14 ms·

AI gets such a bad rap. People only think of unsolved or sort-of-solved problems as AI, and don't give AI any credit for the problems it has solved, I guess bec

by bo1024 6y ago

AI gets such a bad rap. People only think of unsolved or sort-of-solved problems as AI, and don't give AI any credit for the problems it has solved, I guess because by definition those problems seem easy. Think how much Microsoft Office and competitors have amplified business productivity over the last 20 years (yeah yeah, make your jokes too). Word and Powerpoint and Excel are full of AI whether it's spellcheck or auto-fill, drawing algorithms like "fill with color", etc. So many things that were AI research papers of the 70s, 80s, or 90s. And those innovations continue today. Logistics companies rely on huge amounts of optimization and problem-solving. Finding routes for drivers and deliveries, planning schedules, optimizing store layouts, etc. -- that's AI. Employees use AI tools to improve their lives and productivity whether it's a rideshare or maps app to get to work, speech-to-text, asking Siri for answers, translating web pages, etc. All of this comes out of research in AI or related fields. How many office jobs don't require someone to use a search engine to find and access information related to a query? Information retrieval is one million percent AI. Robotics and automated manufacturing has been huge for a long time -- robotics is closely connected AI and related problems like control theory. The best applications of AI have almost always been to support and enhance human decisionmaking, not replace it.

chrisfosterelli 6y ago
The AI effect: AI gets a bad rap because once something exists and is practical it's no longer called AI. [0]: https://en.wikipedia.org/wiki/AI_effect https://en.wikipedia.org/wiki/AI_effect
- VBprogrammer 6y ago
  This reminds me of the Tim Minchin song Storm. "Do you know what they call alternative medicine that has been proven to work?...Medicine." I've never thought of it that way before but alternative medicine and AI have a lot in common.
  - iamcurious 6y ago
    Yup, the similarities are profound. They both confront the limit of consciousness and what counts as knowledge.
  - riantogo 6y ago
    Do you know what qualifies as alternative medicine? Anything that is not medicine.
    - mayankkaizen 6y ago
      What is medicine? I mean if I take some herb and (successfully) use it to treat abdominal pain without knowing what that herb is or how it works, would that herb be classified as medicine or not? I have read description of many medicines and found out that we still don't know how those medicines work. But they are still called medicines. So what is medicine?
      - kilbuz 6y ago
        If your herb was shown to improve abdominal pain in a certain population through use of well-executed, replicated randomized control trials, I think it would count as medicine, yes.
      - hikarudo 6y ago
        Knowing how something works is better than not knowing. But you can still have a pretty good idea that it does have the desired effect (i.e. verify cause and effect) via randomized controlled trials. Of course, alternative medicine proponents rarely do randomized controlled trials.
        mark-r 6y ago
        If the alternative medicine is widely known, you won't be able to get a patent on it. Without a patent you won't be able to make a profit. Without a profit there's no incentive to spend the enormous money required for a randomized controlled trial.
        TeMPOraL 6y ago
        But if the alternative medicine is widely known to work, it means the effect is powerful enough that a cheap RCT done at a local medical university should be more than enough to demonstrate it. If it can't, then frankly, you don't really know it works.
  - lmilcin 6y ago
    It is a problem with medicine. Normally, we would not only want a proof that something works but also verifiable explanation of HOW something works. Medicine is a problem because we don't understand how many of the chemicals work but the problem is so important (and also it is big business) that we just let it pass and we are happy that we can get some results even if we don't completely understand how we get them.
  - dllthomas 6y ago
    > song You mean 9 minute beat poem.
  - mehrdadn 6y ago
    What're some examples of things that were called "alternative medicine" but that were later proven to work and regarded as "medicine"? Edit: Since people are bringing up ancient examples and kind of missing the point of the question: I'm not looking for examples from the Roman Empire here. Let's stick with the past < 50 years. Maybe something your parents might actually remember being dismissed as "alternative medicine" (whatever that meant at the time) but which now is clearly just accepted "medicine". Basically, try to find something that's in the spirit of the question. The goal is obviously to find things that modern medicine actually previously dismissed and later accepted, not to find a loophole in the question.
    - deleted 6y ago
      [deleted]
    - VBprogrammer 6y ago
      I guess it depends how you define alternative medicine. The bark of a willow tree, a traditional remedy, from which aspirin is derived is given as an example in the beat poem.
      - mehrdadn 6y ago
        The point was you don't have to define it at all. You just need some things that were previously dismissed as "alternative medicine" in the past (say) 50 years, but which are now widely seen as ordinary medicine. I'm looking for examples a lot of people might actually remember from their own lives here... if you have to go back a century to find something then that doesn't count (sorry).
        mark-r 6y ago
        Why doesn't it count? Your restriction seems very arbitrary and makes it much harder to find an answer. There are too many counter examples muddying the space, such as vitamin C curing colds.
        mehrdadn 6y ago
  - SkyBelow 6y ago
    >"Do you know what they call alternative medicine that has been proven to work?...Medicine." I don't like this quote. It is mostly true, yet it is not completely true. But because it is mostly true so many treat it as if it is completely true and thus miss the edge cases where it is not true. Take for example certain substances that are deemed by the US federal government to have no medical value. They cannot be medicines. Yet they are alternative medicines and even prescribed by doctors. Their are even states who go against the federal government by saying these substances do have medical value. And if you go back a few decades, you'll find a time where mainstream science largely ignored any medical benefits of these substances, likely due to pressure from the federal government, and yet at that time those substances were alternative medicines that worked.
    - eindiran 6y ago
      The medical establishment doesn't think that eg marijuana is "alternative medicine" or without medical value: the DEA does. The fact that the medical establishment now accepts marijuana as a therapeutic tool is evidence of the quote: it was "alternative medicine" until there was sufficient evidence that it worked. Other drugs which are Schedule 1 (ie without medical value _according to the DEA_) are in various stages of this process (eg MDMA for PTSD). That's not same thing as saying that there isn't anything which is currently considered "alternative medicine" that works. Rather, once an alternative medicine has sufficient evidence going for it (and is better understood), it becomes less mystical and is accepted as mainstream medicine.
      - SkyBelow 6y ago
        >The medical establishment doesn't think that eg marijuana is "alternative medicine" or without medical value: the DEA does. Does the DEA and the FDA not play a role in what is considered a medicine or an alternative medicine? >The fact that the medical establishment now accepts marijuana as a therapeutic tool is evidence of the quote: it was "alternative medicine" until there was sufficient evidence that it worked. This is effectively making the claim that while there were problems in the past, the fixing of past problems can be taken as evidence that current problems do not exist. I'm arguing the opposite. That problems in the past, without fixing the systematic causes of those problems, is a reliable indicator that we are still at risk of those same problems. Think of it like code. If your code had bugs but you fixed them, should you assume that A: my code had bugs but now they are gone and my code is bug free or B: the process by which I write code allows for bugs, and while I have fixed those bugs I haven't fundamentally changed how I write code so I am still at risk for having bugs. I find the latter the more reasonable approach. >That's not same thing as saying that there isn't anything which is currently considered "alternative medicine" that works. When people use that quote, I find that this is exactly what they are saying in the majority of cases. That if something is currently considered alternative medicine, it doesn't work because otherwise it would be considered medicine. A claim that as our knowledge progresses alternative medicine that works becomes medicine is a much more reasonable claim, because it recognizes there is a timeline and since we aren't at the end of that timeline we allow for some alternative medicine actually work with the recognition in the future it will be refined into medicine. And if someone wanted to make the claim that the majority of alternative medicine doesn't work, I would also fully agree. My issue is people taking a guideline that is generally true and applying it as if it is always true.
- saidajigumi 6y ago
  Back in the early 90s, my grad AI class referred to AI as the "incredible shrinking field". The class kicked off with a black-and-white newsreel style interview from the 1950's with an MIT professor[1] who says, to eternal breathless infamy, something along the lines of "we'll have machines that can think within five years!" Part of the challenge is/was the line of thinking "surely if we can solve Hard Problem X, we'll have intelligence!" This turned out to be entirely wrongheaded, since a vast litany of Hard Problems X turned out to have plain old algorithmic solutions. [1] I keep hoping this shows up online somewhere. It was shot using a machine room as the set, where mid-century modern furniture had been brought in for guest and host!
  - shanemhansen 6y ago
    Maybe in a few years we'll have bridged the gap between computer and machine capabilities. Not by deciding computers think, but by realizing that what humans do is computing.
  - ryanhuff 6y ago
    Was the video titled “The Thinking Machine”?
    - saidajigumi 6y ago
      That indeed looks like it, thanks. It also looks like old memory mixed up bits and pieces of it; the interview wasn't in fact set in the machine room shots.
- chongli 6y ago
  This is because intelligence isn't like most of the other words we use in computer science. It's a word with a history of deep philosophical debate and no clear answer. We haven't come to an agreement on what is intelligence in biological systems so it may be premature to call anything artificially intelligent.
  - zoomablemind 6y ago
    I was wondering what happened to the 'Computer-aided' notion? It was very representative of the utility and provenance. Noone claimed intelligence but literally just the help side of the computers. AI as well could stand for 'Assisted Inference'.
  - hnick 6y ago
    Perhaps that is the point. If we can understand it, it's not intelligence. We're trying to make computers do things we can't understand, and if we do, we've reached our goal. Until then we have Machine Learning or gradient descent or whatever else.
- mehrdadn 6y ago
  Eh, I think we still have the Turing test, and AFAIK it hasn't had a case where it's passed without raising eyebrows for potentially trying to cover up for deficiencies. I think the threshold needs to be high (maybe "beyond a reasonable doubt"?) and reproducible with high probability: I'd say at least X% (I don't know what X should be, but it should be much higher than 50%) of the adults that engage in or read the conversation would need to be convinced it's between two typical humans in their societies. Certainly nothing that leaves room for e.g. excuses like the computer being a 13-year-old from another country, or that leaves inadequate time for the participants to gauge the plausibility...
  - Izkata 6y ago
    For years there have been bots that carry on conversations on dating sites and go undetected...
  - outworlder 6y ago
    Turing test? There are other definitions for 'AI' that are not strong AI. Natural language processing is a subset of AI.
- glaugh 6y ago
  Similarly: “Technology is a word that describes something that doesn’t work yet.” Douglas Adams
- muldvarp 6y ago
  That effect is explained by the fact that the problems in AI research are thought to be solvable only by intelligent agents. This can often turn out to be false. Many problems that seemingly require intelligence don't actually require it. Nick Bostrom wrote the following few lines in his book "Superintelligence: Paths, Dangers, Strategies" (which I absolutely recommend reading): > There is an important sense, however, in which chess-playing AI turned out to be a lesser triumph than many imagined it would be. It was once supposed, perhaps not unreasonably, that in order for a computer to play chess at grandmaster level, it would have to be endowed with a high degree of general intelligence.
  - jkhdigital 6y ago
    Feels like this is about where problems lie along the closed-world/open-world, fast-thinking/slow-thinking fault line.
  - jacquesm 6y ago
    But you know what? It could have been solved with general intelligence. But by defining it as some kind of major breakthrough a bunch of money got spent on solving just that one problem and then declaring victory by the players. I predict that this will happen for anything that gets pointed at as 'the' example of what a general AI would solve. A better benchmark would be that a single piece of software that is not specialized is able to solve two of these problems.
    - larksimian 6y ago
      This is trivial to do right now: Build a software program that recognizes the problem it is being set(limited list of problems it can handle at first, ie. extract text from an image, tell me if an image is a cat or a dog, play a chess game, play a go game) and once it has identified the problem get it to call into a specialized program for that problem(chess playing, OCR whatever). As you want to support more use cases, you just need to plug in a new subprogram and modify the top level problem recognizer. A chat bot sitting on top of a bunch of specialized systems, basically. This is clearly still not general intelligence and probably not super useful, but hey. The true benchmark for intelligence is a piece of software that is presented with some pattern and told to turn it into some other pattern and then figures out how to do it. This probably requires general and deep language comprehension(ie. get me a list of emails for environmental managers at US public water utilities. system needs to have some idea about google, some idea about the EPA and their web resources as a starting point for getting that dataset, some ability to google, read and understand web page data etc). Obviously you can cheat by just having a giant database of information, but at some point you have to be able to answer questions that are not in the database.
- Semiapies 6y ago
  Every time someone write software, someone comes along after-the-fact to try to claim it as "artificial intelligence", no matter how little (or absolutely nothing) the software in question has to do with whatever's being sold that year as "AI". AI used to be sold as human-like or even superhuman intelligence. Now, it just means "running software".
deleted 6y ago
[deleted]
jfkebwjsbx 6y ago
Because laymen, movies and nowadays even tech consultants don’t know (or don’t want to know, in the case of the latter, for financial reasons) what AI is and picture advanced ML, fancy neural networks, acrobatic talking robots, Skynet, GAI, etc. instead. Which is way more cool and gives you more dreams (or money).
Avicebron 6y ago
By that same note, people are calling every automated feature AI and it no longer means what the words actually mean.
- contravariant 6y ago
  Well arguably an automated feature is one that is at least somewhat more intelligent than the manual version (e.g. spell-check vs. a dictionary). Whereas on the other end of the scale people are aimlessly using subtle AI-related techniques like neural networks and calling the result "intelligent" even if it is anything but.
ComodoHacker 6y ago
You can't stretch definition of AI that wide. Where's AI in Microsoft Office? Where's AI in spellchecking? Where's AI in route planning? Demand planning, maybe.
- legolas2412 6y ago
  N-gram based grammar rules for spell checking are by definition machine learning
- mcguire 6y ago
  "Where's AI in route planning?" Should we consider the "if it works, it's no longer AI" point made now?
  - deleted 6y ago
    [deleted]
- bo1024 6y ago
  Imagine taking someone who didn't know English words or sounds, sitting them down with a document and dictionary, and asking them to spell-check it. If they could figure out that "butiful" should be "beautiful" in less than a week I'd call that really freaking intelligent. AI researchers of 40 years ago would be astounded by what Word can do. Route planning is essentially "the" fundamental AI problem. You need to get from A to B and there are 2^100 ways to do it. How do you pick the best one?
  - deleted 6y ago
    [deleted]
  - angry_octet 6y ago
    Just because you were taught routing in your AI class doesn't make it AI. It is a topic in graph theory and combinatorics. Dynamic programming is a useful technique for solving traditional AI problem formulations, but it isn't AI. In contrast, your example of the human is like modern AI, specifically unsupervised learning. I'm sure I could get a human doing that kind of pattern matching quite good at it quite quickly. If I didn't have a learning system I could still write an algorithm for it quite quickly, by computing the Levenshtein distance. But that algorithm would notoriously not understand the context of the sentence, probabilities of words, etc. And indeed Word/Android/iOS spell correct still gets it really wrong much of the time. But the AI used is quite different from old timey backtracking.
correlator 6y ago
Everything you outlined is a use case that is powered by machine learning algorithms. You can discuss all of them without using the phrase "AI." They all likely started with rules engines that solved a real business problem and iterated over time to use more sophisticated back ends. The thing that I don't appreciate in this field is that companies seem more focused on discussing their "AI" than the actual problems they hope to solve. When I see this, my mind jumps to the assumption that these companies are either: 1) looking for easy valuation multiples. 2) looking for a way to impress VCs/investors. 3) they don't actually understand the problem they are solving. This is admittedly a big stereotype on my part, but this stereotype was built on pattern recognition over time.
- esoterica 6y ago
  Machine learning is AI.
  - deleted 6y ago
    [deleted]
- edmundsauto 6y ago
  >this stereotype was built on pattern recognition over time. How good was your input data and labels? ;)
unclebucknasty 6y ago
Well, we can't dismiss the overhype either. Watson and all that. IBM alone is likely responsible for much of the disappointment, with its constant ads around Watson solving the Universe's toughest problems, when what they really seemed to be after is somebody to figure out how to take advantage of this thing they built.
pathseeker 6y ago
>Finding routes for drivers and deliveries, planning schedules, optimizing store layouts, etc. -- that's AI. If a path-finding algorithm that I can write on paper is AI, AI has completely lost all meaning. Let's not call graph traversal and sorting "AI" please.
- afeller08 6y ago
  This. A huge amount of stuff can and should be automated by mundane programming. Since that hasn't been done yet, AI isn't about to automate all of the stuff that shouldn't be automated by mundane programming.
  - joefourier 6y ago
    You're proving the point of the original post. Today's mundane programing used to be considered AI. See: search, fuzzy logic, character recognition. Or even more mundane: object-oriented programming, interpreted languages, and tons of generic algorithms used in daily life, all of which came out of AI labs.
- wutbrodo 6y ago
  No, you're just projecting the modern bar for AI into the past. AI roughly means "things human brains can do that computers can't": when computing was primarily straightforward and analytical ("calculating"), then relatively more sophisticated algorithms that could "solve problems" like mazes absolutely were on the AI frontier. The fact that they've since retreated so far from "things computers can't do" is just a function of the fact that it was an early success in the field. Your comment is just a crystallization of what the parent comment is talking about: claiming something isn't AI because "pft that's such an easy, solved problem" _after_ it's solved defines away the possibility that AI can solve problems.
  - Barrin92 6y ago
    If anything the opposite is true. When Minsky et al set out to define AI what they really meant was 'thinking machines'. If anything the opposite has happened. In a painful attempt to push forward notions of success in AI almost purely mechanical tasks have been claimed to be AI, while there is virtually no progress on building machines that can think. I mean sure you can claim all day that the navigation system in your car calculates you a billion routes per second and if that's intelligence my smart-toaster is probably more intelligent than everyone here together, but it completely misses the point, and the reason why people have expanded the term so much is because there has been so little progress on genuine intelligence.
xz0r 6y ago
> Logistics companies rely on huge amounts of optimization and problem-solving. Having worked at the largest tech based Logistics company in India, I can say, we did rely on optimization and problem-solving, but none of them involved AI, they were mathematical models and not black box.
- colechristensen 6y ago
  There's my bet on a less hyped but very prevalent future. Really good real mathematical models of things, that is, deriving systems for your product which can predict and control from scientific laws, not just black box automation. Of course this isn't new, but a broad focus on specializing on developing talent to create these models and methodology and tech to help would be.
- bulldoa 6y ago
  what kind of mathematical models do you guys use (like convex optimizations?), I am very interested in this subject and would hope to learn more.
- Melting_Harps 6y ago
  > Having worked at the largest tech based Logistics company in India, I can say, we did rely on optimization and problem-solving, but none of them involved AI, they were mathematical models and not black box. I was going to say the same thing, but I worked at BMW and VW and spearheaded several initiatives with Corporate partners that relied more on optimizing via mathematical models/data sets within the warrantied parts/Takata airbag recall at BMW and the Tdi Diesel-gate buy program at VW. It entailed lots of data analysis and some trial by error on my part that eventually got us a favourable result, not AI. AI can be useful, one day, but I'm returning back to Supply Chain analytics and Logistics and not much seems to have changed in those years. I submitted my proposal for a Supply Chain Analytics course as my final project that I drew up in 2017 at BMW and got 99.7% for my thorough, and more importunately to me, relevant analysis and execution of a scheme to optimize leadtime and overall turn over using the means and methods available back then. A part of me wishes I could just run an algo/AI protocol with predictive modeling to do that all for me, as it almost got me fired several times trying to deploy it and I had to go over managements head and straight to the owners and corporate to get them to try it. Luckily, I was able to negotiate a return to VW as result of my scheme, who were hemorrhaging Billions, were getting execs thrown in prison at the time so were way more receptive to ideas of cost cutting. Crazy days... * AI initially inserted 'trail,' instead of a commonly used phrase 'trial by error' perhaps proving how autocorrect/spellcheck AI usecases are still not where they need to be to prove the point of the aforementioned post.
colechristensen 6y ago
By that definition, it would be hard to separate out anything a computer does which isn't AI, which is I think not very useful. AI "gets a bad rap" because it is past its hype peak. The number of people realizing that slapping an AI sticker on your product is largely BS and doesn't impress any more is growing, and AI isn't magic to everybody that can solve every problem. It's the same overhype cycle which happens with just about everything.
jmiserez 6y ago
>Information retrieval is one million percent AI. You can add AI of course, but the basics are just math and statistics, e.g. take a look at this book: https://nlp.stanford.edu/IR-book/information-retrieval-book.html https://nlp.stanford.edu/IR-book/information-retrieval-book....
perl4ever 6y ago
'drawing algorithms like "fill with color"' What? You mean this: https://en.wikipedia.org/wiki/Flood_fill https://en.wikipedia.org/wiki/Flood_fill Who ever called that artificial intelligence?
- gnulinux 6y ago
  The classical, as in old fashioned, 70s, 80s definition of AI is solving any problem using heuristics. This is contrasted with algorithmic problem solving; which is impossible to do if your problem is intractable (you can't have an efficient 3SAT solver if you don't use heuristics). The canonical example is CSP (constraint satisfaction problem) solvers: people legit thought, encoding knowledge in a Prolog-like CSP solver will allow us to create AI. AI researchers before the "AI Winter" thought AI is all about encoding the information in a way computers can use heuristic to solve problems like humans.
  - perl4ever 6y ago
    Perhaps, it just jumped out at me because I've implemented one of the classic algorithms and it didn't involve heuristics.
- mkl 6y ago
  When the shapes are hand drawn, and the boundaries have gaps in them, heuristics are needed. Same if filling an object in a photo - where are the edges, exactly? That kind of object recognition is familiar ML stuff. The pictures in this paper show quite a few examples of filling problems: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.655.5364&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.655... I don't know about MS Office, specifically, though.
closeparen 6y ago
Why would we have such a term as AI, if not to distinguish it from algorithmic? I thought the whole point was to get out of the business of having to write down procedures for everything, to have the computer approach novel problems like a programmer does. Is this only a contemporary perspective? Seems like that's where the goalposts were at least 15 years ago.
- smacktoward 6y ago
  If we still defined AI the way it was originally defined, the AI prophets would have to admit they are nowhere near developing AI. That would have been uncomfortable, so the AI prophets have instead responded by changing the meaning of the term.
z3ncyberpunk 6y ago
Might help is there actually was AI... Because currently we just have a lot of people misnomering machine learning, aka glorified brute force pattern recognition, as AI.
angry_octet 6y ago
Is this the point in the curve we redefine anything successful as using 'AI' because it uses a computer program? Literally the only things you mention using AI/ML techniques are "speech-to-text, asking Siri for answers, translating web pages" and search engines, which are external to business process. Internal search is usually a disaster because processes are document based rather than web/publication based. There are ML applications used for business, like speech recog, pricing, marketing and so on, but not so much for business processes. Where are the AI tools for parsing legal contracts? Agents for finding and negotiating prices with suppliers? Filling out regulatory reports?
- bo1024 6y ago
  AI is much broader and older than machine learning. I suggest the textbook "AI: A Modern Approach".
  - angry_octet 6y ago
    Dude, AI is not everything that involves an algorithm, even if AI uses algorithms.
deleted 6y ago
[deleted]
dvfjsdhgfv 6y ago
> Logistics companies rely on huge amounts of optimization and problem-solving. Finding routes for drivers and deliveries, planning schedules, optimizing store layouts, etc. -- that's AI. Your definition of AI seems to be particularly broad. There are several general and specific algorithms designed to handle the examples you gave and they have been working well for the last few decades, some even earlier and have been implemented on computers later. E.g. linear programming was designed to solve several classes of programs and was initially done on paper. Lumping all this as "AI" doesn't seem fair to me.
sevensor 6y ago
> Logistics companies rely on huge amounts of optimization and problem-solving. Finding routes for drivers and deliveries, planning schedules, optimizing store layouts, etc. -- that's AI. Is it? These have largely been done with MILP and related tools for decades, and those approaches have never been called AI. What AI techniques are you thinking of here? Anyway, AI gets a bad rap because there's so much hype and snake oil out there that the signal is being lost in the noise. I'll be much better disposed towards it once the next AI winter hits. Like for instance, I have great respect for anybody selling an expert system at this point in time.

by bo1024 6y ago

chrisfosterelli 6y ago

The AI effect: AI gets a bad rap because once something exists and is practical it's no longer called AI. [0]: https://en.wikipedia.org/wiki/AI_effect https://en.wikipedia.org/wiki/AI_effect

VBprogrammer 6y ago
This reminds me of the Tim Minchin song Storm. "Do you know what they call alternative medicine that has been proven to work?...Medicine." I've never thought of it that way before but alternative medicine and AI have a lot in common.
- iamcurious 6y ago
  Yup, the similarities are profound. They both confront the limit of consciousness and what counts as knowledge.
- riantogo 6y ago
  Do you know what qualifies as alternative medicine? Anything that is not medicine.
  - mayankkaizen 6y ago
    What is medicine? I mean if I take some herb and (successfully) use it to treat abdominal pain without knowing what that herb is or how it works, would that herb be classified as medicine or not? I have read description of many medicines and found out that we still don't know how those medicines work. But they are still called medicines. So what is medicine?
    - kilbuz 6y ago
      If your herb was shown to improve abdominal pain in a certain population through use of well-executed, replicated randomized control trials, I think it would count as medicine, yes.
    - hikarudo 6y ago
      Knowing how something works is better than not knowing. But you can still have a pretty good idea that it does have the desired effect (i.e. verify cause and effect) via randomized controlled trials. Of course, alternative medicine proponents rarely do randomized controlled trials.
      - mark-r 6y ago
        If the alternative medicine is widely known, you won't be able to get a patent on it. Without a patent you won't be able to make a profit. Without a profit there's no incentive to spend the enormous money required for a randomized controlled trial.
        TeMPOraL 6y ago
        But if the alternative medicine is widely known to work, it means the effect is powerful enough that a cheap RCT done at a local medical university should be more than enough to demonstrate it. If it can't, then frankly, you don't really know it works.
- lmilcin 6y ago
  It is a problem with medicine. Normally, we would not only want a proof that something works but also verifiable explanation of HOW something works. Medicine is a problem because we don't understand how many of the chemicals work but the problem is so important (and also it is big business) that we just let it pass and we are happy that we can get some results even if we don't completely understand how we get them.
- dllthomas 6y ago
  > song You mean 9 minute beat poem.
- mehrdadn 6y ago
  What're some examples of things that were called "alternative medicine" but that were later proven to work and regarded as "medicine"? Edit: Since people are bringing up ancient examples and kind of missing the point of the question: I'm not looking for examples from the Roman Empire here. Let's stick with the past < 50 years. Maybe something your parents might actually remember being dismissed as "alternative medicine" (whatever that meant at the time) but which now is clearly just accepted "medicine". Basically, try to find something that's in the spirit of the question. The goal is obviously to find things that modern medicine actually previously dismissed and later accepted, not to find a loophole in the question.
  - deleted 6y ago
    [deleted]
  - VBprogrammer 6y ago
    I guess it depends how you define alternative medicine. The bark of a willow tree, a traditional remedy, from which aspirin is derived is given as an example in the beat poem.
    - mehrdadn 6y ago
      The point was you don't have to define it at all. You just need some things that were previously dismissed as "alternative medicine" in the past (say) 50 years, but which are now widely seen as ordinary medicine. I'm looking for examples a lot of people might actually remember from their own lives here... if you have to go back a century to find something then that doesn't count (sorry).
      - mark-r 6y ago
        Why doesn't it count? Your restriction seems very arbitrary and makes it much harder to find an answer. There are too many counter examples muddying the space, such as vitamin C curing colds.
        mehrdadn 6y ago
- SkyBelow 6y ago
  >"Do you know what they call alternative medicine that has been proven to work?...Medicine." I don't like this quote. It is mostly true, yet it is not completely true. But because it is mostly true so many treat it as if it is completely true and thus miss the edge cases where it is not true. Take for example certain substances that are deemed by the US federal government to have no medical value. They cannot be medicines. Yet they are alternative medicines and even prescribed by doctors. Their are even states who go against the federal government by saying these substances do have medical value. And if you go back a few decades, you'll find a time where mainstream science largely ignored any medical benefits of these substances, likely due to pressure from the federal government, and yet at that time those substances were alternative medicines that worked.
  - eindiran 6y ago
    The medical establishment doesn't think that eg marijuana is "alternative medicine" or without medical value: the DEA does. The fact that the medical establishment now accepts marijuana as a therapeutic tool is evidence of the quote: it was "alternative medicine" until there was sufficient evidence that it worked. Other drugs which are Schedule 1 (ie without medical value _according to the DEA_) are in various stages of this process (eg MDMA for PTSD). That's not same thing as saying that there isn't anything which is currently considered "alternative medicine" that works. Rather, once an alternative medicine has sufficient evidence going for it (and is better understood), it becomes less mystical and is accepted as mainstream medicine.
    - SkyBelow 6y ago
      >The medical establishment doesn't think that eg marijuana is "alternative medicine" or without medical value: the DEA does. Does the DEA and the FDA not play a role in what is considered a medicine or an alternative medicine? >The fact that the medical establishment now accepts marijuana as a therapeutic tool is evidence of the quote: it was "alternative medicine" until there was sufficient evidence that it worked. This is effectively making the claim that while there were problems in the past, the fixing of past problems can be taken as evidence that current problems do not exist. I'm arguing the opposite. That problems in the past, without fixing the systematic causes of those problems, is a reliable indicator that we are still at risk of those same problems. Think of it like code. If your code had bugs but you fixed them, should you assume that A: my code had bugs but now they are gone and my code is bug free or B: the process by which I write code allows for bugs, and while I have fixed those bugs I haven't fundamentally changed how I write code so I am still at risk for having bugs. I find the latter the more reasonable approach. >That's not same thing as saying that there isn't anything which is currently considered "alternative medicine" that works. When people use that quote, I find that this is exactly what they are saying in the majority of cases. That if something is currently considered alternative medicine, it doesn't work because otherwise it would be considered medicine. A claim that as our knowledge progresses alternative medicine that works becomes medicine is a much more reasonable claim, because it recognizes there is a timeline and since we aren't at the end of that timeline we allow for some alternative medicine actually work with the recognition in the future it will be refined into medicine. And if someone wanted to make the claim that the majority of alternative medicine doesn't work, I would also fully agree. My issue is people taking a guideline that is generally true and applying it as if it is always true.
saidajigumi 6y ago
Back in the early 90s, my grad AI class referred to AI as the "incredible shrinking field". The class kicked off with a black-and-white newsreel style interview from the 1950's with an MIT professor[1] who says, to eternal breathless infamy, something along the lines of "we'll have machines that can think within five years!" Part of the challenge is/was the line of thinking "surely if we can solve Hard Problem X, we'll have intelligence!" This turned out to be entirely wrongheaded, since a vast litany of Hard Problems X turned out to have plain old algorithmic solutions. [1] I keep hoping this shows up online somewhere. It was shot using a machine room as the set, where mid-century modern furniture had been brought in for guest and host!
- shanemhansen 6y ago
  Maybe in a few years we'll have bridged the gap between computer and machine capabilities. Not by deciding computers think, but by realizing that what humans do is computing.
- ryanhuff 6y ago
  Was the video titled “The Thinking Machine”?
  - saidajigumi 6y ago
    That indeed looks like it, thanks. It also looks like old memory mixed up bits and pieces of it; the interview wasn't in fact set in the machine room shots.
chongli 6y ago
This is because intelligence isn't like most of the other words we use in computer science. It's a word with a history of deep philosophical debate and no clear answer. We haven't come to an agreement on what is intelligence in biological systems so it may be premature to call anything artificially intelligent.
- zoomablemind 6y ago
  I was wondering what happened to the 'Computer-aided' notion? It was very representative of the utility and provenance. Noone claimed intelligence but literally just the help side of the computers. AI as well could stand for 'Assisted Inference'.
- hnick 6y ago
  Perhaps that is the point. If we can understand it, it's not intelligence. We're trying to make computers do things we can't understand, and if we do, we've reached our goal. Until then we have Machine Learning or gradient descent or whatever else.
mehrdadn 6y ago
Eh, I think we still have the Turing test, and AFAIK it hasn't had a case where it's passed without raising eyebrows for potentially trying to cover up for deficiencies. I think the threshold needs to be high (maybe "beyond a reasonable doubt"?) and reproducible with high probability: I'd say at least X% (I don't know what X should be, but it should be much higher than 50%) of the adults that engage in or read the conversation would need to be convinced it's between two typical humans in their societies. Certainly nothing that leaves room for e.g. excuses like the computer being a 13-year-old from another country, or that leaves inadequate time for the participants to gauge the plausibility...
- Izkata 6y ago
  For years there have been bots that carry on conversations on dating sites and go undetected...
- outworlder 6y ago
  Turing test? There are other definitions for 'AI' that are not strong AI. Natural language processing is a subset of AI.
glaugh 6y ago
Similarly: “Technology is a word that describes something that doesn’t work yet.” Douglas Adams
muldvarp 6y ago
That effect is explained by the fact that the problems in AI research are thought to be solvable only by intelligent agents. This can often turn out to be false. Many problems that seemingly require intelligence don't actually require it. Nick Bostrom wrote the following few lines in his book "Superintelligence: Paths, Dangers, Strategies" (which I absolutely recommend reading): > There is an important sense, however, in which chess-playing AI turned out to be a lesser triumph than many imagined it would be. It was once supposed, perhaps not unreasonably, that in order for a computer to play chess at grandmaster level, it would have to be endowed with a high degree of general intelligence.
- jkhdigital 6y ago
  Feels like this is about where problems lie along the closed-world/open-world, fast-thinking/slow-thinking fault line.
- jacquesm 6y ago
  But you know what? It could have been solved with general intelligence. But by defining it as some kind of major breakthrough a bunch of money got spent on solving just that one problem and then declaring victory by the players. I predict that this will happen for anything that gets pointed at as 'the' example of what a general AI would solve. A better benchmark would be that a single piece of software that is not specialized is able to solve two of these problems.
  - larksimian 6y ago
    This is trivial to do right now: Build a software program that recognizes the problem it is being set(limited list of problems it can handle at first, ie. extract text from an image, tell me if an image is a cat or a dog, play a chess game, play a go game) and once it has identified the problem get it to call into a specialized program for that problem(chess playing, OCR whatever). As you want to support more use cases, you just need to plug in a new subprogram and modify the top level problem recognizer. A chat bot sitting on top of a bunch of specialized systems, basically. This is clearly still not general intelligence and probably not super useful, but hey. The true benchmark for intelligence is a piece of software that is presented with some pattern and told to turn it into some other pattern and then figures out how to do it. This probably requires general and deep language comprehension(ie. get me a list of emails for environmental managers at US public water utilities. system needs to have some idea about google, some idea about the EPA and their web resources as a starting point for getting that dataset, some ability to google, read and understand web page data etc). Obviously you can cheat by just having a giant database of information, but at some point you have to be able to answer questions that are not in the database.
Semiapies 6y ago
Every time someone write software, someone comes along after-the-fact to try to claim it as "artificial intelligence", no matter how little (or absolutely nothing) the software in question has to do with whatever's being sold that year as "AI". AI used to be sold as human-like or even superhuman intelligence. Now, it just means "running software".

deleted 6y ago

[deleted]

jfkebwjsbx 6y ago

Because laymen, movies and nowadays even tech consultants don’t know (or don’t want to know, in the case of the latter, for financial reasons) what AI is and picture advanced ML, fancy neural networks, acrobatic talking robots, Skynet, GAI, etc. instead. Which is way more cool and gives you more dreams (or money).

Avicebron 6y ago

By that same note, people are calling every automated feature AI and it no longer means what the words actually mean.

contravariant 6y ago
Well arguably an automated feature is one that is at least somewhat more intelligent than the manual version (e.g. spell-check vs. a dictionary). Whereas on the other end of the scale people are aimlessly using subtle AI-related techniques like neural networks and calling the result "intelligent" even if it is anything but.

ComodoHacker 6y ago

You can't stretch definition of AI that wide. Where's AI in Microsoft Office? Where's AI in spellchecking? Where's AI in route planning? Demand planning, maybe.

legolas2412 6y ago
N-gram based grammar rules for spell checking are by definition machine learning
mcguire 6y ago
"Where's AI in route planning?" Should we consider the "if it works, it's no longer AI" point made now?
- deleted 6y ago
  [deleted]
bo1024 6y ago
Imagine taking someone who didn't know English words or sounds, sitting them down with a document and dictionary, and asking them to spell-check it. If they could figure out that "butiful" should be "beautiful" in less than a week I'd call that really freaking intelligent. AI researchers of 40 years ago would be astounded by what Word can do. Route planning is essentially "the" fundamental AI problem. You need to get from A to B and there are 2^100 ways to do it. How do you pick the best one?
- deleted 6y ago
  [deleted]
- angry_octet 6y ago
  Just because you were taught routing in your AI class doesn't make it AI. It is a topic in graph theory and combinatorics. Dynamic programming is a useful technique for solving traditional AI problem formulations, but it isn't AI. In contrast, your example of the human is like modern AI, specifically unsupervised learning. I'm sure I could get a human doing that kind of pattern matching quite good at it quite quickly. If I didn't have a learning system I could still write an algorithm for it quite quickly, by computing the Levenshtein distance. But that algorithm would notoriously not understand the context of the sentence, probabilities of words, etc. And indeed Word/Android/iOS spell correct still gets it really wrong much of the time. But the AI used is quite different from old timey backtracking.

correlator 6y ago

Everything you outlined is a use case that is powered by machine learning algorithms. You can discuss all of them without using the phrase "AI." They all likely started with rules engines that solved a real business problem and iterated over time to use more sophisticated back ends. The thing that I don't appreciate in this field is that companies seem more focused on discussing their "AI" than the actual problems they hope to solve. When I see this, my mind jumps to the assumption that these companies are either: 1) looking for easy valuation multiples. 2) looking for a way to impress VCs/investors. 3) they don't actually understand the problem they are solving. This is admittedly a big stereotype on my part, but this stereotype was built on pattern recognition over time.

esoterica 6y ago
Machine learning is AI.
- deleted 6y ago
  [deleted]
edmundsauto 6y ago
>this stereotype was built on pattern recognition over time. How good was your input data and labels? ;)

unclebucknasty 6y ago

Well, we can't dismiss the overhype either. Watson and all that. IBM alone is likely responsible for much of the disappointment, with its constant ads around Watson solving the Universe's toughest problems, when what they really seemed to be after is somebody to figure out how to take advantage of this thing they built.

pathseeker 6y ago

>Finding routes for drivers and deliveries, planning schedules, optimizing store layouts, etc. -- that's AI. If a path-finding algorithm that I can write on paper is AI, AI has completely lost all meaning. Let's not call graph traversal and sorting "AI" please.

afeller08 6y ago
This. A huge amount of stuff can and should be automated by mundane programming. Since that hasn't been done yet, AI isn't about to automate all of the stuff that shouldn't be automated by mundane programming.
- joefourier 6y ago
  You're proving the point of the original post. Today's mundane programing used to be considered AI. See: search, fuzzy logic, character recognition. Or even more mundane: object-oriented programming, interpreted languages, and tons of generic algorithms used in daily life, all of which came out of AI labs.
wutbrodo 6y ago
No, you're just projecting the modern bar for AI into the past. AI roughly means "things human brains can do that computers can't": when computing was primarily straightforward and analytical ("calculating"), then relatively more sophisticated algorithms that could "solve problems" like mazes absolutely were on the AI frontier. The fact that they've since retreated so far from "things computers can't do" is just a function of the fact that it was an early success in the field. Your comment is just a crystallization of what the parent comment is talking about: claiming something isn't AI because "pft that's such an easy, solved problem" _after_ it's solved defines away the possibility that AI can solve problems.
- Barrin92 6y ago
  If anything the opposite is true. When Minsky et al set out to define AI what they really meant was 'thinking machines'. If anything the opposite has happened. In a painful attempt to push forward notions of success in AI almost purely mechanical tasks have been claimed to be AI, while there is virtually no progress on building machines that can think. I mean sure you can claim all day that the navigation system in your car calculates you a billion routes per second and if that's intelligence my smart-toaster is probably more intelligent than everyone here together, but it completely misses the point, and the reason why people have expanded the term so much is because there has been so little progress on genuine intelligence.

xz0r 6y ago

> Logistics companies rely on huge amounts of optimization and problem-solving. Having worked at the largest tech based Logistics company in India, I can say, we did rely on optimization and problem-solving, but none of them involved AI, they were mathematical models and not black box.

colechristensen 6y ago
There's my bet on a less hyped but very prevalent future. Really good real mathematical models of things, that is, deriving systems for your product which can predict and control from scientific laws, not just black box automation. Of course this isn't new, but a broad focus on specializing on developing talent to create these models and methodology and tech to help would be.
bulldoa 6y ago
what kind of mathematical models do you guys use (like convex optimizations?), I am very interested in this subject and would hope to learn more.
Melting_Harps 6y ago
> Having worked at the largest tech based Logistics company in India, I can say, we did rely on optimization and problem-solving, but none of them involved AI, they were mathematical models and not black box. I was going to say the same thing, but I worked at BMW and VW and spearheaded several initiatives with Corporate partners that relied more on optimizing via mathematical models/data sets within the warrantied parts/Takata airbag recall at BMW and the Tdi Diesel-gate buy program at VW. It entailed lots of data analysis and some trial by error on my part that eventually got us a favourable result, not AI. AI can be useful, one day, but I'm returning back to Supply Chain analytics and Logistics and not much seems to have changed in those years. I submitted my proposal for a Supply Chain Analytics course as my final project that I drew up in 2017 at BMW and got 99.7% for my thorough, and more importunately to me, relevant analysis and execution of a scheme to optimize leadtime and overall turn over using the means and methods available back then. A part of me wishes I could just run an algo/AI protocol with predictive modeling to do that all for me, as it almost got me fired several times trying to deploy it and I had to go over managements head and straight to the owners and corporate to get them to try it. Luckily, I was able to negotiate a return to VW as result of my scheme, who were hemorrhaging Billions, were getting execs thrown in prison at the time so were way more receptive to ideas of cost cutting. Crazy days... * AI initially inserted 'trail,' instead of a commonly used phrase 'trial by error' perhaps proving how autocorrect/spellcheck AI usecases are still not where they need to be to prove the point of the aforementioned post.

colechristensen 6y ago

By that definition, it would be hard to separate out anything a computer does which isn't AI, which is I think not very useful. AI "gets a bad rap" because it is past its hype peak. The number of people realizing that slapping an AI sticker on your product is largely BS and doesn't impress any more is growing, and AI isn't magic to everybody that can solve every problem. It's the same overhype cycle which happens with just about everything.

jmiserez 6y ago

>Information retrieval is one million percent AI. You can add AI of course, but the basics are just math and statistics, e.g. take a look at this book: https://nlp.stanford.edu/IR-book/information-retrieval-book.html https://nlp.stanford.edu/IR-book/information-retrieval-book....

perl4ever 6y ago

'drawing algorithms like "fill with color"' What? You mean this: https://en.wikipedia.org/wiki/Flood_fill https://en.wikipedia.org/wiki/Flood_fill Who ever called that artificial intelligence?

gnulinux 6y ago
The classical, as in old fashioned, 70s, 80s definition of AI is solving any problem using heuristics. This is contrasted with algorithmic problem solving; which is impossible to do if your problem is intractable (you can't have an efficient 3SAT solver if you don't use heuristics). The canonical example is CSP (constraint satisfaction problem) solvers: people legit thought, encoding knowledge in a Prolog-like CSP solver will allow us to create AI. AI researchers before the "AI Winter" thought AI is all about encoding the information in a way computers can use heuristic to solve problems like humans.
- perl4ever 6y ago
  Perhaps, it just jumped out at me because I've implemented one of the classic algorithms and it didn't involve heuristics.
mkl 6y ago
When the shapes are hand drawn, and the boundaries have gaps in them, heuristics are needed. Same if filling an object in a photo - where are the edges, exactly? That kind of object recognition is familiar ML stuff. The pictures in this paper show quite a few examples of filling problems: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.655.5364&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.655... I don't know about MS Office, specifically, though.

closeparen 6y ago

Why would we have such a term as AI, if not to distinguish it from algorithmic? I thought the whole point was to get out of the business of having to write down procedures for everything, to have the computer approach novel problems like a programmer does. Is this only a contemporary perspective? Seems like that's where the goalposts were at least 15 years ago.

smacktoward 6y ago
If we still defined AI the way it was originally defined, the AI prophets would have to admit they are nowhere near developing AI. That would have been uncomfortable, so the AI prophets have instead responded by changing the meaning of the term.

z3ncyberpunk 6y ago

Might help is there actually was AI... Because currently we just have a lot of people misnomering machine learning, aka glorified brute force pattern recognition, as AI.

angry_octet 6y ago

Is this the point in the curve we redefine anything successful as using 'AI' because it uses a computer program? Literally the only things you mention using AI/ML techniques are "speech-to-text, asking Siri for answers, translating web pages" and search engines, which are external to business process. Internal search is usually a disaster because processes are document based rather than web/publication based. There are ML applications used for business, like speech recog, pricing, marketing and so on, but not so much for business processes. Where are the AI tools for parsing legal contracts? Agents for finding and negotiating prices with suppliers? Filling out regulatory reports?

bo1024 6y ago
AI is much broader and older than machine learning. I suggest the textbook "AI: A Modern Approach".
- angry_octet 6y ago
  Dude, AI is not everything that involves an algorithm, even if AI uses algorithms.

deleted 6y ago

[deleted]

dvfjsdhgfv 6y ago

> Logistics companies rely on huge amounts of optimization and problem-solving. Finding routes for drivers and deliveries, planning schedules, optimizing store layouts, etc. -- that's AI. Your definition of AI seems to be particularly broad. There are several general and specific algorithms designed to handle the examples you gave and they have been working well for the last few decades, some even earlier and have been implemented on computers later. E.g. linear programming was designed to solve several classes of programs and was initially done on paper. Lumping all this as "AI" doesn't seem fair to me.

sevensor 6y ago

> Logistics companies rely on huge amounts of optimization and problem-solving. Finding routes for drivers and deliveries, planning schedules, optimizing store layouts, etc. -- that's AI. Is it? These have largely been done with MILP and related tools for decades, and those approaches have never been called AI. What AI techniques are you thinking of here? Anyway, AI gets a bad rap because there's so much hype and snake oil out there that the signal is being lost in the noise. I'll be much better disposed towards it once the next AI winter hits. Like for instance, I have great respect for anybody selling an expert system at this point in time.