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IBM is not doing "cognitive computing" with Watson

481 points by Jerry2 10y ago

greenyoda 10y ago
For those who are unfamiliar with the author of this article: Roger Schank is one of the early pioneers of AI research: https://en.wikipedia.org/wiki/Roger_Schank https://en.wikipedia.org/wiki/Roger_Schank
- lingben 10y ago
  don't mean for this to come across as snarky but what has he done lately? is his best work from the 1980's?
  - Animats 10y ago
    That may be the problem. He sounds bitter.
    - fixermark 10y ago
      It does, unfortunately, have a bit of an "Old man yells at cloud" tone to it. And I don't see any solid evidence for his arguments beyond appeal-to-authority in that essay.
      - edtechdev 10y ago
        He may be a bit of a curmudgeon - his blog is called Education Outrage, after all: http://educationoutrage.blogspot.com/ http://educationoutrage.blogspot.com/ But he's done and continues to do a lot of good work. He helped found the Learning Sciences (an offshoot of cognitive science, AI, psychology, etc.) in the late 80s and early 90s. He continued and continues to do work in education, including founding experiential schools and writing books on education: http://www.amazon.com/s/?url=search-alias%3Daps&field-keywords=roger+schank http://www.amazon.com/s/?url=search-alias%3Daps&field-keywor...
xrd 10y ago
Funny that he was Chief Learning Officer at Trump University. Doesn't diminish my feelings for him, but interesting.
- c3534l 10y ago
  Well, I suppose if anyone can recognize a fraud when he sees one, it's a former executive officer and Trump "University."
ramanan 10y ago
Reminds me of a similar article covering the work of Douglas Hofstadter, the author of GEB : The Man Who Would Teach Machines to Think http://www.theatlantic.com/magazine/archive/2013/11/the-man-who-would-teach-machines-to-think/309529/ http://www.theatlantic.com/magazine/archive/2013/11/the-man-...
hackney 10y ago
But I saw it working in a Bruce Willis movie. I think he was a hitman-lol. Which is exactly my point. Computers will never be any smarter than the EXACT commands we as their 'creators' give them. In essence they will never be but an extension, a tool, of ourselves. But to say they can think? Not a chance in hell.
- eru 10y ago
  > Computers will never be any smarter than the EXACT commands we as their 'creators' give them. You never tried debugging, did you? (Ie computers can do surprising things, even when they do exactly as we tell them.) Also, look at AlphaGo (or any modern chess engine): these programs play better than their their programmers could.
  - hackney 10y ago
    When human beings can be defined by the rules and limitations of a chess boardgame, I will agree. That will of course never happen.
- nkozyra 10y ago
  The entire point of AI is to establish human-like intelligence via the same general mechanisms we use to learn. Our limitations are uniquely human and don't apply here. "Thinking" in the short-term means problem solving, whether through analysis and understanding. Machines are capable of that now, and do so much faster than do humans. The parameters of learning will be bound - at least for now - by human input. But not the boundaries of learning.
  - hackney 10y ago
    I agree wholeheartedly with you, except for the definition of learning. Learning implies knowledge and most of what a computer would see as knowledge is garbage to a human being. As well, what exactly a single individual would consider to be true useable knowledge would not even be teachable to a computer, as for the most part, it cannot be truly explained by said individual beyond the individuals own personal viewpoint. If we start trying to marginalize individualism I would think we lose what it means to be human, et al.
ams6110 10y ago
They are not doing "cognitive computing" no matter how many times they say they are Maybe not, but "cloud computing" is getting a little pedestrian. New meaningless names used to market things we've been doing all along are a good way to gin up some interest.
DSingularity 10y ago
Most interesting statement is the last one. Author seems to think we are about to enter into another AI winter. Seems odd given alpha go and recent success of deep learning.
- drcode 10y ago
  Yeah, it seems pretty unlikely to me that there is an AI Winter coming, given that we now have programs that look at a photograph and say "Women wearing a hat, sitting on a bar stool and drinking wine" when 5 years ago such capabilities were unfathomable- The kind of capabilities that are currently being demonstrated have wide reaching applications and will take a decade to filter into the rest of the economy, even if you pessimistically assume that all research from now on reaches a complete standstill.
  - discardorama 10y ago
    > given that we now have programs that look at a photograph and say "Women wearing a hat, sitting on a bar stool and drinking wine" That may be; but then there's also this: http://arxiv.org/abs/1412.1897 http://arxiv.org/abs/1412.1897
    - drcode 10y ago
      Well, personally I think you could perform those exact same attacks against the human brain, but in the case of NNs it's much easier to do simply because computer algos allow for exact repeatable experiments.
    - taneq 10y ago
      So? Any generalizing learning algorithm necessarily accepts a large number of inputs (including some unintended ones) for each possible output. Humans are no more robust against this kind of attack than any other system - consider stage magic, confidence scams, NLP, optical illusions, etc. If you want a truly infallible system, then no, AI will never provide that. What you want is a magic deity.
  - tpm 10y ago
drcode 10y ago
I sure wish some mainstream journalists would look into the whole "Watson" marketing campaign and apply some fact checking to it. I like AI projects as much as the next HN reader, but compared to efforts by the other players in this space (Google, Apple, Tesla, Amazon, etc) whenever I hear a new marketing push about IBM Watson project my "BS detector" goes into the red zone. (That said, it would be awesome if I'm wrong and IBM really is making some genuine advances...)
- guelo 10y ago
  Talking about over-hyped marketing, it's ridiculous to include Tesla with the other companies in your list.
  - drcode 10y ago
    Actually I'm also a bit of a Tesla skeptic, but at least they are shipping actual practical AI algos in their cars and don't walk around intimating they're going to cure cancer. http://www.cio.com/article/2397103/healthcare/can-watson--ibm-s-supercomputer--cure-cancer-.html http://www.cio.com/article/2397103/healthcare/can-watson--ib...
    - guelo 10y ago
      Tesla buys that tech from some outside vendor.
      - exhilaration 10y ago
        Mobileye: http://www.mobileye.com http://www.mobileye.com "It is used by nearly two dozen automakers, including Audi, BMW, General Motors, Ford, and Tesla Motors." -- http://fortune.com/2015/12/17/tesla-mobileye/ http://fortune.com/2015/12/17/tesla-mobileye/
rm999 10y ago
This article mirrors some huge frustrations I've had in recent years as a long-time lover and pusher of machine learning. I spoke to a Watson booth employee for a few minutes at a machine learning conference a couple years ago, and almost right away had similar feelings. I don't like the term 'fraud' here though, 'insanely oversold' seems more appropriate. I looked more into Watson, and realized it's really just a large number of traditional (and not very innovative) machine learning algorithms wrapped into a platform with a huge marketing budget. >AI winter is coming soon. Perhaps, if so Watson is certainly evidence of this. It frustrates me to no end that machine learning has so much potential but is often lost in a sea of noise and buzz words (as much as I love deep learning, I'm almost tempted to lump that in here too given its outsized media coverage). Machine learning is in its infancy of impact, but the overselling by mediocre enterprise companies and ignorant press may shoot its credibility for years to come.
- mark_l_watson 10y ago
  Machine learning is doing fine, please don't worry about that! My wife was trying to find an old photo tonight and all I had to do was suggest that she go to google photos and search based on description. Same thing with Facebook recognizing images. I am getting into using deep learning for NLP, and that looks promising. Google's parser is interesting but I want to see how quickly they can get many layer networks to do things like anaphora resolution (match up pronouns with previous noun phrases).
  - ktRolster 10y ago
    Better parsers are interesting, but I feel like the parsers we have already are 'good enough.' The biggest hole in NLP is going from a parsed sentence to 'meaning.' Once we get that right, and are able to feed meaning back into the parser, then all our parsing problems will be fixed imo.
    - graycat 10y ago
      Let me suggest that the meaning will require working effectively with concepts. That is, humans, who actually have real intelligence, can read words and identify and work with the underlying concepts, but apparently so far no one knows how to program a computer to do this.
mark_l_watson 10y ago
I spent a lot of time in the 1980s experimenting with Roger Schank's and Chris Reisbeck's Conceptual Dependency Theory, a theory that is not much thought of anymore but at the time I thought it was a good notation for encoding knowledge, like case based reasoning. Having helped a friend use Watson a year ago, I sort-of agree with Schank's opinion in this article. IBM Watson is sound technology, but I think that it is hyped in the wrong direction. And over hyped. This seems like a case of business driven rather than science driven descriptions of IBM Watson. Kudos to the development team, but perhaps not to the marketers. Really off topic, but as much as I love the advances in many layer neural networks, I am sorry to not also see tons of resources aimed at what we used to call 'symbolic AI.'
- musesum 10y ago
  Back in the 80's, there were two AI camps: Syntax and Semantics. My favorite for syntax was Terry Winograd. For semantics was Roger Schank. Back then, I was trying to map AI onto biology. Syntax was easier; you could easily map the edges to a McCullough and Pitts neural model. Semantic nets was harder; the edges were more of a way of modeling symbolic relationships. So, I couldn't wrap my head around Shank. Wish I had; it felt like I was missing the point.
- _delirium 10y ago
  There is fortunately a good amount of money being spread across different AI techniques still. Not from every funding source, but the traditional ones are still following the usual model of hedging their bets somewhat conservatively. It's mostly industry, and closely industry-aligned nonprofits like OpenAI that are going 100% all-in on nothing but deep networks. But those kinds of groups have always been a bit short-term driven and susceptible to hype; in the '80s they were putting all their money into expert systems. If you look at which AI projects the National Science Foundation is funding (or in Europe, the Horizon 2020 program), it's a lot more diverse. Even just in machine learning they're not putting all their eggs into the deep neural nets basket, with considerable funding going to the other major areas of ML (e.g. Bayesian methods). Symbolic methods have a decent amount of funding too, including some explicitly "cognitive systems" grants. Some other symbolic techniques are still funded but not as much by "AI" bodies, e.g. the logic-based branch of AI now gets a decent amount of its funding from the software engineering community, because verification is a big application of solver / theorem-prover techniques. Attending this past year's AAAI in Phoenix was kind of funny in that respect. Maybe 95% of the consultants and recruiters there were solely interested in hiring people to tweak deep networks. But the scientific side of the conference didn't look quite like that.
ACow_Adonis 10y ago
I almost want to up vote the article on principle. I try to go to various "machine learning" and "AI" meetups around my city. The most frustrating, but relevant, lesson I've learnt is to just stay away from everything IBM/Watson. I can summarise every single bloody presentation they give because it's the following: "Now, when we say cognitive computing, we don't mean any of that sci-fi and AI stuff, now here's a marketer and marketing materials that will explicitly imply that we're talking about that sci-fi and AI stuff for the next 59 minutes. There will be no technical information."
- laxatives 10y ago
  No first hand experience, but I've everything I've heard seems consistent with what you said. Several engineers I've spoken to at companies using Watson/IBM had very few positive things to say and suggested that any usage was primarily for marketing reasons.
- Spooky23 10y ago
  It's a brand, not a technology. IBM will pitch it for everything from help desks to curing cancer.
- mathattack 10y ago
  It's the latest product being pitched by a massively efficient sales force deeply ingrained in companies who are no longer purchasing big iron. Does anyone really think the next Big Idea will come from a bunch of stiff suits in Armonk, New York? They are great comercializers, consultants and support engineers. They haven't been technical innovators for many decades.
- unabst 10y ago
  > we don't mean any of that sci-fi and AI stuff No one does. Even with AlphaGo the hype was insane, but was mostly caused by people confusing weak AI with strong AI with Arnold Schwarzenegger. Any material that intentionally plays on this confusion is arguably false advertising and fraudulent. The truth is, it's still impossible for anyone to talk about strong AI, because we have hardly been able to define what it even is. We just know we have it, and it's still unlike anything anyone is working on that has made it to the public. The people who write the papers absolutely know this. It's a common goal, but we have yet to engineer anything that remotely resembles strong AI. For the most part, we're either still busy figuring out small but hard problems, or hacking resemblance and avoiding the important problems altogether.
todd8 10y ago
Patrick Winston taught my first AI course around 1974. Things have come a long way, but back then I was flabbergasted to see a program perform Calculus Integration. It seemed to be a task that took a certain amount of insight and problem solving. Professor Winston then proceeded to break down the program for us and to my surprise it easy to understand and wasn't very complex. I'll always remember his comments at that point that AI is mostly simple algorithms working against some database of knowledge. I'm not sure I would still make that claim today, kernel based support vector machines aren't all that straight forward and many of the cutting edge machine learning and AI programs are far from easy to understand. Still, there is a feeling of disappointment when the curtain is pulled aside and the great Oz is revealed to be nothing that magical.
hammock 10y ago
What if Watson analyzed 800 million pages of Dylan critiques and analysis, instead of 800 million pages of lyrics? I bet you could get to the anti-establishment theme. Maybe Watson was just given the wrong set of input data (garbage in, garbage out).
- ars 10y ago
  If you're going to go that far, why not just tell Watson what the theme is directly? Obviously the whole point is for it to figure it out for itself, not to be told.
  - mikevin 10y ago
    I don't think that's going very far. Humans who figure this out also have access to context. You wouldn't know a song is protesting against a war unless you know about the war it's protesting against. 800 million pages might seem overkill but it pales in comparison to the amount of information humans (sub)consciously use to reach these conclusions. Think about the amount of information required to adequately describe the concept of a protest-song to a machine.
- rrego 10y ago
  The themes it produced were not inaccurate when it comes to Dylan. The vast majority (and his most beloved works) are not protest songs. Pretty much everything he did after Bringing It All Back Home is not a protest song. Like A Rolling Stone is definitely not a protest song. In fact, most of his work IS about relationships in some form. I would disregard what the author has to say about Dylan even though it seems to be author's primary example. Dylan wrote a ton of songs and encompassed a couple different personas through his career. He's not one thing.
  - rvense 10y ago
    Would Watson discover this, though? Even if you marked all the lyrics with a year, would it be able to make that sort of inference? I don't think so, I doubt it is able to form anything like a concept of time, or person, or a person changing over time, especially not from an input of song lyrics.
ktRolster 10y ago
AI winter is coming soon. AI winter will come if it isn't able to latch onto strong business cases. For the past few years, we've seen a slow uptake of low-grade AI, for example, Siri. As long as those sorts of things continue, the winter won't have a chance to set in. It's true there is a lot of baseless hype around AI, but there's baseless hype around every new technology (probably around everything that catches people's attention). That said, if someone predicted that Watson is going to die, I would believe them, because they haven't seemed to get much business traction at all.
- reality_hacker 10y ago
  ML as part of AI drives major industries already. Like web search and internet ads.
  - ktRolster 10y ago
    I think it's more accurate to say linear solvers drive internet ads. Which could arguably be characterized as machine learning, I guess.
    - reality_hacker 10y ago
      Mostly logistic regression, and sometimes deep learning. Both are part of ML.
kastnerkyle 10y ago
Thinking of "Watson" more as a catchall term for machine learning research at IBM is more useful than thinking of it as a unified platform (as the marketers try to sell it). This includes research efforts in speech recognition, NLP, and reinforcement learning as well as fun stuff like the "Watson chef". The underlying technology is almost completely different, but it still falls under the Watson umbrella. In general, every company (startups and big co. alike) seems to be hyping their "AI" capabilities out the wazoo, but three years ago saying those two letters together was a death sentence. I don't know if this is a good or bad thing (hype is bad, but general interest is useful for the visibility of the field) but it is definitely a sea change compared to the last 5-10 years. I am extremely skeptical of most claims these days, and am a bit worried about AI Winter 2.0 due to hype around largely mundane technologies. There are exciting things happening in the space, but these things are rarely hyped to the extent the more mundane results with corporate backing are.
thesrcmustflow 10y ago
I was wondering how long it would take before someone actually called IBM out on this.
happycube 10y ago
The ~1990 AI Winter came about because DARPA money dried up after the (pyrric?) failure of the Japanese 5th Generation Project and the end of the Cold War. After those things not enough people could afford $xx+K LISP Machines anymore ;) As long as there's a continual source of money there won't be another one - so basically as long as companies like Google and Facebook are profitable, and preferably money to be made elsewhere, things should be good.
- Animats 10y ago
  No, the AI Winter came because expert systems did not do much. I did a Masters at Stanford CS in 1985, and met most of the big names of that era. Stanford CS was dominated by the expert systems crowd, headed by Feigenbaum, and the logicians, headed by McCarthy. AI was being taught almost as philosophy. (Exam question: "Does a rock have intention?") You could graduate without ever seeing an expert system run, let alone writing one. Very little actually worked. But the faculty was claiming Strong AI Real Soon Now. From expert systems, which are just rules you write and feed to a simple inference engine. You get out pretty much what you put in. It's just another way to program. Feigenbaum was running around, testifying before Congress that the US would become an agrarian nation unless Congress funded a big national AI lab headed by him. Really. There were a number of AI startups, all of which failed. There was a fad for buying Symbolics 3600 LISP machines, a single user refrigerator sized box with a custom CPU. None of this delivered. That's why there was an AI winter.
  - lispm 10y ago
    In 1985 much of the money going into Symbolics came from DARPA funding - direct or indirect. Strategic Defense Initiative, Strategic Computing, etc. Up to then almost all machines were sold into government projects. That was a peak year for Symbolics. In 1986 a Symbolics 3620 was about the size of a large tower PC. http://bitsavers.trailing-edge.com/pdf/symbolics/brochures/3620_1986.pdf http://bitsavers.trailing-edge.com/pdf/symbolics/brochures/3...
tacos 10y ago
Microsoft SQL Server added various machine learning primitives to their SQL dialect. So not only can you query and summarize past data; now you can select from the future as well. Bayesian, NN, clustering, the same old flower matching demo, it's all in there. If you can jam enough numbers in you can certainly handwave that you're getting insight out. https://msdn.microsoft.com/en-us/library/ms175595.aspx https://msdn.microsoft.com/en-us/library/ms175595.aspx Of course basic data mining is certainly not where the latest research is, but it covers many cases I see on HN or talked about in big data pitch decks. Regardless, it all seems a lot less fancy when you can get the job done issuing SQL commands that wouldn't confuse anyone who learned SQL in 1978. The whole thing is oversold and now largely commodified, to boot. If and when this stuff starts to show real results you'll certainly feel it. The first wave of successful connect-the-dot bots will open up so many discoveries that opportunities for human labor will swell. But it's not chess, Jeopardy and a way to mine medical records. That's all obvious corporate bullshit.
pavedwalden 10y ago
Well, this makes me feel a little better that I could never make sense of IBM's Watson advertising. Even after checking out their site, I couldn't figure out what it was for, much less what it was under the hood.
tekni5 10y ago
What is with the poor grammar and spelling errors? "Recently they ran an ad featuring Bob Dylan which made laugh, or would have, if had made not me so angry." "Ask anyone from that era about who Bob Dylan was and no one will tell you his main them was love fades." "Dog’s don’s but Watson isn't as smart as a dog either." etc
- Houshalter 10y ago
  The spelling errors confuse Watson.
- deleted 10y ago
  [deleted]
iamleppert 10y ago
I'm wondering why, as a company, IBM doesn't seem to be doing good in their core business, yet somehow they want us to believe they are at the forefront of the latest darling new technology in ML research and cognitive computing? If they are unable to attract talent and innovate in their core business, how are they supposedly pursuing sophisticated AI, and the biggest question, is why? What other products or innovations have come out of IBM Research? What is their overall reputation, and why should we believe them? Why don't they release Watson to the world, like Microsoft did with their twitter bot? If I were a recent grad or even mid level in my career and wanted to work on as interesting projects as I could, I wouldn't be going to IBM. My first priority would be access to interesting and varied datasets, such as what can be obtained at Facebook, Google, Amazon, or another such company. A close second would be any of the players in the hardware ML industry such as Nvidia. I don't understand what's so special about Watson, it all seems like marketing BS to me for a company in the death throws.
- andars 10y ago
  > What other products or innovations have come out of IBM Research? Are you asking just about recent developments in AI and ML, or in general?
- EwanToo 10y ago
  IBM spends billions of dollars in fairly fundamental technology R&D, they've built on of their strongest business models on licencing the patents they develop out to others, whether it's silicon improvements, disk density increases, or now, cognitive computing.
  - throwzout 10y ago
    What actually-useful patents are you referring to? Genuinely curious.
    - NEDM64 10y ago
      For the sake of sanity, IBM was the company with most patents awarded last year. Is it that difficult to admit that they are well enough? If it were household names like Google or Apple, would help?
pesenti 10y ago
If you want to figure out what Watson can do and bypass all the marketing hype, you can just try all the services available at http://ibm.com/watsondevelopercloud http://ibm.com/watsondevelopercloud. I won't argue that the PR goes often too far, and that's a big debate we have internally (I work for Watson). But it's a pity that most of the negative opinions expressed here come from people who haven't even bothered to try any of the services we put out there or read any of the scientific papers that have been published by our team.
- ChicagoBoy11 10y ago
  I have tried it -- but for me, at least, it reinforced the negative opinion that other have expressed here. Not because many of the services offered aren't good -- they are -- but because you can't help but note the enormous chasm between what I can actually do with Watson today to what you see on IBM ads. To me, the resentment is completely understandable. When Watson goes on Jeopardy -- an incredible technical and PR achievement -- the implication to the rest of the world is that ".... and now you can use it too!" The ads, too, convey that idea. But that isn't the case. Instead, I can access APIs for language translation, sentiment analysis, object recognition, etc... You guys are selling Watson as a new paradigm of AI never before seen by man -- that I can plug my business and my app into this and do things never-before conceived in the history of computing. The service you let me access is basically a bunch of algorithms for which there are countless alternatives -- even in places like Algorithmia. There's a huge disconnect.
  - pesenti 10y ago
    You will indeed be able to do Jeopardy too, and hopefully much more (we found that answering factoid questions isn't the most critical function so we haven't prioritized it, but it's coming). Many of the services that are on the platform can do things that were inconceivable just 5 years ago (like having a general visual classifier handle earth imagery with high enough accuracy to be useful http://www.huffingtonpost.com/entry/ibm-watson-california-water_us_573f2e9ae4b045cc9a70c0f1 http://www.huffingtonpost.com/entry/ibm-watson-california-wa...). Yes, there are alternatives - which is the sign of a healthy market - but we keep improving ours to stay state-of-the-art and to introduce higher level functions.
nl 10y ago
Meh. I'm no fan of Watson-the-marketing-term, but this sounds like the bitter remarks of a symbolic AI defender who is so sure that their way of doing AI is the only way that anything else is fraud. Watson-the-Jeopardy-winner did "cognition" (which he implies means following chains of logical reasoning) as well as any other system that has been built. See for example "Structured data and inference in DeepQA" or "Fact-based question decomposition in DeepQA[2]. It's true that the the Watson image analysis services don't use this. I'm guessing that is because they don't actually work very well in that domain. [1] http://ieeexplore.ieee.org/Xplore/defdeny.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Fstamp%2Fstamp.jsp%3Ftp%3D%26arnumber%3D6177725%26userType%3Dinst&denyReason=-133&arnumber=6177725&productsMatched=null&userType=inst http://ieeexplore.ieee.org/Xplore/defdeny.jsp?url=http%3A%2F... [2] http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6177726&abstractAccess=no&userType=inst http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6177...
- muglug 10y ago
  But he talks a lot about analysing data in context (which it seems is shorthand for "prior information that is relevant to the current input") and it's not unfair to say that we're still a long way from having machines that can make the sorts of connections between different texts that the author describes.
  - nl 10y ago
    It's true that we (as in everyone working on these problems - not just IBM) don't have this working. Two points, though: 1) This is probably the most active area of research in machine learning/AI at the moment. The same type of progress that was made in image understanding 2 years ago using deep learning techniques is now being seen in NLP. See for example[1]. 2) It isn't at all clear that "making connections" of the type he talks about is needed to generate the types on insights that he claims. For example, the work StitchFix is doing combining analogy reasoning on words along with other non-textual data[2] indicates to me that the current state-of-the-art absolutely could "understand" that Bob Dylan wrote about themes that were associated with anti-war sentiment. [1] "Teaching Machines to Read and Comprehend" http://arxiv.org/abs/1506.03340 http://arxiv.org/abs/1506.03340 [2] http://multithreaded.stitchfix.com/blog/2015/03/11/word-is-worth-a-thousand-vectors/ http://multithreaded.stitchfix.com/blog/2015/03/11/word-is-w..., https://github.com/stitchfix/context2vec https://github.com/stitchfix/context2vec,
phtevus 10y ago
I couldn't concentrate on what the article was saying because there were so many grammatical errors; I kept catching myself re-reading sentences, replacing phrasing or inserting missing words.
ACow_Adonis 10y ago
A pity? IBM is DIRECTLY responsible for me not doing so any more. I've just given up on it because you (IBM) waste my time and insult my intelligence. And i sought you guys out and your company pissed in my face! If every time you invite people to your party you serve nothing but turd sandwiches, don't bitch about how we didn't give you credit for the croquembouche you've got in the fridge out the back...
- dang 10y ago
  This comment breaks the HN guidelines. Please (re)-read them and only post comments that are civil and substantive from now on. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newswelcome.html https://news.ycombinator.com/newswelcome.html We detached this comment from https://news.ycombinator.com/item?id=11751662 https://news.ycombinator.com/item?id=11751662 and marked it off-topic.
vonsydov 10y ago
No it isn't. Maybe for IBM, but others are doing great e.g. people love amazon echo and if viv accomplishes what they're trying to do, that'll be another win for AI. Image recognition startups are doing great as well and many have been acquired. X.ai is simply amazing particularly wrt their strategy and a few other chat bot companies are doing similar work in other areas. Most companies are not building general thinking AI, they're focused on actual industries or customers and going from there. Nobody cares on AI's that can think -- if they can help you to do something, that's just fine. There are plenty of data analysis companies that are doing specific work and are revenue generating. It's really about what you're selling - if you're selling general AI and it falls short that could be a problem.
tps5 10y ago
I agree that there's a lot of AI hype and I suspect that we won't see all that much come out of it. At the same time, there's a bit of a cop-out that goes on when we privilege our own cognitive processes over those of an AI just because our own minds are, more or less, a black-box. I think he does a lot of that in this article. At the end of the day "human intuition" is just a filler until we figure out what's really going on.
dingo_bat 10y ago
>Suppose I told you that I heard a friend was buying a lot of sleeping pills and I was worried. Would Watson say I hear you are thinking about suicide? Would Watson suggest we hurry over and talk to our friend about their problems? Of course not. Although the author may be right overall, this paragraph certainly assumes a lot, and is probably wrong. Computer systems have been able to make such correlations for some time now.
matchagaucho 10y ago
AI winter is coming soon It would appear so, IBM hype aside. From chat bots to image recognition and playing Go; the media is having a field day around the AI theme. If this hype feeds Investor and Consumer expectations, the next round of AI startups are doomed to underperform.
bitmapbrother 10y ago
Usually when you call someone a liar you present plausible proof. No proof was presented. Instead all we got was an opinion of Watson's cognitive abilities from a former Trump University employee.
mathattack 10y ago
* People learn from conversation and Google can’t have one. It can pretend to have one using Siri but really those conversations tend to get tiresome when you are past asking about where to eat.* Am I the only shmuck who thought Siri came from Apple, not Google?
- rdtsc 10y ago
  Yeah to me it seems the author is angry and confused. Not sure why the article is upvoted that much. I guess people just liked the clickbaity title.
  - mathattack 10y ago
    The author used to be a big name in AI and learning but now sounds like someone complaining about going to and from school uphill both ways in the snow.
- T-A 10y ago
  I asked Google: "does siri use google". Top result: "Currently, Siri defaults to the user's preferred Safari search engine, which is set by default to Google but can be changed to Yahoo or Bing. But with the debut of iOS 7, Siri search will default to Bing instead."
leoh 10y ago
I've been impressed Watson/Bluemix and I think IBM is on an interesting track. Marketing is not always effective at conveying the particular and stunning work that engineers, such as those at IBM, accomplish.
digital_ins 10y ago
I loved this article. Not just the term "AI", I've seen startups abuse the terms "machine learning" and "big data" to such an extent that it literally makes me cringe when I hear them. How many times have you seen a TechCrunch article where the writer parrots the buzzwords the founder has thrown at them such as "x uses machine learning to sync your contacts with the cloud".
koytch 10y ago
Apparently Watson believes Mr Schank has 'mixed' feelings towards it and IBM. Go to http://www.alchemyapi.com/products/demo/alchemylanguage http://www.alchemyapi.com/products/demo/alchemylanguage, feed it the article link and see what happens :)
balx 10y ago
Business Area Limited UK is seeking to expand its investments into innovative computer software projects to turn over about 78 Million USD in medical device , computer development and biotechnologies.
balx 10y ago
Business Area Limited UK is seeking to expand its investments into innovative computer software projects to turn over about 78 Million USD in medical device , computer development and biotechnologies.
balx 10y ago
Business Area Limited UK is seeking to expand its investments into innovative computer software projects to turn over about 78 Million USD in medical device , computer development and biotechnologies. If IBM is accepting external investment portfolios.
nxzero 10y ago
Really dislike the IBM meetups, they're full of marketing speak and people they have no idea what a load of bs the "sponsor" heavy presentations are. Meetup should ban groups like this.
facepalm 10y ago
His argument is that Watson supposedly doesn't have an opinion on ISIS. While I don't know if that is even true, it seems like a very weak argument. Even if it could only "think" in a very limited domain, it could still be useful. The author mentions himself that today's 20somethings have never heard of Bob Dylan, yet uses Watson's alleged ignorance of Dylan to dismiss it. Yet 20somethings are thinking entities. Mostly it sounds like sour grapes, because his 1984 book didn't receive the recognition he thinks it deserves.
headShrinker 10y ago
I get his cynicism from an idealist engineer's prospective. It's a problem for anyone who has applicable knowledge that meets a marketing/branding agency. Watson was a new tool that could play jeopardy and IBM needed a way to sell the heck out of it. branding Watson as AI is the act of an increasingly desperate corporation. While true AI is a decade or two off, with each AI winter, an increasing number of human jobs are displaced. This next wave promises to be devastating to human productivity and a boon for machine productivity. The effects are real even if the intelligence isn't. When true AI is birthed, it won't need to be marketed. All that will be left are a few trillionaires, and food lines for the rest of us. About the future "Wealth will be based on how many robots you own and control."
sdneirf 10y ago
I have always been confused too. Their approach is old school HMM GMM and hard bulldozing. Not state of the art anymore.
ai_ja_nai 10y ago
What do you expect from somebody that manages a unit called "branded content and global creative"?
YeGoblynQueenne 10y ago
>> AI winter is coming soon. Not really. There's a lot more private funding for AI nowadays and a lot of research is happening in the industry, rather than in academia. Machine learning is not cognitive computing, like Roger Schank puts it, but it's championed by most of the large tech corps (count them: Google, Microsoft, Facebook, IBM, Baidu). Those folks have the money to keep spring going for a long, long time, much longer than last time. Just being indignant is not going to achieve anything. Roger Schank and those of us who think he's more or less right in spirit (if not in tone) have a very simple way to prove his point: make it all work. Show why Good Old-Fashioned AI is better than machine learning for achieving the goals it set itself back in the early days. But we've not been able to do that. That's the fault of the people, like Roger Schank, who started various parts of the original AI project- and failed to take it to completion. Again, and again and again. Google, IBM and the rest will do what they need to do to keep the money coming in and they'll fund a lot of research that way. The rest of us can suck it up- or come up with something that works better. Noone's stopping us.
lwall_mba 10y ago
Two points come to mind when reading the article and comments made here. One, humans have personalities based on dualistic and conflictive emotions. Only humans can love and hate at the same time at the same individual. AI is focused on mimicking some behaviors based on stimuli, but behaviors is not a personality in action. Personality is much more complex. Some Psychology 101 disperses all confusions around this. Two, the challenges around language recognition can't be programmed unless one solves meaning. Linguists have struggled to define meaning for decades; best definitions explain meaning fluctuates culturally, historically, politically, and to some extent by the individual.

481 points by Jerry2 10y ago

For those who are unfamiliar with the author of this article: Roger Schank is one of the early pioneers of AI research: https://en.wikipedia.org/wiki/Roger_Schank https://en.wikipedia.org/wiki/Roger_Schank

lingben 10y ago
don't mean for this to come across as snarky but what has he done lately? is his best work from the 1980's?
- Animats 10y ago
  That may be the problem. He sounds bitter.
  - fixermark 10y ago
    It does, unfortunately, have a bit of an "Old man yells at cloud" tone to it. And I don't see any solid evidence for his arguments beyond appeal-to-authority in that essay.
    - edtechdev 10y ago
      He may be a bit of a curmudgeon - his blog is called Education Outrage, after all: http://educationoutrage.blogspot.com/ http://educationoutrage.blogspot.com/ But he's done and continues to do a lot of good work. He helped found the Learning Sciences (an offshoot of cognitive science, AI, psychology, etc.) in the late 80s and early 90s. He continued and continues to do work in education, including founding experiential schools and writing books on education: http://www.amazon.com/s/?url=search-alias%3Daps&field-keywords=roger+schank http://www.amazon.com/s/?url=search-alias%3Daps&field-keywor...

xrd 10y ago

Funny that he was Chief Learning Officer at Trump University. Doesn't diminish my feelings for him, but interesting.

c3534l 10y ago
Well, I suppose if anyone can recognize a fraud when he sees one, it's a former executive officer and Trump "University."

ramanan 10y ago

Reminds me of a similar article covering the work of Douglas Hofstadter, the author of GEB : The Man Who Would Teach Machines to Think http://www.theatlantic.com/magazine/archive/2013/11/the-man-who-would-teach-machines-to-think/309529/ http://www.theatlantic.com/magazine/archive/2013/11/the-man-...

hackney 10y ago

But I saw it working in a Bruce Willis movie. I think he was a hitman-lol. Which is exactly my point. Computers will never be any smarter than the EXACT commands we as their 'creators' give them. In essence they will never be but an extension, a tool, of ourselves. But to say they can think? Not a chance in hell.

eru 10y ago
> Computers will never be any smarter than the EXACT commands we as their 'creators' give them. You never tried debugging, did you? (Ie computers can do surprising things, even when they do exactly as we tell them.) Also, look at AlphaGo (or any modern chess engine): these programs play better than their their programmers could.
- hackney 10y ago
  When human beings can be defined by the rules and limitations of a chess boardgame, I will agree. That will of course never happen.
nkozyra 10y ago
The entire point of AI is to establish human-like intelligence via the same general mechanisms we use to learn. Our limitations are uniquely human and don't apply here. "Thinking" in the short-term means problem solving, whether through analysis and understanding. Machines are capable of that now, and do so much faster than do humans. The parameters of learning will be bound - at least for now - by human input. But not the boundaries of learning.
- hackney 10y ago
  I agree wholeheartedly with you, except for the definition of learning. Learning implies knowledge and most of what a computer would see as knowledge is garbage to a human being. As well, what exactly a single individual would consider to be true useable knowledge would not even be teachable to a computer, as for the most part, it cannot be truly explained by said individual beyond the individuals own personal viewpoint. If we start trying to marginalize individualism I would think we lose what it means to be human, et al.

ams6110 10y ago

They are not doing "cognitive computing" no matter how many times they say they are Maybe not, but "cloud computing" is getting a little pedestrian. New meaningless names used to market things we've been doing all along are a good way to gin up some interest.

DSingularity 10y ago

Most interesting statement is the last one. Author seems to think we are about to enter into another AI winter. Seems odd given alpha go and recent success of deep learning.

drcode 10y ago
Yeah, it seems pretty unlikely to me that there is an AI Winter coming, given that we now have programs that look at a photograph and say "Women wearing a hat, sitting on a bar stool and drinking wine" when 5 years ago such capabilities were unfathomable- The kind of capabilities that are currently being demonstrated have wide reaching applications and will take a decade to filter into the rest of the economy, even if you pessimistically assume that all research from now on reaches a complete standstill.
- discardorama 10y ago
  > given that we now have programs that look at a photograph and say "Women wearing a hat, sitting on a bar stool and drinking wine" That may be; but then there's also this: http://arxiv.org/abs/1412.1897 http://arxiv.org/abs/1412.1897
  - drcode 10y ago
    Well, personally I think you could perform those exact same attacks against the human brain, but in the case of NNs it's much easier to do simply because computer algos allow for exact repeatable experiments.
  - taneq 10y ago
    So? Any generalizing learning algorithm necessarily accepts a large number of inputs (including some unintended ones) for each possible output. Humans are no more robust against this kind of attack than any other system - consider stage magic, confidence scams, NLP, optical illusions, etc. If you want a truly infallible system, then no, AI will never provide that. What you want is a magic deity.
- tpm 10y ago

drcode 10y ago

I sure wish some mainstream journalists would look into the whole "Watson" marketing campaign and apply some fact checking to it. I like AI projects as much as the next HN reader, but compared to efforts by the other players in this space (Google, Apple, Tesla, Amazon, etc) whenever I hear a new marketing push about IBM Watson project my "BS detector" goes into the red zone. (That said, it would be awesome if I'm wrong and IBM really is making some genuine advances...)

guelo 10y ago
Talking about over-hyped marketing, it's ridiculous to include Tesla with the other companies in your list.
- drcode 10y ago
  Actually I'm also a bit of a Tesla skeptic, but at least they are shipping actual practical AI algos in their cars and don't walk around intimating they're going to cure cancer. http://www.cio.com/article/2397103/healthcare/can-watson--ibm-s-supercomputer--cure-cancer-.html http://www.cio.com/article/2397103/healthcare/can-watson--ib...
  - guelo 10y ago
    Tesla buys that tech from some outside vendor.
    - exhilaration 10y ago
      Mobileye: http://www.mobileye.com http://www.mobileye.com "It is used by nearly two dozen automakers, including Audi, BMW, General Motors, Ford, and Tesla Motors." -- http://fortune.com/2015/12/17/tesla-mobileye/ http://fortune.com/2015/12/17/tesla-mobileye/

rm999 10y ago

This article mirrors some huge frustrations I've had in recent years as a long-time lover and pusher of machine learning. I spoke to a Watson booth employee for a few minutes at a machine learning conference a couple years ago, and almost right away had similar feelings. I don't like the term 'fraud' here though, 'insanely oversold' seems more appropriate. I looked more into Watson, and realized it's really just a large number of traditional (and not very innovative) machine learning algorithms wrapped into a platform with a huge marketing budget. >AI winter is coming soon. Perhaps, if so Watson is certainly evidence of this. It frustrates me to no end that machine learning has so much potential but is often lost in a sea of noise and buzz words (as much as I love deep learning, I'm almost tempted to lump that in here too given its outsized media coverage). Machine learning is in its infancy of impact, but the overselling by mediocre enterprise companies and ignorant press may shoot its credibility for years to come.

mark_l_watson 10y ago
Machine learning is doing fine, please don't worry about that! My wife was trying to find an old photo tonight and all I had to do was suggest that she go to google photos and search based on description. Same thing with Facebook recognizing images. I am getting into using deep learning for NLP, and that looks promising. Google's parser is interesting but I want to see how quickly they can get many layer networks to do things like anaphora resolution (match up pronouns with previous noun phrases).
- ktRolster 10y ago
  Better parsers are interesting, but I feel like the parsers we have already are 'good enough.' The biggest hole in NLP is going from a parsed sentence to 'meaning.' Once we get that right, and are able to feed meaning back into the parser, then all our parsing problems will be fixed imo.
  - graycat 10y ago
    Let me suggest that the meaning will require working effectively with concepts. That is, humans, who actually have real intelligence, can read words and identify and work with the underlying concepts, but apparently so far no one knows how to program a computer to do this.

mark_l_watson 10y ago

I spent a lot of time in the 1980s experimenting with Roger Schank's and Chris Reisbeck's Conceptual Dependency Theory, a theory that is not much thought of anymore but at the time I thought it was a good notation for encoding knowledge, like case based reasoning. Having helped a friend use Watson a year ago, I sort-of agree with Schank's opinion in this article. IBM Watson is sound technology, but I think that it is hyped in the wrong direction. And over hyped. This seems like a case of business driven rather than science driven descriptions of IBM Watson. Kudos to the development team, but perhaps not to the marketers. Really off topic, but as much as I love the advances in many layer neural networks, I am sorry to not also see tons of resources aimed at what we used to call 'symbolic AI.'

musesum 10y ago
Back in the 80's, there were two AI camps: Syntax and Semantics. My favorite for syntax was Terry Winograd. For semantics was Roger Schank. Back then, I was trying to map AI onto biology. Syntax was easier; you could easily map the edges to a McCullough and Pitts neural model. Semantic nets was harder; the edges were more of a way of modeling symbolic relationships. So, I couldn't wrap my head around Shank. Wish I had; it felt like I was missing the point.
_delirium 10y ago
There is fortunately a good amount of money being spread across different AI techniques still. Not from every funding source, but the traditional ones are still following the usual model of hedging their bets somewhat conservatively. It's mostly industry, and closely industry-aligned nonprofits like OpenAI that are going 100% all-in on nothing but deep networks. But those kinds of groups have always been a bit short-term driven and susceptible to hype; in the '80s they were putting all their money into expert systems. If you look at which AI projects the National Science Foundation is funding (or in Europe, the Horizon 2020 program), it's a lot more diverse. Even just in machine learning they're not putting all their eggs into the deep neural nets basket, with considerable funding going to the other major areas of ML (e.g. Bayesian methods). Symbolic methods have a decent amount of funding too, including some explicitly "cognitive systems" grants. Some other symbolic techniques are still funded but not as much by "AI" bodies, e.g. the logic-based branch of AI now gets a decent amount of its funding from the software engineering community, because verification is a big application of solver / theorem-prover techniques. Attending this past year's AAAI in Phoenix was kind of funny in that respect. Maybe 95% of the consultants and recruiters there were solely interested in hiring people to tweak deep networks. But the scientific side of the conference didn't look quite like that.

ACow_Adonis 10y ago

I almost want to up vote the article on principle. I try to go to various "machine learning" and "AI" meetups around my city. The most frustrating, but relevant, lesson I've learnt is to just stay away from everything IBM/Watson. I can summarise every single bloody presentation they give because it's the following: "Now, when we say cognitive computing, we don't mean any of that sci-fi and AI stuff, now here's a marketer and marketing materials that will explicitly imply that we're talking about that sci-fi and AI stuff for the next 59 minutes. There will be no technical information."

laxatives 10y ago
No first hand experience, but I've everything I've heard seems consistent with what you said. Several engineers I've spoken to at companies using Watson/IBM had very few positive things to say and suggested that any usage was primarily for marketing reasons.
Spooky23 10y ago
It's a brand, not a technology. IBM will pitch it for everything from help desks to curing cancer.
mathattack 10y ago
It's the latest product being pitched by a massively efficient sales force deeply ingrained in companies who are no longer purchasing big iron. Does anyone really think the next Big Idea will come from a bunch of stiff suits in Armonk, New York? They are great comercializers, consultants and support engineers. They haven't been technical innovators for many decades.
unabst 10y ago
> we don't mean any of that sci-fi and AI stuff No one does. Even with AlphaGo the hype was insane, but was mostly caused by people confusing weak AI with strong AI with Arnold Schwarzenegger. Any material that intentionally plays on this confusion is arguably false advertising and fraudulent. The truth is, it's still impossible for anyone to talk about strong AI, because we have hardly been able to define what it even is. We just know we have it, and it's still unlike anything anyone is working on that has made it to the public. The people who write the papers absolutely know this. It's a common goal, but we have yet to engineer anything that remotely resembles strong AI. For the most part, we're either still busy figuring out small but hard problems, or hacking resemblance and avoiding the important problems altogether.

todd8 10y ago

Patrick Winston taught my first AI course around 1974. Things have come a long way, but back then I was flabbergasted to see a program perform Calculus Integration. It seemed to be a task that took a certain amount of insight and problem solving. Professor Winston then proceeded to break down the program for us and to my surprise it easy to understand and wasn't very complex. I'll always remember his comments at that point that AI is mostly simple algorithms working against some database of knowledge. I'm not sure I would still make that claim today, kernel based support vector machines aren't all that straight forward and many of the cutting edge machine learning and AI programs are far from easy to understand. Still, there is a feeling of disappointment when the curtain is pulled aside and the great Oz is revealed to be nothing that magical.

hammock 10y ago

What if Watson analyzed 800 million pages of Dylan critiques and analysis, instead of 800 million pages of lyrics? I bet you could get to the anti-establishment theme. Maybe Watson was just given the wrong set of input data (garbage in, garbage out).

ars 10y ago
If you're going to go that far, why not just tell Watson what the theme is directly? Obviously the whole point is for it to figure it out for itself, not to be told.
- mikevin 10y ago
  I don't think that's going very far. Humans who figure this out also have access to context. You wouldn't know a song is protesting against a war unless you know about the war it's protesting against. 800 million pages might seem overkill but it pales in comparison to the amount of information humans (sub)consciously use to reach these conclusions. Think about the amount of information required to adequately describe the concept of a protest-song to a machine.
rrego 10y ago
The themes it produced were not inaccurate when it comes to Dylan. The vast majority (and his most beloved works) are not protest songs. Pretty much everything he did after Bringing It All Back Home is not a protest song. Like A Rolling Stone is definitely not a protest song. In fact, most of his work IS about relationships in some form. I would disregard what the author has to say about Dylan even though it seems to be author's primary example. Dylan wrote a ton of songs and encompassed a couple different personas through his career. He's not one thing.
- rvense 10y ago
  Would Watson discover this, though? Even if you marked all the lyrics with a year, would it be able to make that sort of inference? I don't think so, I doubt it is able to form anything like a concept of time, or person, or a person changing over time, especially not from an input of song lyrics.

ktRolster 10y ago

AI winter is coming soon. AI winter will come if it isn't able to latch onto strong business cases. For the past few years, we've seen a slow uptake of low-grade AI, for example, Siri. As long as those sorts of things continue, the winter won't have a chance to set in. It's true there is a lot of baseless hype around AI, but there's baseless hype around every new technology (probably around everything that catches people's attention). That said, if someone predicted that Watson is going to die, I would believe them, because they haven't seemed to get much business traction at all.

reality_hacker 10y ago
ML as part of AI drives major industries already. Like web search and internet ads.
- ktRolster 10y ago
  I think it's more accurate to say linear solvers drive internet ads. Which could arguably be characterized as machine learning, I guess.
  - reality_hacker 10y ago
    Mostly logistic regression, and sometimes deep learning. Both are part of ML.

kastnerkyle 10y ago

Thinking of "Watson" more as a catchall term for machine learning research at IBM is more useful than thinking of it as a unified platform (as the marketers try to sell it). This includes research efforts in speech recognition, NLP, and reinforcement learning as well as fun stuff like the "Watson chef". The underlying technology is almost completely different, but it still falls under the Watson umbrella. In general, every company (startups and big co. alike) seems to be hyping their "AI" capabilities out the wazoo, but three years ago saying those two letters together was a death sentence. I don't know if this is a good or bad thing (hype is bad, but general interest is useful for the visibility of the field) but it is definitely a sea change compared to the last 5-10 years. I am extremely skeptical of most claims these days, and am a bit worried about AI Winter 2.0 due to hype around largely mundane technologies. There are exciting things happening in the space, but these things are rarely hyped to the extent the more mundane results with corporate backing are.

thesrcmustflow 10y ago

I was wondering how long it would take before someone actually called IBM out on this.

happycube 10y ago

The ~1990 AI Winter came about because DARPA money dried up after the (pyrric?) failure of the Japanese 5th Generation Project and the end of the Cold War. After those things not enough people could afford $xx+K LISP Machines anymore ;) As long as there's a continual source of money there won't be another one - so basically as long as companies like Google and Facebook are profitable, and preferably money to be made elsewhere, things should be good.

Animats 10y ago
No, the AI Winter came because expert systems did not do much. I did a Masters at Stanford CS in 1985, and met most of the big names of that era. Stanford CS was dominated by the expert systems crowd, headed by Feigenbaum, and the logicians, headed by McCarthy. AI was being taught almost as philosophy. (Exam question: "Does a rock have intention?") You could graduate without ever seeing an expert system run, let alone writing one. Very little actually worked. But the faculty was claiming Strong AI Real Soon Now. From expert systems, which are just rules you write and feed to a simple inference engine. You get out pretty much what you put in. It's just another way to program. Feigenbaum was running around, testifying before Congress that the US would become an agrarian nation unless Congress funded a big national AI lab headed by him. Really. There were a number of AI startups, all of which failed. There was a fad for buying Symbolics 3600 LISP machines, a single user refrigerator sized box with a custom CPU. None of this delivered. That's why there was an AI winter.
- lispm 10y ago
  In 1985 much of the money going into Symbolics came from DARPA funding - direct or indirect. Strategic Defense Initiative, Strategic Computing, etc. Up to then almost all machines were sold into government projects. That was a peak year for Symbolics. In 1986 a Symbolics 3620 was about the size of a large tower PC. http://bitsavers.trailing-edge.com/pdf/symbolics/brochures/3620_1986.pdf http://bitsavers.trailing-edge.com/pdf/symbolics/brochures/3...

tacos 10y ago

Microsoft SQL Server added various machine learning primitives to their SQL dialect. So not only can you query and summarize past data; now you can select from the future as well. Bayesian, NN, clustering, the same old flower matching demo, it's all in there. If you can jam enough numbers in you can certainly handwave that you're getting insight out. https://msdn.microsoft.com/en-us/library/ms175595.aspx https://msdn.microsoft.com/en-us/library/ms175595.aspx Of course basic data mining is certainly not where the latest research is, but it covers many cases I see on HN or talked about in big data pitch decks. Regardless, it all seems a lot less fancy when you can get the job done issuing SQL commands that wouldn't confuse anyone who learned SQL in 1978. The whole thing is oversold and now largely commodified, to boot. If and when this stuff starts to show real results you'll certainly feel it. The first wave of successful connect-the-dot bots will open up so many discoveries that opportunities for human labor will swell. But it's not chess, Jeopardy and a way to mine medical records. That's all obvious corporate bullshit.

pavedwalden 10y ago

Well, this makes me feel a little better that I could never make sense of IBM's Watson advertising. Even after checking out their site, I couldn't figure out what it was for, much less what it was under the hood.

tekni5 10y ago

What is with the poor grammar and spelling errors? "Recently they ran an ad featuring Bob Dylan which made laugh, or would have, if had made not me so angry." "Ask anyone from that era about who Bob Dylan was and no one will tell you his main them was love fades." "Dog’s don’s but Watson isn't as smart as a dog either." etc

Houshalter 10y ago
The spelling errors confuse Watson.
deleted 10y ago
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iamleppert 10y ago

I'm wondering why, as a company, IBM doesn't seem to be doing good in their core business, yet somehow they want us to believe they are at the forefront of the latest darling new technology in ML research and cognitive computing? If they are unable to attract talent and innovate in their core business, how are they supposedly pursuing sophisticated AI, and the biggest question, is why? What other products or innovations have come out of IBM Research? What is their overall reputation, and why should we believe them? Why don't they release Watson to the world, like Microsoft did with their twitter bot? If I were a recent grad or even mid level in my career and wanted to work on as interesting projects as I could, I wouldn't be going to IBM. My first priority would be access to interesting and varied datasets, such as what can be obtained at Facebook, Google, Amazon, or another such company. A close second would be any of the players in the hardware ML industry such as Nvidia. I don't understand what's so special about Watson, it all seems like marketing BS to me for a company in the death throws.

andars 10y ago
> What other products or innovations have come out of IBM Research? Are you asking just about recent developments in AI and ML, or in general?
EwanToo 10y ago
IBM spends billions of dollars in fairly fundamental technology R&D, they've built on of their strongest business models on licencing the patents they develop out to others, whether it's silicon improvements, disk density increases, or now, cognitive computing.
- throwzout 10y ago
  What actually-useful patents are you referring to? Genuinely curious.
  - NEDM64 10y ago
    For the sake of sanity, IBM was the company with most patents awarded last year. Is it that difficult to admit that they are well enough? If it were household names like Google or Apple, would help?

pesenti 10y ago

If you want to figure out what Watson can do and bypass all the marketing hype, you can just try all the services available at http://ibm.com/watsondevelopercloud http://ibm.com/watsondevelopercloud. I won't argue that the PR goes often too far, and that's a big debate we have internally (I work for Watson). But it's a pity that most of the negative opinions expressed here come from people who haven't even bothered to try any of the services we put out there or read any of the scientific papers that have been published by our team.

ChicagoBoy11 10y ago
I have tried it -- but for me, at least, it reinforced the negative opinion that other have expressed here. Not because many of the services offered aren't good -- they are -- but because you can't help but note the enormous chasm between what I can actually do with Watson today to what you see on IBM ads. To me, the resentment is completely understandable. When Watson goes on Jeopardy -- an incredible technical and PR achievement -- the implication to the rest of the world is that ".... and now you can use it too!" The ads, too, convey that idea. But that isn't the case. Instead, I can access APIs for language translation, sentiment analysis, object recognition, etc... You guys are selling Watson as a new paradigm of AI never before seen by man -- that I can plug my business and my app into this and do things never-before conceived in the history of computing. The service you let me access is basically a bunch of algorithms for which there are countless alternatives -- even in places like Algorithmia. There's a huge disconnect.
- pesenti 10y ago
  You will indeed be able to do Jeopardy too, and hopefully much more (we found that answering factoid questions isn't the most critical function so we haven't prioritized it, but it's coming). Many of the services that are on the platform can do things that were inconceivable just 5 years ago (like having a general visual classifier handle earth imagery with high enough accuracy to be useful http://www.huffingtonpost.com/entry/ibm-watson-california-water_us_573f2e9ae4b045cc9a70c0f1 http://www.huffingtonpost.com/entry/ibm-watson-california-wa...). Yes, there are alternatives - which is the sign of a healthy market - but we keep improving ours to stay state-of-the-art and to introduce higher level functions.

nl 10y ago

Meh. I'm no fan of Watson-the-marketing-term, but this sounds like the bitter remarks of a symbolic AI defender who is so sure that their way of doing AI is the only way that anything else is fraud. Watson-the-Jeopardy-winner did "cognition" (which he implies means following chains of logical reasoning) as well as any other system that has been built. See for example "Structured data and inference in DeepQA" or "Fact-based question decomposition in DeepQA[2]. It's true that the the Watson image analysis services don't use this. I'm guessing that is because they don't actually work very well in that domain. [1] http://ieeexplore.ieee.org/Xplore/defdeny.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Fstamp%2Fstamp.jsp%3Ftp%3D%26arnumber%3D6177725%26userType%3Dinst&denyReason=-133&arnumber=6177725&productsMatched=null&userType=inst http://ieeexplore.ieee.org/Xplore/defdeny.jsp?url=http%3A%2F... [2] http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6177726&abstractAccess=no&userType=inst http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6177...

muglug 10y ago
But he talks a lot about analysing data in context (which it seems is shorthand for "prior information that is relevant to the current input") and it's not unfair to say that we're still a long way from having machines that can make the sorts of connections between different texts that the author describes.
- nl 10y ago
  It's true that we (as in everyone working on these problems - not just IBM) don't have this working. Two points, though: 1) This is probably the most active area of research in machine learning/AI at the moment. The same type of progress that was made in image understanding 2 years ago using deep learning techniques is now being seen in NLP. See for example[1]. 2) It isn't at all clear that "making connections" of the type he talks about is needed to generate the types on insights that he claims. For example, the work StitchFix is doing combining analogy reasoning on words along with other non-textual data[2] indicates to me that the current state-of-the-art absolutely could "understand" that Bob Dylan wrote about themes that were associated with anti-war sentiment. [1] "Teaching Machines to Read and Comprehend" http://arxiv.org/abs/1506.03340 http://arxiv.org/abs/1506.03340 [2] http://multithreaded.stitchfix.com/blog/2015/03/11/word-is-worth-a-thousand-vectors/ http://multithreaded.stitchfix.com/blog/2015/03/11/word-is-w..., https://github.com/stitchfix/context2vec https://github.com/stitchfix/context2vec,

phtevus 10y ago

I couldn't concentrate on what the article was saying because there were so many grammatical errors; I kept catching myself re-reading sentences, replacing phrasing or inserting missing words.

ACow_Adonis 10y ago

A pity? IBM is DIRECTLY responsible for me not doing so any more. I've just given up on it because you (IBM) waste my time and insult my intelligence. And i sought you guys out and your company pissed in my face! If every time you invite people to your party you serve nothing but turd sandwiches, don't bitch about how we didn't give you credit for the croquembouche you've got in the fridge out the back...

dang 10y ago
This comment breaks the HN guidelines. Please (re)-read them and only post comments that are civil and substantive from now on. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newswelcome.html https://news.ycombinator.com/newswelcome.html We detached this comment from https://news.ycombinator.com/item?id=11751662 https://news.ycombinator.com/item?id=11751662 and marked it off-topic.

vonsydov 10y ago

No it isn't. Maybe for IBM, but others are doing great e.g. people love amazon echo and if viv accomplishes what they're trying to do, that'll be another win for AI. Image recognition startups are doing great as well and many have been acquired. X.ai is simply amazing particularly wrt their strategy and a few other chat bot companies are doing similar work in other areas. Most companies are not building general thinking AI, they're focused on actual industries or customers and going from there. Nobody cares on AI's that can think -- if they can help you to do something, that's just fine. There are plenty of data analysis companies that are doing specific work and are revenue generating. It's really about what you're selling - if you're selling general AI and it falls short that could be a problem.

tps5 10y ago

I agree that there's a lot of AI hype and I suspect that we won't see all that much come out of it. At the same time, there's a bit of a cop-out that goes on when we privilege our own cognitive processes over those of an AI just because our own minds are, more or less, a black-box. I think he does a lot of that in this article. At the end of the day "human intuition" is just a filler until we figure out what's really going on.

dingo_bat 10y ago

>Suppose I told you that I heard a friend was buying a lot of sleeping pills and I was worried. Would Watson say I hear you are thinking about suicide? Would Watson suggest we hurry over and talk to our friend about their problems? Of course not. Although the author may be right overall, this paragraph certainly assumes a lot, and is probably wrong. Computer systems have been able to make such correlations for some time now.

matchagaucho 10y ago

AI winter is coming soon It would appear so, IBM hype aside. From chat bots to image recognition and playing Go; the media is having a field day around the AI theme. If this hype feeds Investor and Consumer expectations, the next round of AI startups are doomed to underperform.

bitmapbrother 10y ago

Usually when you call someone a liar you present plausible proof. No proof was presented. Instead all we got was an opinion of Watson's cognitive abilities from a former Trump University employee.

mathattack 10y ago

* People learn from conversation and Google can’t have one. It can pretend to have one using Siri but really those conversations tend to get tiresome when you are past asking about where to eat.* Am I the only shmuck who thought Siri came from Apple, not Google?

rdtsc 10y ago
Yeah to me it seems the author is angry and confused. Not sure why the article is upvoted that much. I guess people just liked the clickbaity title.
- mathattack 10y ago
  The author used to be a big name in AI and learning but now sounds like someone complaining about going to and from school uphill both ways in the snow.
T-A 10y ago
I asked Google: "does siri use google". Top result: "Currently, Siri defaults to the user's preferred Safari search engine, which is set by default to Google but can be changed to Yahoo or Bing. But with the debut of iOS 7, Siri search will default to Bing instead."

leoh 10y ago

I've been impressed Watson/Bluemix and I think IBM is on an interesting track. Marketing is not always effective at conveying the particular and stunning work that engineers, such as those at IBM, accomplish.

digital_ins 10y ago

I loved this article. Not just the term "AI", I've seen startups abuse the terms "machine learning" and "big data" to such an extent that it literally makes me cringe when I hear them. How many times have you seen a TechCrunch article where the writer parrots the buzzwords the founder has thrown at them such as "x uses machine learning to sync your contacts with the cloud".

koytch 10y ago

Apparently Watson believes Mr Schank has 'mixed' feelings towards it and IBM. Go to http://www.alchemyapi.com/products/demo/alchemylanguage http://www.alchemyapi.com/products/demo/alchemylanguage, feed it the article link and see what happens :)

balx 10y ago

Business Area Limited UK is seeking to expand its investments into innovative computer software projects to turn over about 78 Million USD in medical device , computer development and biotechnologies.

balx 10y ago

nxzero 10y ago

Really dislike the IBM meetups, they're full of marketing speak and people they have no idea what a load of bs the "sponsor" heavy presentations are. Meetup should ban groups like this.

facepalm 10y ago

His argument is that Watson supposedly doesn't have an opinion on ISIS. While I don't know if that is even true, it seems like a very weak argument. Even if it could only "think" in a very limited domain, it could still be useful. The author mentions himself that today's 20somethings have never heard of Bob Dylan, yet uses Watson's alleged ignorance of Dylan to dismiss it. Yet 20somethings are thinking entities. Mostly it sounds like sour grapes, because his 1984 book didn't receive the recognition he thinks it deserves.

headShrinker 10y ago

I get his cynicism from an idealist engineer's prospective. It's a problem for anyone who has applicable knowledge that meets a marketing/branding agency. Watson was a new tool that could play jeopardy and IBM needed a way to sell the heck out of it. branding Watson as AI is the act of an increasingly desperate corporation. While true AI is a decade or two off, with each AI winter, an increasing number of human jobs are displaced. This next wave promises to be devastating to human productivity and a boon for machine productivity. The effects are real even if the intelligence isn't. When true AI is birthed, it won't need to be marketed. All that will be left are a few trillionaires, and food lines for the rest of us. About the future "Wealth will be based on how many robots you own and control."

sdneirf 10y ago

I have always been confused too. Their approach is old school HMM GMM and hard bulldozing. Not state of the art anymore.

ai_ja_nai 10y ago

What do you expect from somebody that manages a unit called "branded content and global creative"?

YeGoblynQueenne 10y ago

>> AI winter is coming soon. Not really. There's a lot more private funding for AI nowadays and a lot of research is happening in the industry, rather than in academia. Machine learning is not cognitive computing, like Roger Schank puts it, but it's championed by most of the large tech corps (count them: Google, Microsoft, Facebook, IBM, Baidu). Those folks have the money to keep spring going for a long, long time, much longer than last time. Just being indignant is not going to achieve anything. Roger Schank and those of us who think he's more or less right in spirit (if not in tone) have a very simple way to prove his point: make it all work. Show why Good Old-Fashioned AI is better than machine learning for achieving the goals it set itself back in the early days. But we've not been able to do that. That's the fault of the people, like Roger Schank, who started various parts of the original AI project- and failed to take it to completion. Again, and again and again. Google, IBM and the rest will do what they need to do to keep the money coming in and they'll fund a lot of research that way. The rest of us can suck it up- or come up with something that works better. Noone's stopping us.

lwall_mba 10y ago

Two points come to mind when reading the article and comments made here. One, humans have personalities based on dualistic and conflictive emotions. Only humans can love and hate at the same time at the same individual. AI is focused on mimicking some behaviors based on stimuli, but behaviors is not a personality in action. Personality is much more complex. Some Psychology 101 disperses all confusions around this. Two, the challenges around language recognition can't be programmed unless one solves meaning. Linguists have struggled to define meaning for decades; best definitions explain meaning fluctuates culturally, historically, politically, and to some extent by the individual.