numbers to choose options- why didn't it ask me to speak those aloud? And at the end of the line, when all the options ran out, and only then, it let me know that the offices were closed for the holidays and I should call again tomorrow- Byyye! Is that natural, or artificial, stupidity? One way or another, it's a picture of the future: imagine a 1000-page form in triplicate, stamping on a human face, forever.

tim333 10y ago

Bit of an iffy article arguing "2016’s AI hype will begin to unravel in 2017" because roughly: 3) When something goes wrong, such as a car crash... who do you put in jail? 2) "The Consumer Doesn’t Want It" - eg clippy, automated call centers 1) "AI is a make believe world populated by mad people, and nobody wants to be part of it" - it's all a cult Which is all a bit silly - 3) you don't put anyone in jail, you work on the algorithms to reduce our existing 1m+ road deaths a year 2) There's some crap but people like Amazon Echo and I want my self driving car and 1) hardly dignifies a reply. Meanwhile in 2016, computers mastered Go, the tools became good enough that the likes of Zuck and GeoHot could make somewhat functional Jarvis like assistants or self driving cars in a few months hacking and IDC are predicting the "AI Market is projected to grow from $8 billion today to $47 billion by 2020."

devoply 10y ago
AI for business is about saving money. Can AI help business save money by reducing those pesky meat bags called employees. Yes, yes it can. And that's all that matters. And it will be doing more of that in years to come. There is nothing that can be done to stop this or slow it down. Meat bags are much more expensive than bolt bags.
- tim333 10y ago
  A lot of business AI so far has been more about targeting content / ads for what that's worth. The meat bags may get redeployed to some extent as the buggy whip makers and peasant farmers were.
maglavaitss 10y ago
I wonder if you'd be this dismissive if an autonomous car kills your parents or children, and you'll still advocate "don't put anyone in jail". Just wondering.
- tim333 10y ago
  Probably not but statistically I'm vastly more likely to be pissed off by a human driver killing them. I think in the last year the numbers killed were approx a million by humans, one or two by self driving cars. If the percentage killed by self driving cars gets over 0.1% I'll worry about it.