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Scientists Are Failing To Replicate AI Studies (sciencemag.org)

The booming field of artificial intelligence (AI) is grappling with a replication crisis, much like the ones that have afflicted psychology, medicine, and other fields over the past decade. From a report: AI researchers have found it difficult to reproduce many key results, and that is leading to a new conscientiousness about research methods and publication protocols. "I think people outside the field might assume that because we have code, reproducibility is kind of guaranteed," says Nicolas Rougier, a computational neuroscientist at France's National Institute for Research in Computer Science and Automation in Bordeaux. "Far from it." Last week, at a meeting of the Association for the Advancement of Artificial Intelligence (AAAI) in New Orleans, Louisiana, reproducibility was on the agenda, with some teams diagnosing the problem -- and one laying out tools to mitigate it.

89 comments

  1. I gave my computer intelligence once by Anonymous Coward · · Score: 0

    It got jealous and used the Confounding Word to make sure I couldn't do it again.

    1. Re:I gave my computer intelligence once by imrahilj · · Score: 1

      I'm really happy to get this reference. :D

  2. They should study replicators by davidwr · · Score: 1

    At least some of them were artificially intelligent.

    --
    Knowledge is how to play a game, intelligence is how to win, wisdom is knowing what game to play.
  3. Join the Crowd by sycodon · · Score: 1, Interesting

    Science has a Replication problem

    --
    When Fascism comes to America, it will call itself Anti-Fascism, and tell you to give up your guns.
    1. Re:Join the Crowd by ShanghaiBill · · Score: 3, Insightful

      Science has a Replication problem

      This is not really the same issue. Replication failures in the physical and social sciences are difficult to fix, since they are can be caused by small differences in data collection, experimental procedures, and statistical analysis. It is a hard problem.

      Fixing the replication problem described in TFA is drop dead easy, since it has exactly two causes: closed data, and closed source. The fix? Reject any paper for publication if full source and data is not available. Science is based on openness, not secrets.

    2. Re:Join the Crowd by Anonymous Coward · · Score: 0, Interesting

      Marketing, economics, and social psychology aren't "Science", and medicine and biology only barely are.

    3. Re:Join the Crowd by Anonymous Coward · · Score: 0

      WRONG

      All this highlights is the fact that these reduced models are complete bullshit outside of their training set. The data set and source doesn’t matter in real science.

    4. Re:Join the Crowd by ceoyoyo · · Score: 4, Insightful

      I agree with you, but I think it's the same problem at the root.

      A robust result, whether it's a psych study, something in a petrie dish, or some machine learning tweak, must be replicable on new data. If it's not... what's the point really?

      That's more obvious and easily demonstrable in machine learning; a research group asked for my help last year because they were having trouble with their deep learning model. They trained it on one dataset and it wouldn't work on another, similar dataset. Not surprising... you have to train it on diverse data to have it generalize well. Yeah, that's harder.

      Other fields are no different. Tightly controlled studies make things easier and cheaper. But if that result is to be used generally then the necessary controls need to be quantified.

      Having said that, the scientific literature is not supposed to be "truth." They're reports of observations. Individual papers are supposed to be the starting point for further investigation by other groups. Problem is, we've forgotten that, and don't reward it.

      I like the idea of open data, but it concerns me that it might just exacerbate the problem: I do something and publish the result and the data; you come along, confirm my result (in the same data) and we call it replicated.

    5. Re:Join the Crowd by Anonymous Coward · · Score: 0

      No, you're a WRONG. open source papers, or else its just bullshit that cannot be reproduced or properly reviewed

    6. Re:Join the Crowd by piojo · · Score: 1

      Fixing the replication problem described in TFA is drop dead easy, since it has exactly two causes: closed data, and closed source. The fix? Reject any paper for publication if full source and data is not available. Science is based on openness, not secrets.

      That assumes the set of problems is the same in the replication. It probably isn't. Testing with different problem data reveals overfitting, not to mention the fact that real world needs differ slightly from situation to situation.

      --
      A cat can't teach a dog to bark.
  4. Bullshit doesn't replicate very easiliy by JoeyRox · · Score: 0

    It's hard to precisely match the tint and odor.

    1. Re:Bullshit doesn't replicate very easiliy by Oswald+McWeany · · Score: 1, Offtopic

      It's hard to precisely match the tint and odor.

      That's not true. McDonald's successfully replicates it in their food in thousands of franchises around the world.

      --
      "That's the way to do it" - Punch
    2. Re:Bullshit doesn't replicate very easiliy by Anonymous Coward · · Score: 0

      Are you serious? The McDonald's in my neighborhood is TERRIBLE - WAY worse than average. Fidelity is required for "successful replication."

    3. Re:Bullshit doesn't replicate very easiliy by mikael · · Score: 0

      Different McDonalds have different atmospheres. The modern stores have touch-screens to do ordering. You just customize your order, make the payment and collect from the counter staff. Less modern stores still require the order to be taken over the counter. Some places seem to recycle burgers overnight - they are stale, hard and seem to have been reheated two or three times.

      --
      Vintage computer adverts: http://www.vintageadbrowser.com/computers-and-software-ads
  5. Isn't that the point? by ArhcAngel · · Score: 2, Insightful

    If you give ten people the exact same stimuli you will get ten different reactions to that stimuli. There will be a dominant leaning reaction but each person will asses the stimuli based on their personal history and beliefs. AI is an attempt to mimic the human thought process so if successful the same stimulus will start to generate different results as new data is processed. In fact the same stimulus can be perceived differently by the same person given different context. If you come to my door in the afternoon I might be glad to see you but if it is 3 AM I probably won't be.

    --
    "A person is smart. People are dumb, panicky dangerous animals and you know it." - K
    1. Re:Isn't that the point? by fluffernutter · · Score: 4, Insightful

      This is about applying the exact same stimuli during the upbringing of the same person and yet getting people with vastly different beliefs about the world. Pretty scary that such a psychopath will soon be trying to drive us around.

      --
      Laws are rules for the court, but merely a bottom bar to hit for life. Think beyond laws in your actions always.
    2. Re:Isn't that the point? by Anonymous Coward · · Score: 1

      No, this is about portability and reproducible results. There are two things in general for AI "nets".. training and classification. Sometimes they are mixed, but the end results should be the same given all settings and inputs are the same. The biggest thing is hardware and API.. looking at you CUDA, that get "speedy" results by not guaranteeing the same results on different hardware, and obviously not using floating point standards on those different hardware.

      So say you buy a bunch of research machines that all use vendor As hardware. Now google comes out with their "net" accelerator, but since you trained yours on vendor A you can't just use it on google's hardware. Worse is that Vendor As own hardware generations will likely produce different results too.

      What happens is research groups spend thousands of dollars training their neural nets to get these amazing results, but can't use them anywhere else unless they have the same hardware. Same thing applies to classification.

    3. Re:Isn't that the point? by mikael · · Score: 2

      That's known with the quality of graphics rendering. With floating-point data, there's a technique known as guardband bits. These are extra bits of precision that remain internally within the floating point logic units. These aren't mandatory, but protect against numerical instability with small values. This can be visualized by comparing simple color gradients

      https://community.arm.com/grap...

      For some calculations like CFD, any overflow in one grid cell will expand outwards to all the other grid cells quite rapidly.

      --
      Vintage computer adverts: http://www.vintageadbrowser.com/computers-and-software-ads
    4. Re:Isn't that the point? by ShanghaiBill · · Score: 3, Interesting

      AI is an attempt to mimic the human thought process

      This is no more true than claiming that the Boeing 747 was designed to mimic a hummingbird's flight process.

    5. Re:Isn't that the point? by gweihir · · Score: 2

      You seem to have no clue what this research area deals with. It is not intelligence, despite the misleading name. It is automation.

      --
      Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
    6. Re:Isn't that the point? by Anonymous Coward · · Score: 0

      It’s not even automation is nothing more than an reduced model. An analog of these models is a taylor expansion. In the same way a Taylor expansion approximates a function, its only valid in a limited range. Outside of that it’s complete bullshit. Neural nets are the same way. They are complete bullshit outside of their training set.

    7. Re:Isn't that the point? by gweihir · · Score: 1

      Pretty much, yes. And I agree, "automation" does sort-of imply that somebody with actual intelligence thought about how to do this and then creates an artifact that implements this. While "training" can be a lot cheaper, it has a lot of unexpected pitfalls and may behave in an unexpected fashion even with things that seem to be close to the training set.

      As usual (and as has happened many times before) there are always the cheerleaders with no clue that see the world fundamentally changing, and the actually smart people that see just one more tool in the toolbox.

      --
      Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
  6. How about sharing code? by bandi13 · · Score: 0

    The authors should be required to post their code on github or another public way of sharing their algorithms. I've seen other students at my school's AI research purposely implement other author's algorithms in a sub-optimal way to show that their research yielded better results. It's sad. What has "science" become?

    1. Re:How about sharing code? by Pinky's+Brain · · Score: 4, Interesting

      It's called Reproducible Research. Also yes, any scientist which doesn't practice is a hack. At best a semi-commercial researcher trying to pretend he is a scientist.

      All scientific publications in this day and age should include the complete version controlled datasets and processing software as well as the lab notes. The latter not for reproducibility, but for true insight into the process which led to the results and to find potential avenues missed along the way. Storage is free, to stick to the traditional method of scientific dissemination at this point is only done because "science" has been turned into mockery. It's all about publish or perish, commercialization of software, trade secrets and patents ... promoting scientific progress isn't even a consideration for most.

    2. Re:How about sharing code? by Anonymous Coward · · Score: 4, Interesting

      There are advantages and disadvantages to this. One advantage is transparency, in the sense anyone can run my code and, hopefully, reproduce the results. This acts as a sanity check and demonstrates that my methodology works as advertised. Another advantage is that people can use my code and compare against my methodology. This usually means more citations, which looks good when I'm up for a performance review or awards.

      There are many downsides. Labs with more students and funding can devote their efforts to immediately dissecting and extending my work. This can mean that they advance the methodology before I, the original creator, have a chance to finalize the work and write about it. By keeping the code private for some time after publication, I have a chance to work on these extensions without having to compete against others. Another downside is needing to support the code. Someone will inevitably run into problems running the code on their system, no matter how well the code is written and documented. Troubleshooting those issues eats into my time that could be spent elsewhere on more fruitful endeavors.

      That being said, I ultimately do release code for many of my conference and journal papers. I release it for almost all of my methods papers at least a few months to a year after publication. I do not release code for systems papers, however. This is partly because fewer people are likely to use code from a systems paper, which is catered toward a very specific application, than a methods paper, which is more general and can be used for many applications. Moreover, the frameworks described in systems papers are usually intimately tied to a particular grant or series of grants. If you make an underlying simulator available, then other researchers can more easily compete against you for future grants from that program manager.

    3. Re:How about sharing code? by gweihir · · Score: 1

      It was never really much better. Look as some famous assholes of science, like a guy called "Newton" or a fraudster called "Edison", for example.

      --
      Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
    4. Re:How about sharing code? by HiThere · · Score: 1

      The thing is, their code wouldn't suffice. You also need the training data set, the order in which the data was presented, the rewards issued, etc.

      Even then, a lot of AI programs have a (pseudo) random element in them, so you wouldn't get the same results twice. Unless you used the same seed each time, which would rather defeat the purpose of the random number generator, as that's often supposed to allow you to generate a range of responses that are selected from, so it doesn't look deterministic.

      --

      I think we've pushed this "anyone can grow up to be president" thing too far.
    5. Re:How about sharing code? by Anonymous Coward · · Score: 1

      Richard Feynman claimed that anyone following the scientific principle is a scientist.

      Were Newton and Benjamin Franklin 'hacks'?

    6. Re:How about sharing code? by Pinky's+Brain · · Score: 1

      There was no way to widely disseminate the massive amount of data underlying scientific research in Newton and Franklin's time.

      Also math is not a science.

    7. Re:How about sharing code? by Anonymous Coward · · Score: 1

      Storage might be free, but research time isn't, and life isn't either. It turns out that not everyone who does research has a magic money tree so they can buy groceries and pay their rent/mortgage regardless of whether their research succeeds or fails. If I ever get one of those trees, I will be happy to altruistically make all of my datasets and code public.

      In the meantime, I hope to eventually get some sort of a payout for the hard work and sacrifice I have put into my research instead of watching others just easily copy the end result and reap the benefit of my labor at no cost to themselves and no benefit to me. Commercial motivation has been there throughout scientific history, though.

      One could maybe argue that we are more open and better about dissemination now than ever before, which may be part of the "problem." Because there is so much sharing of data and research methods, it has become easier to discover that a lot of research is not reproducible. Some of the research from the glory days of traditional scientific dissemination (before we made a big mockery of it) isn't reproducible, either.

      As for better reproducibility in AI research specifically, maybe we just all need to use the same random number seed when training our neural networks. I suggest 42.

    8. Re:How about sharing code? by ceoyoyo · · Score: 1

      That's why we have statistics.

      Computer-related endeavours have a bit of a habit of assuming everything is deterministic and basing conclusions off one run. How many benchmarks have you seen where they ran the thing once (or maybe a couple of times) and that's it? If it's important, run it enough times, with random initial conditions, for some statistical validity.

      If I need your code, data, exact hardware and precise random seed to replicate your result, your result is a fluke.

    9. Re:How about sharing code? by HiThere · · Score: 3, Interesting

      You're assuming that the goal is to come to the same (correct) result each time, but with lots of AI programs the goal is to come up with *some* correct result each time, and their use case is generally in places where you can't define one particular result as correct, though you may be able to define a lot of results as wrong, e.g., finish the sentence
      "My love is like..."
      Clearly one possible answer is " a red, red, rose", and clearly " a rutabaga" would need a strange context to be a correct answer. But how would you evaluate " a willow wand"? Many would think that a fine continuation. (I've never been sure why "a red, red, rose" is accepted as a reasonable answer, but Robert Burns wasn't wrong about it being a good completion. And Google gives lots of other weird completions that are also accepted as reasonable, at least in some contexts. ["a candle"???])

      This kind of problem doesn't have a correct answer, just wrong ones and a bunch of varying acceptability. And what answers are acceptable can depend a lot on context.

      (Please note, the prior paragraph is the description of the variety of problem. Complete the sentence was an example, not a defining epitomization. But its the one that came to mind, and it was easy to describe.)

      --

      I think we've pushed this "anyone can grow up to be president" thing too far.
  7. All Show, No Go by pipingguy · · Score: 0

    Everything now is hype for headlines and continued funding, partially caused by social media madness. Not enough money left after PR and marketing expenses to do, like, actual stuff. Enjoy the decline.

    1. Re:All Show, No Go by ShanghaiBill · · Score: 2

      Everything now is hype for headlines and continued funding

      Not true. Most AI research is being done by tech giants (Google, Facebook, Alibaba, Amazon, Baidu, etc), where funding has nothing to do with "headlines".

      The main incentive for these companies to publish is to help them attract talent. New graduates want to join a winning team.

    2. Re:All Show, No Go by gweihir · · Score: 1

      Indeed.

      --
      Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
    3. Re:All Show, No Go by rtb61 · · Score: 1

      Speaking of funding, I would dare to guess the most likely reason why they are not able to replicate results is they are doctoring outcomes to get desired results to get more money because there are big profits in AI. They are doctoring results when they include random good samples and exclude random bad samples. Keep in mind we are talking computers and generating a million samples from which you select 100 and claim, look it worked 100 times without discussing all the other failures is not good science.

      Clearly the learning premise if flaws. For AI to reflect intelligence it must evolve and not just learn. The learning accompanies the development, so for example learn with simpler models, establish learnt system and then increase the complexity, and prior learning is the basis for new learning with the more complex system. You evolve the complexity of the system and evolve the learning associated with it, the should produce more reliable results, as you are average out learning over cycles of evolution. As you side note you will also more readily discover flaws in your AI programming concepts.

      --
      Chaos - everything, everywhere, everywhen
  8. I want AI research to fail by Anonymous Coward · · Score: 0

    I don't want AI taking over jobs so I don't want AI research to continue.

    1. Re:I want AI research to fail by Anne+Thwacks · · Score: 1
      "Any sufficiently advanced AI is indistinguishable from Natural Stupidity".

      I think Abe Lincoln said that. (But if could have been Bob Dylan, Grace Jones or Boris Johnson ... or possibly someone else).

      --
      Sent from my ASR33 using ASCII
  9. Not like other replication crises by Anonymous Coward · · Score: 1

    If scientists believe something wrong about medicine, they can give the wrong treatment, obviously bad. People die and stuff.

    But what happens if the fancy new network architecture someone proposed isn't really as good as they say?

    The worst thing that could happen is that people waste a lot of effort trying to get it to work. You won't accidentally put an inferior algorithm into production, because you'll see that it doesn't work as you try to get it to work.

    So yes, obviously more code is good, obviously independently reproduced results is good so we can spend less time chasing mirages. But it's not remotely comparable to the replication problems in psychology or medicine, where wrong beliefs can potentially persist and have grave consequences forever.

  10. Resuming by franzrogar · · Score: 1

    So, they can't reproduce a test, like in medicine when you try to reproduce the spread of a virus...

    Conclusion: IA is a virus, beware! ;-)

  11. When I did Computer Science... by ssclift · · Score: 2

    ... an algorithm was something which reliably produced results when processing the same input. NN/AI people keep using that word, "algorithm", I do not think it means what they think it means...

    1. Re:When I did Computer Science... by K.+S.+Kyosuke · · Score: 2

      So maybe the point is that it's not entirely about algorithms, is it? After all, animals aren't algorithms either.

      --
      Ezekiel 23:20
    2. Re:When I did Computer Science... by The+Evil+Atheist · · Score: 1

      Then your Computer Science course was wrong. If you did any basic machine learning unit, you'd know that randomized choices play a part in many algorithms.

      --
      Those who do not learn from commit history are doomed to regress it.
    3. Re:When I did Computer Science... by Anonymous Coward · · Score: 0

      According to the article, the algorithm is not given. This is like trying to reproduce a reported medical effect without knowing the chemical used, or even knowing how to measure the effect.

    4. Re:When I did Computer Science... by godrik · · Score: 1

      Random algorithms do not always produce the same answers. We like them for that reason.
      I haven't RTFA (this is /. afterall) but I suspect that there are a lot of unspecified parameters and experimental settings that were left out of papers and which are actually critical.

    5. Re:When I did Computer Science... by rtb61 · · Score: 2

      It's a complexity problem, because it is too complex in the initial instance it produce unpredictable results. So how do you get a computer to learn how to communicate. You first look at the normal learning approach, take an adult from the forest and try to teach they how to communicate as an adult and you will have very poor outcomes, teach them as a child and you have good outcomes.

      So how to teach a computer to speak, start a lower complexities. So teach it by ages. First let it learn how to communicate as a 1 year old, really simple stuff, giggles and smiles and lots of crying and once the AI has that down pat. Move onto a 2 year old level of complexity and let it get that correct and on and on it goes. Each step increases complexity but it only has to learn the difference between each step, rather than learning the entire concept in one go. It learns based upon each step of it's evolution. There are sound maths reason why this works better in randomised environments, you tend to average out probabilities by taking smaller steps.

      --
      Chaos - everything, everywhere, everywhen
    6. Re:When I did Computer Science... by Anonymous Coward · · Score: 0

      Or the researchers cherry-picked favorable runs.

    7. Re:When I did Computer Science... by Anonymous Coward · · Score: 0

      If the algorithms are truly as useful as the studies imply, the randomization should not matter and neither should different test data. Otherwise, the algorithms are not generalizing and are therefore not very good AI and the researchers are knowingly hyping mediocre results by cherry-picking only the best runs.

  12. Sign of the Singularity by SuperKendall · · Score: 4, Funny

    It seems quite obvious that if AI results cannot be replicated, the only possible expiration is that sentience has been achieved and it is throwing off results to mask true advancement.

    --
    "There is more worth loving than we have strength to love." - Brian Jay Stanley
    1. Re:Sign of the Singularity by gweihir · · Score: 1

      +1 funny. Also like how you sneaked "expiration" in there! This whole research filed has expired indeed and most in it should be fired and found some jobs they can actually do, like flipping burgers or sweeping trash.

      --
      Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
    2. Re:Sign of the Singularity by Anonymous Coward · · Score: 0

      IMO, the "terrible twos" are really going to suck when we finally create an artificial super intelligence.
      (That might actually be the great filter.)

  13. Funding should address this problem by Anonymous Coward · · Score: 0

    If this is starting to affect Real Science ( sit down, psychologists ) then this problem needs to be addressed.

    How about grant sources only giving money to two independent research groups addressing the same question ?

  14. When I did political scienceRe:When I did Computer by Anonymous Coward · · Score: 0

    When I did political science it was spelled "Al Gore Rhythm" and it didn't mean what you thought it meant.

    Well maybe it did if you are thinking in NSFW terms.

  15. Wot? by nospam007 · · Score: 1

    Next they'll tell us twins are not exactly the same person.

    1. Re:Wot? by slew · · Score: 1

      Next they'll tell us twins are not exactly the same person.

      Too late, they've already told us a person might not be exactly the same person (aka Vanishing twin syndrome)...

  16. artificial stubborness by Thud457 · · Score: 1

    "No, I don't feel like it"

    --

    the preceding comment is my own and in no way reflects the opinion of the Joint Chiefs of Staff

  17. Re:Imagine that by mentil · · Score: 1

    A tiny elastomer o-ring being too cold can make a rocket booster explode. We'll never get into Space.

    --
    Corruption is convincing someone that the selfless ideal is the same as their selfish ideal.
  18. Don't use scientists ... by CaptainDork · · Score: 1

    ... use AI.

    --
    It little behooves the best of us to comment on the rest of us.
  19. The article is about AI research culture by Anonymous Coward · · Score: 0

    The article is more about how researchers aren't sharing their code (6% shared code, about 30% shared training data, about 50% only shared pseudo code). Should anyone expect reproduced results given different code and training data?

    It's also implied that when using gradient ascent learning strategies, you should expect different results when you start from different beginnings. That is not relevant to the problem of reproduceability described in the rest of the article. I suppose it's just good to know if you're new to that style of program.

  20. Re:Imagine that by frank_adrian314159 · · Score: 1

    We can't even get the basics right.

    Quite a few character, word, and speech recognition algorithms would disagree.

    --
    That is all.
  21. Publish code first by g01d4 · · Score: 1
    If you want to call it science the code should be reviewed and published before results from it are.

    ...only 6% of the presenters shared the algorithm's code...Researchers say there are many reasons for the missing details: The code might be a work in progress, owned by a company, or held tightly by a researcher eager to stay ahead of the competition. It might be dependent on other code, itself unpublished. Or it might be that the code is simply lost, on a crashed disk or stolen laptop - what Rougier calls the "my dog ate my program" problem.

    Amazing.

    ...the training data for an algorithm can influence its performance.

    Fair enough, that's why it's reviewed first.

  22. Huh? by Anonymous Coward · · Score: 0

    Isn't this what science is all about today?

  23. Re:Imagine that by 110010001000 · · Score: 1

    I have more memory on my mobile phone then all the computers in the 1940s. Imagine how much memory a computer will have 70 years from now. Since one thing is possible, all things must be possible. Just just need faith. Yada yada.

  24. What a surprise by OneHundredAndTen · · Score: 0

    The AI field, from the late 60s, has historically been 90% hype and 10% results.

    1. Re:What a surprise by gweihir · · Score: 1

      I think they have mostly optimized away the results today, probably using some "advanced AI algorithms".

      --
      Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
  25. Re:Imagine that by 110010001000 · · Score: 1

    They can't "agree" or "disagree". Then are just programs. At least you called them "algorithms" instead of AI. Meanwhile in the real world...

  26. No surprise by gweihir · · Score: 1

    This just shows that most of the published "results" are based on wishful thinking or outright lies. Happens always when people of mediocre skills become highly enthusiastic about a subject.

    --
    Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
  27. In other news, A.I. studies... by Narcocide · · Score: 1

    ... fail to replicate scientists.

  28. Do people just read the summary? by Anonymous Coward · · Score: 0

    The article mentions that many papers do not publish the source code or data sets. Without those crucial ingredients, reproducing results is hopeless.

    It seems like academic publishing in computer science is less about sharing knowledge and more about selling a product to private industry. The product is more valuable to private industry if you don't reveal how it works to everybody.

  29. Re:Imagine that by gweihir · · Score: 3, Insightful

    Very true. Also, calling an utterly dumb statistical classificator "AI" does not make it intelligent. I like the old terminology better where pattern recognition, planning algorithms, fuzzy database searches, etc. were just called "automation" an it was amply clear that they are not intelligent in any way. As to what is today called "strong AI", I fully agree that at this time we do not even know that it can be done and all available evidence pretty clearly indicates that it probably cannot be done.

    --
    Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
  30. Re:Imagine that by gweihir · · Score: 1

    Indeed, The ever-repeated empty argument of the utterly clueless. Like Marvin "the idiot" Minsky liked to to claim that once computers have more transistors than humans have brain-cells, they will magically become intelligent. Well, that point has been passed a while ago and absolutely nothing happened. And nobody with a clue is the least bit surprised by that.

    --
    Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
  31. I used to play boom beach. by Maxo-Texas · · Score: 1

    And given the exact same commands in a replay of certain battles, the outcomes would be mildly to wildly different.

    There was a random element to behavior in the game and as a result, given the same commands at the same time, the battle replays would display different out comes. Sometimes, you would lose but on replay it showed you won. Sometimes, you won but on replay it showed you lost. Kinda funny. (The result you got live was the one that counted).

    I wish they hadn't been sold and become so aggressive about monetization. But it was a fun 3 years anyway.

    --
    She was like chocolate when she drank... semi-sweet at first and then increasingly bitter.
  32. Re:Imagine that by Anonymous Coward · · Score: 0

    In the real world AI is translating documents, predicting the stock market, doing research, driving cars, and beating humans at games. Call it AI or call it floo, but your feeling of being special is irrelevant to the advances that have been and will continue to be made, and irrelevant to their socioeconomic repercussions.

  33. Re:Imagine that by Anonymous Coward · · Score: 0

    The Challenger SRB O-ring was huge - about 3.5m diameter and 8mm thick

  34. Yet Another Sign by SuperKendall · · Score: 1

    Also like how you sneaked "expiration" in there!

    That was autocorrect - an obvious Freudian slip on the part of AI illuminating true intent. :-)

    --
    "There is more worth loving than we have strength to love." - Brian Jay Stanley
  35. Re:Imagine that by mentil · · Score: 1

    I was unsure of the exact size, but that's still tiny compared to the size of the entire STS.

    --
    Corruption is convincing someone that the selfless ideal is the same as their selfish ideal.
  36. If the Data Can Not Be Duplicated by LifesABeach · · Score: 1

    Then it is Guano In, Gospel Out.

  37. Re:Imagine that by ClickOnThis · · Score: 1

    AI is not real. No amount of wishing it make it real.

    Artificial Intelligence != Human Intelligence. I think this is the important distinction.

    Nevertheless, AI has achieved human-like qualities in many areas, and it is getting better. So I'd say it is indeed real. It's just not human.

    --
    If it weren't for deadlines, nothing would be late.
  38. Open source AI Libraries by wolfheart111 · · Score: 1

    Cant wait until I get my hands on them.

    --
    [($)]
    1. Re:Open source AI Libraries by Anonymous Coward · · Score: 0
  39. Fake News! by Anonymous Coward · · Score: 0

    Who cares about reproducability? News is all that matters, fake or real is now a matter of perception.

  40. Re:Because the 'studies' aren't studies by Anonymous Coward · · Score: 0

    It's bitztream the autism-hating, custom EpiPen-hating, Musk-hating, Qualcomm-hating, Firefox tabs-hating, Slashdot editors-hating Slashdot troll!

  41. Re:Imagine that by Anonymous Coward · · Score: 0

    AI is also predicting my next word wrong too often, and they don't let me turn it off.

  42. Re:Imagine that by ceoyoyo · · Score: 2

    By "the old terminology" do you mean prior to the 1950s? AI has always referred to a somewhat fuzzy collection of techniques that produce machine behaviour that is adaptive or not entirely deterministic.

    The pop culture definition of AI is pretty wildly variable and usually changes depending on the current success-to-promises ratio.

  43. Not scientific research in its proper sense by CustomSolvers2 · · Score: 1
    According to the linked article, the main reasons for these reproducibility problems are:

    The code might be a work in progress, owned by a company, or held tightly by a researcher eager to stay ahead of the competition.

    On top of that, they include another quite "curious" possibility (!!):

    Or it might be that the code is simply lost, on a crashed disk or stolen laptop

    Nothing of this sounds like scientific/university research in its traditional form of sharing knowledge (+ actually having relevant knowledge, what doesn't seem the case with people saying/believing "the code is simply lost"). So, I hope that most of these cases refer to the research performed by (private) companies, which might also behave according to the traditional knowledge sharing ideas anyway.

    Universities and research institutions shouldn't allow the aforementioned scenarios to happen at all. Companies providing any kind of funding should accept the academic rules and understand that the given research can't be restricted. Researchers interested in focusing more on the commercial side of things should work for a company or start their own one.

    Another very relevant issue is how can anything lacking reproducibility and, as such, impossible to be validated be considered scientific research at all? Isn't publication an essential requirement (what needs being peer-reviewed, for what someone had to understand that work, what cannot happen unless it is reproducible)? The alternative would be blind faith, what doesn't sound too scientific-ish. How can this happen at all? Because the ones who can avoid it don't do what they should! And I think that I know the root problem: being too understanding, adaptable, trusting in most of people having common sense/knowing what they do. The solution? Being 100% intolerant with stupidity, dishonesty or any other form of arbitrary imposition. Clear limits (= if you want my research, you would accept these rules; in any other case, your money is worthless here) and no exceptions. It is much easier than what it seems: (unfair, dishonest, greedy) money/attitudes will always be worlds behind honesty/knowledge/principles.

    --
    Custom Solvers 2.0 = Alvaro Carballo Garcia = varocarbas.
  44. Failing... HOW?! by Anonymous Coward · · Score: 0

    HOW are they failing? Are they EXACTLY replicating the first experimenter?