20 ms·

The AI Misinformation Epidemic

337 points by aaronyy 10y ago

zackchase 10y ago
Some strident Singularitarians joined the comment thread.
- kordless 10y ago
  I'm from the camp the singularity already happened! ;)
  - archgoon 10y ago
    Shh! Quiet! Or I'll feed you to the Basilisk.
  - colordrops 10y ago
    It's always happening.
  - Banthum 10y ago
    Probably happened when proto-people developed complex grunting noises. Or maybe before - with grasping digits? Hard to tell.
  - jodrellblank 10y ago
    I'm from the camp the singularity is a continuous process. When you travel away from the Sun, the light from it gets dimmer and dimmer and dimmer, until it becomes single photons appearing with more and more delays but on average energy of 'dimmer' light. Fly towards the Sun and there isn't a sudden cutoff point where it goes from dark to bright, or bright to incandescent, it's a continual increase. Same with life, lots of people born, lots of intensity around birth and infant children and parents and education, intensity diminishes with age as people spread out and dissipate, everyone's looking back in at the source of new life while getting further and further from it and more and more separated from each other and lower energy levels and less and less 'happening'. Singularity? Moving towards the intensity with technological development and more intricate, faster, and sheerly more connectivity all over, more encoding of ideas into information patterns. Unless you want to imagine it like flying towards the Sun becoming falling towards the Sun, becoming a specific point where everyone burns up and dies. :/
    - beaconstudios 10y ago
      the whole premise of a singularity is that we will hit a point of exponential technological growth, extrapolated from the accelerating pace of technological development over human history and usually based on the idea that we'll make a self-iterating AI which will lead to runaway intelligence. The "singularity" specifically is intended as a tipping-point where the acceleration of technology becomes faster than human capability (i.e. the approaching-vertical line on an exponential curve).
      - arca_vorago 10y ago
        Yep, this is why the singularity is a zero-sum game... I expect many entities to vie for the title, but the first one there will subsequently dominate... which is why it's my intention to program my conciousness into my own AI which seeks to become the singularity and therefor my digial conciousness version will become the ultimate god of the universe. mad scientist laugh
        beaconstudios 10y ago
        race you to the pseudoreligious finish line!
    - kordless 10y ago
      > becoming a specific point where everyone burns up and dies Some of us seek this in the attainment of Nirvana.
- Teodolfo 10y ago
  The singularity cult is real. The geek rapture will occur when they blog about someone else making God in a Box hard enough to drown out the normal charlatans. Please fund their blogging, it is the most impactful way you can spend your money.
unityByFreedom 10y ago
Someone tell Musk. Oh wait, he profits from such misinformation. Nevermind.
- prvnsmpth 10y ago
  Care to elaborate?
  - acover 10y ago
    One way he profits is in the expectations of self driving cars. If people expect it in 3 years and it to be 10x better than humans [to quote musk] then there is huge value in any company that can provide it. Tesla has a market cap larger than Ford. Tesla also has been on the edge of bankruptcy every couple years and recently raised $1 billion in capital.
    - graycat 10y ago
      Sounds like a good short selling opportunity.
      - unityByFreedom 10y ago
        Hard to time that kind of thing. Not worth it when you risk losing your shirt. You can lose an infinite amount of money shorting, whereas going long you might only lose all of what you put in.
        jfoutz 10y ago
        don't options solve this? Buy a put at 50, watch it fall, then exercise. Doesn't work out, and you're only out the premium.
        cglouch 10y ago
        Options solve it in the sense that you limit your downside, but you can still very well lose your premium. Even if you're 100% convinced that $TSLA is overvalued, markets can remain irrational longer than you can remain solvent, and your puts may very well expire worthless.
apsec112 10y ago
I'm very interested in this topic, but I'd hold off on discussing until the other posts are out. The current post is largely just a summary of what future posts will say, and doesn't cover much by itself.
charles-salvia 10y ago
Yeah, terms like "machine learning" and "AI" have basically become buzz words which, to most laymen, probably encourage the idea that we're on the cusp of creating Data from Star Trek. Unfortunately, the reality is that.... sorry... it's mostly just statistical algorithms based around regression and intermediate calculus. State-of-the-art "deep" neural networks are not really anything like the absurdly parallel, asynchronous biological networks that power our neo-cortex - rather, they're basically an application of matrix multiplication designed to "learn" a function by iteratively minimizing an error value using gradient descent. It's still very unclear what, if anything, this algorithm has in common with how a human brain actually operates. It turns out that these kind of statistical algorithms can work pretty well when you have petabytes of data to learn from. But we're still not anywhere near the unsupervised learning capabilities demonstrated by a human infant.
- eli_gottlieb 10y ago
  > It's still very unclear what, if anything, this algorithm has in common with how a human brain actually operates. Not very much at all. Most psychological evidence shows that human beings seem to operate off composable, hierarchical generative models and probabilistic inference. Deep neural networks are basically just huge continuous circuit approximators.
  - akyu 10y ago
    >composable, hierarchical generative models and probabilistic inference. Deep neural networks are basically just huge continuous circuit approximators. These two things are not mutually exclusive.
    - eli_gottlieb 10y ago
      What sort of neural network implements human-style learning and inference?
      - shahbaby 10y ago
bluetwo 10y ago
Remember those AT&T commercials "You Will..."? They won a bunch of awards for them but most of the technologies, if they came to be, were brought to you by people other than AT&T. Same thing with the next steps in AI. They might happen, but they aren't going to come from the companies who currently have large marketing departments looking for something to hype.
tempodox 10y ago
The epidemic starts with calling it “AI”.
- zackchase 10y ago
  I generally agree with this. I used machine learning almost exclusively in the article. Yet "AI misinformation" seems more appropriate in the title since the misinformation, generally, is in reference to "artificial intelligence".
- graycat 10y ago
  Yup, we've had several AI winters. Now we have an AI Spring of Hype. Then we will have a Summer of Hope. Then a Fall of Failure. Then another, long AI Winter.
  - Razengan 10y ago
    Sounds like VR hype through the ages..
- walrus 10y ago
  I've been informally A/B testing the terms machine learning, artificial intelligence, and computational statistics: - Machine learning: "Oh, neat, what are you working on?" - Artificial intelligence: "What do you think about the singularity?" or [rolls eyes] - Computational statistics: "That's nice. So, how was your weekend?"
- lottin 10y ago
  Agreed, FI -for fake intelligence- would be more accurate :)
  - nostrademons 10y ago
    I think AI is accurate, but it's actually short for "aggregated intelligence". Most AI algorithms can't actually generate "intelligence" as we know it. Rather, they aggregate the intelligence of the humans who contributed to their training data, and then generalize it to situations where those humans are not present. If the humans are stupid (as we saw with Microsoft's Tay chatbot), the AI is going to be pretty stupid as well. If the humans are racist, the AI is going to be racist as well.
graycat 10y ago
From all I can see, nearly all the present AI boils down to one word -- hype. From what is really going on, nearly all of it looks like (1) in some cases a lot of new data, (2) some new, faster processor hardware, e.g., based on graphical processor units although the x86 processors are astoundingly fast anyway, able to manipulate the new data, (3) for what manipulations to do on the data, some tweaks of some of the work of L. Breiman and his CART -- Classification and Regression Trees, (4) fitting with S-shaped (neural) sigmoid functions, and (5) the radar, etc. engineering of autonomous vehicles. E.g., the neural networks might be able to simulate the operation of a neuron in a worm. What I don't see is (A) much progress in better methods for how to manipulate the data, that is, the basic applied math and (B) progress in working with concepts and causality -- in the history of science, progress with concepts and causality did well where the new methods would need Nevada full of disk drives of data. E.g., space flight navigation is based, first, on Newton's law of gravity and second law of motion, not on fitting massive of data via deep learning. Uh, when the AI people use classic regression analysis as in Draper and Smith, etc. and the IBM Scientific Subroutine Package, SPSS, SAS, R, etc. to find some regression coefficients, they claim that their machine learned the coefficients. Gee, I didn't see that in, say, C. Radhakrishna Rao, Linear Statistical Inference and Its Applications: Second Edition, ISBN 0-471-70823-2, John Wiley and Sons, New York, 1967. or Breiman's CART. Again, the rest I see looks like hype. E.g., it appears that there is a basic, clever, publicity, hype idea: Whenever do some technical work, give it a catchy name. Then just use the name in the hype and ignore what is really going on in any math or science. E.g., a while back I published some work in statistical hypothesis testing that is both multi-dimensional and distribution-free. The intended use was for high quality hypothesis testing of zero day problems in computer networks and server farms. Alas, I neglected to give the work a catchy name! The OP seemed surprised that a big, famous company might say things where they know better. Why not? Just assume that they are trying to sell something to some people with money. Similarly for the news media: They want eyeballs for the ad revenue. That the newsies are willing to write junk to get eyeballs goes back at least to Jefferson's remarks as in http://press-pubs.uchicago.edu/founders/documents/amendI_speechs29.html http://press-pubs.uchicago.edu/founders/documents/amendI_spe... and are not nearly new. We have long had a good filter to apply to the writing of the newsies: Does the writing meet common high school term paper writing standards for solid references and primary sources? Rarely is the answer yes. My view of the printed news is that it can't compete with Charmin, not even with cheap, house-brand paper towels. For the electronic versions, they are not useful even as fire starter, shredding for cat litter, or wrapping dead fish heads -- that is, are useless. So, don't read them. And don't debunk them, either -- debunking wastes your time and is something the newsies long since have ignored. The newsies have no shame. Ignore the newsies. They ignore the debunking efforts. My startup manipulates some data, and how is from some applied math I derived. From what I've seen of AI, my work would qualify as quite good and innovative AI -- besides the work is solid theorems and proofs. Still, I see no good reason to give my work a catchy name or call it AI. E.g., I'm not trying to fool anyone. Or, why would I want to associate my good work with a lot of hype to fool people?
Fricken 10y ago
Welcome to the club. Now you know how Economists, healthcare professionals, skateboarders, basket weavers and anybody else whose domain knowledge runs deeper than the average joe's feels whenever their area of technical expertise becomes the subject du jour for the public at large.
- rickdg 10y ago
  Yeah, but my kid knows cyber.
- deleted 10y ago
  [deleted]
- iagovar 10y ago
  This. Everyone has the same problem. And it even gets worse in the Internet, where people just pretend to know things that they don't.
  - Cthulhu_ 10y ago
    Well OTOH, in the land of the blind, one-eye is king - this goes for a lot of subjects. If you can give a general introduction to AI or the latest update, you can write for thousands of online outlets, each of which attracts some views and therefore money. Simple economics. Volume pays more than quality.
    - eli_gottlieb 10y ago
      >If you can give a general introduction to AI or the latest update, you can write for thousands of online outlets, each of which attracts some views and therefore money. Oh really? Where?
- zackchase 10y ago
  As someone with an economics background (BA), and medical research career (concurrent with ML), I can say (subjectively), that this feels different.
didibus 10y ago
Sounds like only a primer, I couldn't find any glimpse at what the problem was though?
- nfd 10y ago
  It's a series of articles the author is starting. Check back soon.
  - ndh2 10y ago
    Um, no. At this point it's some PhD candidate claiming to start a series of blog posts. Do you know how many blog posts there are claiming to have a second part? Either do something or don't. Don't waste other peoples time publishing your grandiose plans. If you want accountability, tell people you actually know, not the internet. Not so much his fault really, but I'm a bit disappointed that this got upvoted so much.
- Safety1stClyde 10y ago
  I only read the first three paragraphs and decided it was probably yet more self-indulgent rambling on the interwebs, came here to read the comments and find out if there was anything interesting here. Apparently not.
ExactoKnight 10y ago
The AI and Singularity hype irks me, because I'm genuinely in agreement with Peter Thiel's argument that technological progress is actually decelerating relative to how it was moving 60 years ago once you look beyond the advancements we have experienced in information technology and finance.
- Banthum 10y ago
  True that. 1880-1950 (70 years) took us from train-and-telegraph to jet-and-atom bomb. Horse and carriage was the top-tier tech for personal transportation in 1880, and they were just starting to understand that diseases are often caused by these little blobby creatures called germs. 1950-2020 (70 years) will take us much less distance. Almost everything we're developing seems to be about information processing. If you look at the technologies that actually do things in the physical world, it seems like almost nothing has changed since the 60's. Cars, trains, bridges, rockets, sewers... all more or less the same.
  - uwiiuvvwu 10y ago
    compared to what though ? are we assuming a linear rate of development ? in evolution organisms change gradually with occasional bursts, and the same seems to be true of human tech evolution. There are periods of stagnation with tiny increments or even regress in places, then there are rapid bursts of unpredictable change, often enabled by information from one area reaching another previously unrelated one.
    - ExactoKnight 10y ago
      Peter Thiel has made some other interesting observations: - that our language about the ‘developed' vs ‘developing' world is excessively bullish about globalization while implicitly pessimistic about technology. - that government has changed from thinking that progress can be achieved via planning, into thinking that it's more just there to watch random forces & statistics evolve the world. This change in mindset away from planning for innovation has made it impossible to achieve grandiose mission like the Apollo space missions. As a result if there is going to be a government role in getting innovation started, people have to philosophically believe again that it’s possible to plan. - that environmentalism has induced a deep skepticism about anything involving the manipulation of nature or material objects in the real world. This skepticism explains why computer tech has been able to advance so much but not physical technology like transportation. - that peer review and grant approval processes are too political, science has suffered because it is hard to find scientists who excel at both science and politics. - that a shift from manufacturing to non-tradeable services has led to a political class (such as lawyers) that is weirdly immune to globalization and mostly oblivious to it.
TuringNYC 10y ago
Since we are on the topic, how do the big firms (Google, Facebook, etc) view Singularity University? Is it considered positive, neutral, or negative? Would appreciate inside perspectives.
- tim333 10y ago
  Well, Google chipped in $3m and hired Kurzweil so presumably they kinda like it.
- Teodolfo 10y ago
  I'm sure many AI experts at these places view it negatively. These are not monolithic organizations, but massive companies filled with real people with varying opinions.
TuringNYC 10y ago
Here is my annoyance with AI Hype: people seeking extra tailwinds pitch their startups as "ML companies" even with the most tangential usage of ML. It drowns out real ML companies. Most people cannot tell the difference. At a hackathon recently, someone pitched their app as an "ML-driven app" though the only ML in there was some 1-line language translation feature they were consuming off Watson REST services for a tangential feature on their app. Meanwhile, my submission actually used a self-trained CNN on a custom dataset using TensorFlow and changes to start/end layers on the NN. The image classification features were the core of the app and it wasn't something that was just a wrapper over an Off-the-shelf API. We actually tried multiple networks and went thru the trouble of parameterizing everything. At the end, I wonder how many judges actually understood the difference in effort/value to the two attempts at ML.
- AndrewKemendo 10y ago
  Difficulty level 1: The only ML in there was some 1-line language translation feature they were consuming off Watson REST services for a tangential feature on their app Difficulty level 2: Self-trained CNN on a custom dataset using TensorFlow and changes to start/end layers on the NN Difficulty level 3: Custom rolled 12 layer CNN trained with with novel hand labeled data. How many people to you think know the difference between these and the fact that each step is a magnitude or more harder than the last? That's not even getting into trying to apply research grade stuff.
  - wolf84 10y ago
    I got tensorflow to analyze blutooth signals off a wireless controller. talk about dreamland autoaim
    - wolf84 10y ago
      you know, something like thumbs as a correlation
  - erkkie 10y ago
    Why should people be able to tell the difference vs the outcome of those products, unless someone (investors?) is specifically just buying into the AI hype itself? (in which case, this is nothing different from when everything was "social")
not_a_terrorist 10y ago
Took a course with a few classes that touched AI. First thing the prof wrote on the board: "Artificial Intelligence = Human Stupidity" Spent a few hours analysing all aspects of that statement. Was entertaining.
hullsean 10y ago
I like the use of the word "epidemic". I couldn't resist clicking!
ilaksh 10y ago
Most of the people who have a strong machine learning or deep learning background are actually unaware of the large amount of existing research that applies to artificial general intelligence (AGI) because that group is just not mainstream. But there are groups who are combining cutting edge neural network research with AGI and seriously trying to build general intelligence. Researchers who are working on narrow AI tasks and are familiar with this will continue to be incredulous right up to (and possibly beyond) the point where they see a system that seems intelligent to them.
- wiricon 10y ago
  Care to share links to those labs' websites/relevant papers? I'm a deep learning researcher, and I've been noticing this gap that you mentioned between the DL community and what everyone else in AI is doing, and think it might be worthwhile trying to bridge that gap.
  - ilaksh 10y ago
    Google for publications by Deep Mind, Ogma, Good AI, Open AI, Numenta, OpenCog, 'Towards Deep Developmental Learning', projects related to new DARPA program 'L2M'. Also search for projects labeled AGI.
    - claytonjy 10y ago
      I'm unfamiliar with most of those, but aren't Deep Mind and Open AI pretty standard sources of knowledge in the DL community these days? I say this as a practitioner who has read some things from both, and had the impression that while cutting-edge, they are both "traditional" DL-focused institutions at the moment, not so concerned with AGI.
- CuriouslyC 10y ago
  Honestly I think trying to top down design general intelligence is a mistake. The only model of intelligence we have resulted from the gradual agglomeration and integration of narrow intelligences. Not only is it a demonstrated path, but at every point along the way it is useful. Nature has given us a great roadmap, all we have to do is follow it.
uwu 10y ago
what's with the claustrophobia-inducing thick black border around the page
- somestag 10y ago
  That's interesting; I didn't even notice it. But the border doesn't scale with window size, and I tend to keep my windows large on an already large monitor, so the relative effect was small and (subjectively) even pleasant. I can't get too mad at the design choice, but maybe it should scale in some way to window size.
jacquesm 10y ago
A lot of start-ups are hyping themselves as deep-learning or something close to that in order to make themselves appear 'hot'. Recently I looked at a company that had absolutely nothing to do with deep-learning or even any kind of machine learning whatsoever and that still managed to sprinkle the various buzz-words with great regularity throughout their investor targeted docs. What I don't get about this behavior is this: It won't work, and in fact is a net negative, so why do it in the first place? Investing is a trust thing, if you break trust before you even get to talk to your potential investor there is no way you will raise money from them.
- stult 10y ago
  Sometimes it's just desperation. Sometimes it just actually works. You'd be amazed how much easier it is to pitch buzz word heavy software to non-technical people. Presumably most serious investors aren't that easily fooled, but surely some are. And some are simply cynically acknowledging that a company which exploits the zeitgeist for marketing purposes is more likely to succeed with its non-technical customer base.
- thearn4 10y ago
  What were the technical buzzwords that companies used to signal hotness in the industry before the ML hype train (startup or not)? I know on the process & management side for large organizations, there's been a revolving door of Lean/Agile/6 Sigma/ISO 9000, each with their own set of certifications, colored belts, and army of advisors/consultants. I like the idea of always being retrospective and asking what can be improved, but it's made me a bit cynical seeing management chase fads based on whatever a vendor tells them.
  - jacquesm 10y ago
    Web 2.0, Semantic web, cloud, async, big data... you could keep this up for quite a while.
    - cr0sh 10y ago
      I tend to think this whole "hype marketing" thing has been going on for a very long time; I can't quantify how long. I do know that if you look at various technology marketing around the decade after the release of Capek's RUR (1920) - almost everything that was remotely mechanical or automatic or electronic was referred to as a "robot". So it has been going on at least that long, and I suspect longer.
psyc 10y ago
IMO, the practical sorts, such as this author, who want everybody's vision for AI to be as narrow as their present-year work is, suffer from the reverse affliction to what they think futurists suffer from. I will call this affliction "rationality-signaling".
c0ntrarian 10y ago
This is a very offensive epithet and I demand you rescind it immediately. Just because you have your own language does not mean you can make up hurtful words in English.
- catoc 10y ago
  We have the same word in Dutch, 'vakidioot', roughly pronounced as 'fuckidiot'. We will rescind it immediately for you :-)
- prance 10y ago
  In German we have "Fachidiot", which is not pronounced like the Dutch 'vakidioot' at all, but many English speakers would do so nevertheless. You're free to rescind your own abomination of that word :D
- arca_vorago 10y ago
  Did you forget a /s?
- dang 10y ago
  Please don't. We detached this subthread from https://news.ycombinator.com/item?id=13975970 https://news.ycombinator.com/item?id=13975970 and marked it off-topic.
bischofs 10y ago
Stop calling it "Machine Learning" and "Neural Networks" if you don't want the attention. Do we refer to code or computers as "Machines?". That kind of language is just begging for skynet references. Any sort of elaborate processing network could be called "Neural" or maybe even a fancy linked-list . Something more reasonable like a learning network would keep the sensationalism down. Im sure we can come up with better names...
- justin66 10y ago
  > Do we refer to code or computers as "Machines?" I do, sometimes. I don't know where I picked up the habit, to be honest, but it might date back to the eighties or nineties. (I know I'm not the only one)
  - bischofs 10y ago
    Fair enough, but take anything in computers and replace it with "Machines" and it illustrates the point. ram could be called "Machine memory" or a network could be called a "Machine communication matrix" or in the reverse "Terminator 3: rise of the computers"
    - justin66 10y ago
      Yeah, I won't try to defend the "machine learning" moniker, except to point out that it's not nearly as dorky as "deep learning."
- cpburns2009 10y ago
  With the prevalence of VMs (virtual machines), I don't think it's a stretch to call physical computers "machines". Granted, I usually hear the term "computer" or "box" used instead. Besides that moot point, I completely agree with you.
- mljoe 10y ago
  How about "statistical inference"? This is not an uncommon term for ML techniques in the statistical community.
deleted 10y ago
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akyu 10y ago
I'm not sure which I find more annoying; the AI hypers, or the who people who insist that machine learning is "basically just matrix multiplication". As a researcher none of it makes a difference to me either way.
- sddfd 10y ago
  I think part of the excitement is justified: computers can translate between speech and text, and text of different languages. On the other hand neural networks are most likely just one tool in a larger toolset that will be needed for general AI.
  - 1_2__3 10y ago
    That's basically like saying that horses and buggies will just be tools in a larger toolset needed for space travel. What generalized AI will look like bears little or no resemblance to what we're doing today.
  - Retric 10y ago
    Computers don't really translate languages. They take language sample from A into something close to B, and people translate something close to B into language B. I don't mean this in some abstract philosophical argument, rather as an outgrowth of how they operate. Modern methods are much better than this, but even the most simple mechanical translation of each word in language A into one and only one word in language B allows people to get some value. But, improving without understanding has some inherent limitations. Humans run into similar problems when they try and translate complex source material they don't understand. Generally this is not a major problem, but it can be.
- RodericDay 10y ago
  I find the AI hypers way more annoying.
Chris2048 10y ago
Author says (in comments) in support of Singularity being nonsense: > Technology is not a quantity Er, yeah, "technology" is a complicated thing, but it can be considered a quantity. Computing power grows, so does automation and material knowledge. Dismissing a useful concept as religion because it isn't mathematically rigorous isn't very objective.
deleted 10y ago
[deleted]
throw2016 10y ago
The amount of glee at unemployment and disempowerment expressed during most AI discussions here is truly disturbing, especially given the nascent stage of things. The irony of laments about HIB and outsourcing then sit starkly. It reveals not a genuine excitement about technology progress and a better world but a darker underbelly of a self obsessed and insular tech community composed seemingly of closet tinpots itching to climb up the food chain. How can this lead to any positive outcome? Same old, only replaced by a new group. Technology can leap but humans mindsets remain stagnant around power and greed.
tim333 10y ago
>see the recent Maureen Dowd piece on Elon Musk, Demis Hassabis, and AI Armaggedon in Vanity Fair for a masterclass in low-quality, opportunistic journalism I finally read through most of the 8000+ words of it and it's not that bad - mostly a bunch of interview quotes from Musk, Kurzweil et al and some of it's a bit sceptical eg: >When I mentioned to Andrew Ng that I was going to be talking to Kurzweil, he rolled his eyes. “Whenever I read Kurzweil’s Singularity, my eyes just naturally do that,” he said.

337 points by aaronyy 10y ago

zackchase 10y ago

Some strident Singularitarians joined the comment thread.

kordless 10y ago
I'm from the camp the singularity already happened! ;)
- archgoon 10y ago
  Shh! Quiet! Or I'll feed you to the Basilisk.
- colordrops 10y ago
  It's always happening.
- Banthum 10y ago
  Probably happened when proto-people developed complex grunting noises. Or maybe before - with grasping digits? Hard to tell.
- jodrellblank 10y ago
  I'm from the camp the singularity is a continuous process. When you travel away from the Sun, the light from it gets dimmer and dimmer and dimmer, until it becomes single photons appearing with more and more delays but on average energy of 'dimmer' light. Fly towards the Sun and there isn't a sudden cutoff point where it goes from dark to bright, or bright to incandescent, it's a continual increase. Same with life, lots of people born, lots of intensity around birth and infant children and parents and education, intensity diminishes with age as people spread out and dissipate, everyone's looking back in at the source of new life while getting further and further from it and more and more separated from each other and lower energy levels and less and less 'happening'. Singularity? Moving towards the intensity with technological development and more intricate, faster, and sheerly more connectivity all over, more encoding of ideas into information patterns. Unless you want to imagine it like flying towards the Sun becoming falling towards the Sun, becoming a specific point where everyone burns up and dies. :/
  - beaconstudios 10y ago
    the whole premise of a singularity is that we will hit a point of exponential technological growth, extrapolated from the accelerating pace of technological development over human history and usually based on the idea that we'll make a self-iterating AI which will lead to runaway intelligence. The "singularity" specifically is intended as a tipping-point where the acceleration of technology becomes faster than human capability (i.e. the approaching-vertical line on an exponential curve).
    - arca_vorago 10y ago
      Yep, this is why the singularity is a zero-sum game... I expect many entities to vie for the title, but the first one there will subsequently dominate... which is why it's my intention to program my conciousness into my own AI which seeks to become the singularity and therefor my digial conciousness version will become the ultimate god of the universe. mad scientist laugh
      - beaconstudios 10y ago
        race you to the pseudoreligious finish line!
  - kordless 10y ago
    > becoming a specific point where everyone burns up and dies Some of us seek this in the attainment of Nirvana.
Teodolfo 10y ago
The singularity cult is real. The geek rapture will occur when they blog about someone else making God in a Box hard enough to drown out the normal charlatans. Please fund their blogging, it is the most impactful way you can spend your money.

unityByFreedom 10y ago

Someone tell Musk. Oh wait, he profits from such misinformation. Nevermind.

prvnsmpth 10y ago
Care to elaborate?
- acover 10y ago
  One way he profits is in the expectations of self driving cars. If people expect it in 3 years and it to be 10x better than humans [to quote musk] then there is huge value in any company that can provide it. Tesla has a market cap larger than Ford. Tesla also has been on the edge of bankruptcy every couple years and recently raised $1 billion in capital.
  - graycat 10y ago
    Sounds like a good short selling opportunity.
    - unityByFreedom 10y ago
      Hard to time that kind of thing. Not worth it when you risk losing your shirt. You can lose an infinite amount of money shorting, whereas going long you might only lose all of what you put in.
      - jfoutz 10y ago
        don't options solve this? Buy a put at 50, watch it fall, then exercise. Doesn't work out, and you're only out the premium.
        cglouch 10y ago
        Options solve it in the sense that you limit your downside, but you can still very well lose your premium. Even if you're 100% convinced that $TSLA is overvalued, markets can remain irrational longer than you can remain solvent, and your puts may very well expire worthless.

apsec112 10y ago

I'm very interested in this topic, but I'd hold off on discussing until the other posts are out. The current post is largely just a summary of what future posts will say, and doesn't cover much by itself.

charles-salvia 10y ago

Yeah, terms like "machine learning" and "AI" have basically become buzz words which, to most laymen, probably encourage the idea that we're on the cusp of creating Data from Star Trek. Unfortunately, the reality is that.... sorry... it's mostly just statistical algorithms based around regression and intermediate calculus. State-of-the-art "deep" neural networks are not really anything like the absurdly parallel, asynchronous biological networks that power our neo-cortex - rather, they're basically an application of matrix multiplication designed to "learn" a function by iteratively minimizing an error value using gradient descent. It's still very unclear what, if anything, this algorithm has in common with how a human brain actually operates. It turns out that these kind of statistical algorithms can work pretty well when you have petabytes of data to learn from. But we're still not anywhere near the unsupervised learning capabilities demonstrated by a human infant.

eli_gottlieb 10y ago
> It's still very unclear what, if anything, this algorithm has in common with how a human brain actually operates. Not very much at all. Most psychological evidence shows that human beings seem to operate off composable, hierarchical generative models and probabilistic inference. Deep neural networks are basically just huge continuous circuit approximators.
- akyu 10y ago
  >composable, hierarchical generative models and probabilistic inference. Deep neural networks are basically just huge continuous circuit approximators. These two things are not mutually exclusive.
  - eli_gottlieb 10y ago
    What sort of neural network implements human-style learning and inference?
    - shahbaby 10y ago

bluetwo 10y ago

Remember those AT&T commercials "You Will..."? They won a bunch of awards for them but most of the technologies, if they came to be, were brought to you by people other than AT&T. Same thing with the next steps in AI. They might happen, but they aren't going to come from the companies who currently have large marketing departments looking for something to hype.

tempodox 10y ago

The epidemic starts with calling it “AI”.

zackchase 10y ago
I generally agree with this. I used machine learning almost exclusively in the article. Yet "AI misinformation" seems more appropriate in the title since the misinformation, generally, is in reference to "artificial intelligence".
graycat 10y ago
Yup, we've had several AI winters. Now we have an AI Spring of Hype. Then we will have a Summer of Hope. Then a Fall of Failure. Then another, long AI Winter.
- Razengan 10y ago
  Sounds like VR hype through the ages..
walrus 10y ago
I've been informally A/B testing the terms machine learning, artificial intelligence, and computational statistics: - Machine learning: "Oh, neat, what are you working on?" - Artificial intelligence: "What do you think about the singularity?" or [rolls eyes] - Computational statistics: "That's nice. So, how was your weekend?"
lottin 10y ago
Agreed, FI -for fake intelligence- would be more accurate :)
- nostrademons 10y ago
  I think AI is accurate, but it's actually short for "aggregated intelligence". Most AI algorithms can't actually generate "intelligence" as we know it. Rather, they aggregate the intelligence of the humans who contributed to their training data, and then generalize it to situations where those humans are not present. If the humans are stupid (as we saw with Microsoft's Tay chatbot), the AI is going to be pretty stupid as well. If the humans are racist, the AI is going to be racist as well.

graycat 10y ago

From all I can see, nearly all the present AI boils down to one word -- hype. From what is really going on, nearly all of it looks like (1) in some cases a lot of new data, (2) some new, faster processor hardware, e.g., based on graphical processor units although the x86 processors are astoundingly fast anyway, able to manipulate the new data, (3) for what manipulations to do on the data, some tweaks of some of the work of L. Breiman and his CART -- Classification and Regression Trees, (4) fitting with S-shaped (neural) sigmoid functions, and (5) the radar, etc. engineering of autonomous vehicles. E.g., the neural networks might be able to simulate the operation of a neuron in a worm. What I don't see is (A) much progress in better methods for how to manipulate the data, that is, the basic applied math and (B) progress in working with concepts and causality -- in the history of science, progress with concepts and causality did well where the new methods would need Nevada full of disk drives of data. E.g., space flight navigation is based, first, on Newton's law of gravity and second law of motion, not on fitting massive of data via deep learning. Uh, when the AI people use classic regression analysis as in Draper and Smith, etc. and the IBM Scientific Subroutine Package, SPSS, SAS, R, etc. to find some regression coefficients, they claim that their machine learned the coefficients. Gee, I didn't see that in, say, C. Radhakrishna Rao, Linear Statistical Inference and Its Applications: Second Edition, ISBN 0-471-70823-2, John Wiley and Sons, New York, 1967. or Breiman's CART. Again, the rest I see looks like hype. E.g., it appears that there is a basic, clever, publicity, hype idea: Whenever do some technical work, give it a catchy name. Then just use the name in the hype and ignore what is really going on in any math or science. E.g., a while back I published some work in statistical hypothesis testing that is both multi-dimensional and distribution-free. The intended use was for high quality hypothesis testing of zero day problems in computer networks and server farms. Alas, I neglected to give the work a catchy name! The OP seemed surprised that a big, famous company might say things where they know better. Why not? Just assume that they are trying to sell something to some people with money. Similarly for the news media: They want eyeballs for the ad revenue. That the newsies are willing to write junk to get eyeballs goes back at least to Jefferson's remarks as in http://press-pubs.uchicago.edu/founders/documents/amendI_speechs29.html http://press-pubs.uchicago.edu/founders/documents/amendI_spe... and are not nearly new. We have long had a good filter to apply to the writing of the newsies: Does the writing meet common high school term paper writing standards for solid references and primary sources? Rarely is the answer yes. My view of the printed news is that it can't compete with Charmin, not even with cheap, house-brand paper towels. For the electronic versions, they are not useful even as fire starter, shredding for cat litter, or wrapping dead fish heads -- that is, are useless. So, don't read them. And don't debunk them, either -- debunking wastes your time and is something the newsies long since have ignored. The newsies have no shame. Ignore the newsies. They ignore the debunking efforts. My startup manipulates some data, and how is from some applied math I derived. From what I've seen of AI, my work would qualify as quite good and innovative AI -- besides the work is solid theorems and proofs. Still, I see no good reason to give my work a catchy name or call it AI. E.g., I'm not trying to fool anyone. Or, why would I want to associate my good work with a lot of hype to fool people?

Fricken 10y ago

Welcome to the club. Now you know how Economists, healthcare professionals, skateboarders, basket weavers and anybody else whose domain knowledge runs deeper than the average joe's feels whenever their area of technical expertise becomes the subject du jour for the public at large.

rickdg 10y ago
Yeah, but my kid knows cyber.
deleted 10y ago
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iagovar 10y ago
This. Everyone has the same problem. And it even gets worse in the Internet, where people just pretend to know things that they don't.
- Cthulhu_ 10y ago
  Well OTOH, in the land of the blind, one-eye is king - this goes for a lot of subjects. If you can give a general introduction to AI or the latest update, you can write for thousands of online outlets, each of which attracts some views and therefore money. Simple economics. Volume pays more than quality.
  - eli_gottlieb 10y ago
    >If you can give a general introduction to AI or the latest update, you can write for thousands of online outlets, each of which attracts some views and therefore money. Oh really? Where?
zackchase 10y ago
As someone with an economics background (BA), and medical research career (concurrent with ML), I can say (subjectively), that this feels different.

didibus 10y ago

Sounds like only a primer, I couldn't find any glimpse at what the problem was though?

nfd 10y ago
It's a series of articles the author is starting. Check back soon.
- ndh2 10y ago
  Um, no. At this point it's some PhD candidate claiming to start a series of blog posts. Do you know how many blog posts there are claiming to have a second part? Either do something or don't. Don't waste other peoples time publishing your grandiose plans. If you want accountability, tell people you actually know, not the internet. Not so much his fault really, but I'm a bit disappointed that this got upvoted so much.
Safety1stClyde 10y ago
I only read the first three paragraphs and decided it was probably yet more self-indulgent rambling on the interwebs, came here to read the comments and find out if there was anything interesting here. Apparently not.

ExactoKnight 10y ago

The AI and Singularity hype irks me, because I'm genuinely in agreement with Peter Thiel's argument that technological progress is actually decelerating relative to how it was moving 60 years ago once you look beyond the advancements we have experienced in information technology and finance.

Banthum 10y ago
True that. 1880-1950 (70 years) took us from train-and-telegraph to jet-and-atom bomb. Horse and carriage was the top-tier tech for personal transportation in 1880, and they were just starting to understand that diseases are often caused by these little blobby creatures called germs. 1950-2020 (70 years) will take us much less distance. Almost everything we're developing seems to be about information processing. If you look at the technologies that actually do things in the physical world, it seems like almost nothing has changed since the 60's. Cars, trains, bridges, rockets, sewers... all more or less the same.
- uwiiuvvwu 10y ago
  compared to what though ? are we assuming a linear rate of development ? in evolution organisms change gradually with occasional bursts, and the same seems to be true of human tech evolution. There are periods of stagnation with tiny increments or even regress in places, then there are rapid bursts of unpredictable change, often enabled by information from one area reaching another previously unrelated one.
  - ExactoKnight 10y ago
    Peter Thiel has made some other interesting observations: - that our language about the ‘developed' vs ‘developing' world is excessively bullish about globalization while implicitly pessimistic about technology. - that government has changed from thinking that progress can be achieved via planning, into thinking that it's more just there to watch random forces & statistics evolve the world. This change in mindset away from planning for innovation has made it impossible to achieve grandiose mission like the Apollo space missions. As a result if there is going to be a government role in getting innovation started, people have to philosophically believe again that it’s possible to plan. - that environmentalism has induced a deep skepticism about anything involving the manipulation of nature or material objects in the real world. This skepticism explains why computer tech has been able to advance so much but not physical technology like transportation. - that peer review and grant approval processes are too political, science has suffered because it is hard to find scientists who excel at both science and politics. - that a shift from manufacturing to non-tradeable services has led to a political class (such as lawyers) that is weirdly immune to globalization and mostly oblivious to it.

TuringNYC 10y ago

Since we are on the topic, how do the big firms (Google, Facebook, etc) view Singularity University? Is it considered positive, neutral, or negative? Would appreciate inside perspectives.

tim333 10y ago
Well, Google chipped in $3m and hired Kurzweil so presumably they kinda like it.
Teodolfo 10y ago
I'm sure many AI experts at these places view it negatively. These are not monolithic organizations, but massive companies filled with real people with varying opinions.

TuringNYC 10y ago

Here is my annoyance with AI Hype: people seeking extra tailwinds pitch their startups as "ML companies" even with the most tangential usage of ML. It drowns out real ML companies. Most people cannot tell the difference. At a hackathon recently, someone pitched their app as an "ML-driven app" though the only ML in there was some 1-line language translation feature they were consuming off Watson REST services for a tangential feature on their app. Meanwhile, my submission actually used a self-trained CNN on a custom dataset using TensorFlow and changes to start/end layers on the NN. The image classification features were the core of the app and it wasn't something that was just a wrapper over an Off-the-shelf API. We actually tried multiple networks and went thru the trouble of parameterizing everything. At the end, I wonder how many judges actually understood the difference in effort/value to the two attempts at ML.

AndrewKemendo 10y ago
Difficulty level 1: The only ML in there was some 1-line language translation feature they were consuming off Watson REST services for a tangential feature on their app Difficulty level 2: Self-trained CNN on a custom dataset using TensorFlow and changes to start/end layers on the NN Difficulty level 3: Custom rolled 12 layer CNN trained with with novel hand labeled data. How many people to you think know the difference between these and the fact that each step is a magnitude or more harder than the last? That's not even getting into trying to apply research grade stuff.
- wolf84 10y ago
  I got tensorflow to analyze blutooth signals off a wireless controller. talk about dreamland autoaim
  - wolf84 10y ago
    you know, something like thumbs as a correlation
- erkkie 10y ago
  Why should people be able to tell the difference vs the outcome of those products, unless someone (investors?) is specifically just buying into the AI hype itself? (in which case, this is nothing different from when everything was "social")

not_a_terrorist 10y ago

Took a course with a few classes that touched AI. First thing the prof wrote on the board: "Artificial Intelligence = Human Stupidity" Spent a few hours analysing all aspects of that statement. Was entertaining.

hullsean 10y ago

I like the use of the word "epidemic". I couldn't resist clicking!

ilaksh 10y ago

Most of the people who have a strong machine learning or deep learning background are actually unaware of the large amount of existing research that applies to artificial general intelligence (AGI) because that group is just not mainstream. But there are groups who are combining cutting edge neural network research with AGI and seriously trying to build general intelligence. Researchers who are working on narrow AI tasks and are familiar with this will continue to be incredulous right up to (and possibly beyond) the point where they see a system that seems intelligent to them.

wiricon 10y ago
Care to share links to those labs' websites/relevant papers? I'm a deep learning researcher, and I've been noticing this gap that you mentioned between the DL community and what everyone else in AI is doing, and think it might be worthwhile trying to bridge that gap.
- ilaksh 10y ago
  Google for publications by Deep Mind, Ogma, Good AI, Open AI, Numenta, OpenCog, 'Towards Deep Developmental Learning', projects related to new DARPA program 'L2M'. Also search for projects labeled AGI.
  - claytonjy 10y ago
    I'm unfamiliar with most of those, but aren't Deep Mind and Open AI pretty standard sources of knowledge in the DL community these days? I say this as a practitioner who has read some things from both, and had the impression that while cutting-edge, they are both "traditional" DL-focused institutions at the moment, not so concerned with AGI.
CuriouslyC 10y ago
Honestly I think trying to top down design general intelligence is a mistake. The only model of intelligence we have resulted from the gradual agglomeration and integration of narrow intelligences. Not only is it a demonstrated path, but at every point along the way it is useful. Nature has given us a great roadmap, all we have to do is follow it.

uwu 10y ago

what's with the claustrophobia-inducing thick black border around the page

somestag 10y ago
That's interesting; I didn't even notice it. But the border doesn't scale with window size, and I tend to keep my windows large on an already large monitor, so the relative effect was small and (subjectively) even pleasant. I can't get too mad at the design choice, but maybe it should scale in some way to window size.

jacquesm 10y ago

A lot of start-ups are hyping themselves as deep-learning or something close to that in order to make themselves appear 'hot'. Recently I looked at a company that had absolutely nothing to do with deep-learning or even any kind of machine learning whatsoever and that still managed to sprinkle the various buzz-words with great regularity throughout their investor targeted docs. What I don't get about this behavior is this: It won't work, and in fact is a net negative, so why do it in the first place? Investing is a trust thing, if you break trust before you even get to talk to your potential investor there is no way you will raise money from them.

stult 10y ago
Sometimes it's just desperation. Sometimes it just actually works. You'd be amazed how much easier it is to pitch buzz word heavy software to non-technical people. Presumably most serious investors aren't that easily fooled, but surely some are. And some are simply cynically acknowledging that a company which exploits the zeitgeist for marketing purposes is more likely to succeed with its non-technical customer base.
thearn4 10y ago
What were the technical buzzwords that companies used to signal hotness in the industry before the ML hype train (startup or not)? I know on the process & management side for large organizations, there's been a revolving door of Lean/Agile/6 Sigma/ISO 9000, each with their own set of certifications, colored belts, and army of advisors/consultants. I like the idea of always being retrospective and asking what can be improved, but it's made me a bit cynical seeing management chase fads based on whatever a vendor tells them.
- jacquesm 10y ago
  Web 2.0, Semantic web, cloud, async, big data... you could keep this up for quite a while.
  - cr0sh 10y ago
    I tend to think this whole "hype marketing" thing has been going on for a very long time; I can't quantify how long. I do know that if you look at various technology marketing around the decade after the release of Capek's RUR (1920) - almost everything that was remotely mechanical or automatic or electronic was referred to as a "robot". So it has been going on at least that long, and I suspect longer.

psyc 10y ago

IMO, the practical sorts, such as this author, who want everybody's vision for AI to be as narrow as their present-year work is, suffer from the reverse affliction to what they think futurists suffer from. I will call this affliction "rationality-signaling".

c0ntrarian 10y ago

This is a very offensive epithet and I demand you rescind it immediately. Just because you have your own language does not mean you can make up hurtful words in English.

catoc 10y ago
We have the same word in Dutch, 'vakidioot', roughly pronounced as 'fuckidiot'. We will rescind it immediately for you :-)
prance 10y ago
In German we have "Fachidiot", which is not pronounced like the Dutch 'vakidioot' at all, but many English speakers would do so nevertheless. You're free to rescind your own abomination of that word :D
arca_vorago 10y ago
Did you forget a /s?
dang 10y ago
Please don't. We detached this subthread from https://news.ycombinator.com/item?id=13975970 https://news.ycombinator.com/item?id=13975970 and marked it off-topic.

bischofs 10y ago

Stop calling it "Machine Learning" and "Neural Networks" if you don't want the attention. Do we refer to code or computers as "Machines?". That kind of language is just begging for skynet references. Any sort of elaborate processing network could be called "Neural" or maybe even a fancy linked-list . Something more reasonable like a learning network would keep the sensationalism down. Im sure we can come up with better names...

justin66 10y ago
> Do we refer to code or computers as "Machines?" I do, sometimes. I don't know where I picked up the habit, to be honest, but it might date back to the eighties or nineties. (I know I'm not the only one)
- bischofs 10y ago
  Fair enough, but take anything in computers and replace it with "Machines" and it illustrates the point. ram could be called "Machine memory" or a network could be called a "Machine communication matrix" or in the reverse "Terminator 3: rise of the computers"
  - justin66 10y ago
    Yeah, I won't try to defend the "machine learning" moniker, except to point out that it's not nearly as dorky as "deep learning."
cpburns2009 10y ago
With the prevalence of VMs (virtual machines), I don't think it's a stretch to call physical computers "machines". Granted, I usually hear the term "computer" or "box" used instead. Besides that moot point, I completely agree with you.
mljoe 10y ago
How about "statistical inference"? This is not an uncommon term for ML techniques in the statistical community.

deleted 10y ago

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akyu 10y ago

I'm not sure which I find more annoying; the AI hypers, or the who people who insist that machine learning is "basically just matrix multiplication". As a researcher none of it makes a difference to me either way.

sddfd 10y ago
I think part of the excitement is justified: computers can translate between speech and text, and text of different languages. On the other hand neural networks are most likely just one tool in a larger toolset that will be needed for general AI.
- 1_2__3 10y ago
  That's basically like saying that horses and buggies will just be tools in a larger toolset needed for space travel. What generalized AI will look like bears little or no resemblance to what we're doing today.
- Retric 10y ago
  Computers don't really translate languages. They take language sample from A into something close to B, and people translate something close to B into language B. I don't mean this in some abstract philosophical argument, rather as an outgrowth of how they operate. Modern methods are much better than this, but even the most simple mechanical translation of each word in language A into one and only one word in language B allows people to get some value. But, improving without understanding has some inherent limitations. Humans run into similar problems when they try and translate complex source material they don't understand. Generally this is not a major problem, but it can be.
RodericDay 10y ago
I find the AI hypers way more annoying.

Chris2048 10y ago

Author says (in comments) in support of Singularity being nonsense: > Technology is not a quantity Er, yeah, "technology" is a complicated thing, but it can be considered a quantity. Computing power grows, so does automation and material knowledge. Dismissing a useful concept as religion because it isn't mathematically rigorous isn't very objective.

deleted 10y ago

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throw2016 10y ago

The amount of glee at unemployment and disempowerment expressed during most AI discussions here is truly disturbing, especially given the nascent stage of things. The irony of laments about HIB and outsourcing then sit starkly. It reveals not a genuine excitement about technology progress and a better world but a darker underbelly of a self obsessed and insular tech community composed seemingly of closet tinpots itching to climb up the food chain. How can this lead to any positive outcome? Same old, only replaced by a new group. Technology can leap but humans mindsets remain stagnant around power and greed.

tim333 10y ago

>see the recent Maureen Dowd piece on Elon Musk, Demis Hassabis, and AI Armaggedon in Vanity Fair for a masterclass in low-quality, opportunistic journalism I finally read through most of the 8000+ words of it and it's not that bad - mostly a bunch of interview quotes from Musk, Kurzweil et al and some of it's a bit sceptical eg: >When I mentioned to Andrew Ng that I was going to be talking to Kurzweil, he rolled his eyes. “Whenever I read Kurzweil’s Singularity, my eyes just naturally do that,” he said.