8 ms·

When the bubble bursts

114 points by dstein64 8y ago

olivermarks 8y ago
'We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten...'
jaggederest 8y ago
I think it's interesting that there's a few things you could start thinking about when you see the title. I might be alone but it's feeling a little bubbly to me in a few different areas. ML is certainly one of them.
zamalek 8y ago
A few things, or rather ripples, survived the bubbles. AI crashed in the 1980s - but we eventually created Dragon Speech, handwriting recognition and a few other useful solutions. The DotCom bubble burst, but we wound up with [arguably] useful results in the long run (agile, or whatever comes next, might be the biggest ripple). Even if this bubble bursts, bigger and greater things will arise because of it. With only 2 samples of these bubbles the p-value is miserable, but history has taught us to see these bubbles through. Wisdom is not the sum of success, it is the sum of failure. We need to learn just how far we can push deep learning - within reasonable moral degrees of freedom.
- blueprint 8y ago
  > Wisdom is not the sum of success, it is the sum of failure That doesn't make any sense. Failing is not implicitly useful and (while we are on the topic of morality) must not be held up as a goal.
  - ianai 8y ago
    Failure is not what happened in any of those examples. A failure is several orders of magnitude below a Great Recession or Great Depression.
  - zamalek 8y ago
    > failure [...] morality They were simultaneously different points and part of the same point in my argument. Separately, failure is a good thing - as any CEO would tell you. Together, they are horrific. It's very complicated, which is a far cry from "idiotic" as the article portrays.
    - blueprint 8y ago
      Failure is a good thing? By itself? What a strange fantasy.
  - paulcole 8y ago
    Succeeding isn’t implicitly useful either. Succeeding mustn’t be held up as a goal or you end up with Uber.
    - blueprint 8y ago
      We were talking about wisdom.
  - vertexFarm 8y ago
    Ha. You are in for some rough lessons my friend.
    - blueprint 8y ago
      Go ahead and say what they are if you know them. I doubt you will be able to say anything. Instead of being silent, you should have the courage to admit you don't actually know what you're talking about and don't have much if anything to tell me.
      - blueprint 8y ago
        More downvotes please. The weakness of your argument and the fact all you can do is repress and attempt to censor my reply (because you can't understand it) needs to be made more obvious! Best prevent other people from finding out about what I said and attempt to socially pressure them into not holding such an opinion because then they wouldn't be able to be fooled by you anymore and even you might have to change. And that's just too scary. I can answer every critique you throw at me about this topic. Yet no one here could reply to even one of my responses. You're laughable in your denial, ignorance, and weak-mindedness.
        DanBC 8y ago
        vertexfarm did not downvote you. It's not possible to downvote replies to your own comments.
        blueprint 8y ago
        Yes, I know. That much was already clear by the fact more than one downvote was received. I'm addressing a group of individuals whose way of thinking is so homogeneous they may as well have lost their individual identities.
        deleted 8y ago
        [deleted]
      - 8y ago
  - SuoDuanDao 8y ago
    I would say failure by definition cannot be held up as a goal. The upside of failure is that it teaches more reliable lessons than success, there's no survivorship bias at play when learning from failures like there is with success. Jack Ma's lengthy interview at Davos this year touches on the subject if you'd like to see that perspective defended by someone with authority.
    - blueprint 8y ago
      > I would say failure by definition cannot be held up as a goal. It depends on who is doing it. Maybe you understand what you said, but others have an interest in not understanding it because they have an obstacle in themselves. > The upside of failure is that it teaches more reliable lessons than success, there's no survivorship bias at play when learning from failures like there is with success. I would like to improve your abilities or otherwise open up your wisdom. Any "upside of failure" is by definition a success. Therefore people's statements about success and failure, as if the nature of the result can be captured by a singular datapoint, are self-contradictory, and meaningful only as a reflection of the individual's limitation of understanding. > if you'd like to see that perspective defended by someone with authority. We're talking about wisdom here, so the only authority is a perfectly enlightened being, not an ordinary human being who has knowledge but no way to confirm the degree of exactness of their own ability to make confirmations. No one without enlightenment perceives the causes of why things happen to them. If you want to convince me someone is an authority on how a good and a bad thing happens then I will need to see any proof at all they realize the principle by which the world operates. Otherwise you should realize that's merely their own ideas, of which some percentage may be correct, despite their inability to confirm it.
- ianai 8y ago
  Bubbles (last I checked) don’t have a firm empirical definition. But the ebb and flow that you’re arguing for is very dramatic. Society could have made those discoveries without leaving large swaths of people and places unemployed. Further, anything that impacts the populous negatively makes a bigger, deeper, and longer lasting, negative impact on national wealth than anything a few companies could ever achieve in similar constraints.
  - zamalek 8y ago
    > Society could have made those discoveries without leaving large swaths of people and places unemployed I am currently a proponent of self-driving cars, as I believe that human reflexes are designed to operate at, on average, 6mph. Almost anything could be better than us, at least in theory. Testing the limits of self-driving cars is how we determine what we can't do with them (and asking too much is how we zero-in on the failure point). This has complex moral consequences. Will more people be killed due to failure, or fewer? Thats great if it works out, but horrific if it doesn't. It's incredibly difficult to draw a line given that we don't know what the whole landscape is. This bubble is worsening unemployment. One ripple arising from that is UBI. Another is a positive-sum world. ML is currently successful in medicine. It's not all doom and gloom - we are already reaping long-term benefits.
    - 80x25 8y ago
      > This bubble is worsening unemployment. By what measure?
      - zamalek 8y ago
        By the measure of the parent comment, and, I think globally. It's often best to accommodate an argument when you have more than one way to make your case. If someone believes that unemployment is on the rise, despite the facts that you (specifically) may have, let them win it - because they have seen the same facts and don't care.
    - AstralStorm 8y ago
      Our reflexes are fine at about 100 Hz. That gives up to 2m distance at rival urban speeds before action and drivers shouldn't rely just on reflexes anyway. The problem is not reflexes, the problem is some drivers being dumb and a bunch of others distracted. You could mandate a very limited systento prevent both without solving the self driving car problem at all. (I recommend looking at trains for this solution.) It is being done because it is attractive, not because it is necessary.
- gaius 8y ago
  The DotCom bubble burst, but we wound up with [arguably] useful results in the long run (agile, or whatever comes next, might be the biggest ripple). The outcome of the dotcom bubble was the build-out of the infrastructure (dark fibre). A similar bubble built out the railway infrastructure the century before that. Agile is a bubble in and of itself.
- deleted 8y ago
  [deleted]
rckclmbr 8y ago
It's down, here's a cache. http://webcache.googleusercontent.com/search?q=cache:hunch.net/?p%3D9604328&num=1&strip=1&vwsrc=0 http://webcache.googleusercontent.com/search?q=cache:hunch.n...
epsilonoptions 8y ago
If this bubble is to burst it will be followed by a "trough of disillusionment" (see the gartner hype cyle). But then hopefully the "slope of enlightenment" - unfortunately many of the early companies won;t survive the disillusionment phase.
- Jedi72 8y ago
  This curve was invented to justify why consultant BS shifters are always wrong.
  - epsilonoptions 8y ago
    :-) Point taken. It was first invented after the 2000-2001 dot com bubble I think. However i think it has some merit. Some of the things that were part of that period's hype (eg migration of retail to ecommerce) did . Eventually (nearly 20 years so far)....
tlear 8y ago
I would argue that we might be in a Research bubble(who knows.. I don't have a clue) but we are definitely not in "using the ML for practical problems bubble". Amount of industries and businesses that can benefit not from the state of the art but from stuff that been known for years now and just works because it was developed for harder problems is huge. The big return/promise companies are vacuuming up all the talent while niches all over the place can benefit from someone spending few month cleaning up data and using some transfer learning to save them a ton of $$. For these application you don't need PhD you need an engineer who knows how to ship stuff but on other hand also knows how to work with current DL frameworks.
- ackbar03 8y ago
  This sounds good on paper but I don't feel we see all that many real examples of this sort of model (engineer + niche problem) or at least haven't heard of them. But then again if we did I guess that opportunities already gone or saturated.
  - tlear 8y ago
    Different areas of manufacturing for example. All that computer vision, now apply it to X-rays of metal parts used to try and detect failures(not it is a guy looking at them all day using a dozen primitive filters, 8 hours a day every day). These are very domain specific, like liners of internal combustion engines, turbine blades etc On app side.. Cookpad added this neat feature last year, where it scans your pictures and adds to you cfood/cook log if it is food. The had a PhD do it, but this is because they want to do a lot more with it later I guess so building expertise and team. Food in general I think has a lot of neat computer vision apps that will happen eventually.
- Jedi72 8y ago
  There is a lot of old tech out there that could be implemented and would probably provide ROI, but isnt. So many businesses are still running on paper! My point is that industry isnt just sitting around waiting for new tech so they can get higher efficiency, there are reasons why not everyone is doing the latest and greatest (including ML) and they're usually valid.
raverbashing 8y ago
The AI bubble was caused by researchers being trapped on a local minimum and their focus on gradient descent meant they couldn't get out of that.
deleted 8y ago
[deleted]
grosjona 8y ago
Right now most AI experts in the industry are financially incentivized. They are more passionate about the money that they can make than about the research. It attracts the wrong kind of experts. The real experts are those who are working for universities and getting paid peanuts. Those who value knowledge above money.
- hikarudo 8y ago
  There are "real experts" in industry too. Industry doesn't need only good algorithms with solid foundations, which are invented in universities (say, SVM), but also people who understand the domain and can code that knowledge into algorithms and data (e.g. feature engineering).
therealmarv 8y ago
nah, there is no bubble. We just need to combine it with blockchain technology and then we have something shiny, rock stable which will change the industry ;)
greaseball 8y ago
I get the sense reading this article that the main concern raised is whether or not enough value is being generated by companies and researchers that "use machine learning to solve problems related to X" to justify the investment. The author doesn't touch upon whether using ML could be exacerbating the very problems these implementations are trying to solve. Inappropriate implementations of classification algorithms and predictive analysis that create false positives has the potential to inflate this sort of a bubble even further.

114 points by dstein64 8y ago

'We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten...'

jaggederest 8y ago

I think it's interesting that there's a few things you could start thinking about when you see the title. I might be alone but it's feeling a little bubbly to me in a few different areas. ML is certainly one of them.

zamalek 8y ago

A few things, or rather ripples, survived the bubbles. AI crashed in the 1980s - but we eventually created Dragon Speech, handwriting recognition and a few other useful solutions. The DotCom bubble burst, but we wound up with [arguably] useful results in the long run (agile, or whatever comes next, might be the biggest ripple). Even if this bubble bursts, bigger and greater things will arise because of it. With only 2 samples of these bubbles the p-value is miserable, but history has taught us to see these bubbles through. Wisdom is not the sum of success, it is the sum of failure. We need to learn just how far we can push deep learning - within reasonable moral degrees of freedom.

blueprint 8y ago
> Wisdom is not the sum of success, it is the sum of failure That doesn't make any sense. Failing is not implicitly useful and (while we are on the topic of morality) must not be held up as a goal.
- ianai 8y ago
  Failure is not what happened in any of those examples. A failure is several orders of magnitude below a Great Recession or Great Depression.
- zamalek 8y ago
  > failure [...] morality They were simultaneously different points and part of the same point in my argument. Separately, failure is a good thing - as any CEO would tell you. Together, they are horrific. It's very complicated, which is a far cry from "idiotic" as the article portrays.
  - blueprint 8y ago
    Failure is a good thing? By itself? What a strange fantasy.
- paulcole 8y ago
  Succeeding isn’t implicitly useful either. Succeeding mustn’t be held up as a goal or you end up with Uber.
  - blueprint 8y ago
    We were talking about wisdom.
- vertexFarm 8y ago
  Ha. You are in for some rough lessons my friend.
  - blueprint 8y ago
    Go ahead and say what they are if you know them. I doubt you will be able to say anything. Instead of being silent, you should have the courage to admit you don't actually know what you're talking about and don't have much if anything to tell me.
    - blueprint 8y ago
      More downvotes please. The weakness of your argument and the fact all you can do is repress and attempt to censor my reply (because you can't understand it) needs to be made more obvious! Best prevent other people from finding out about what I said and attempt to socially pressure them into not holding such an opinion because then they wouldn't be able to be fooled by you anymore and even you might have to change. And that's just too scary. I can answer every critique you throw at me about this topic. Yet no one here could reply to even one of my responses. You're laughable in your denial, ignorance, and weak-mindedness.
      - DanBC 8y ago
        vertexfarm did not downvote you. It's not possible to downvote replies to your own comments.
        blueprint 8y ago
        Yes, I know. That much was already clear by the fact more than one downvote was received. I'm addressing a group of individuals whose way of thinking is so homogeneous they may as well have lost their individual identities.
      - deleted 8y ago
        [deleted]
    - 8y ago
- SuoDuanDao 8y ago
  I would say failure by definition cannot be held up as a goal. The upside of failure is that it teaches more reliable lessons than success, there's no survivorship bias at play when learning from failures like there is with success. Jack Ma's lengthy interview at Davos this year touches on the subject if you'd like to see that perspective defended by someone with authority.
  - blueprint 8y ago
    > I would say failure by definition cannot be held up as a goal. It depends on who is doing it. Maybe you understand what you said, but others have an interest in not understanding it because they have an obstacle in themselves. > The upside of failure is that it teaches more reliable lessons than success, there's no survivorship bias at play when learning from failures like there is with success. I would like to improve your abilities or otherwise open up your wisdom. Any "upside of failure" is by definition a success. Therefore people's statements about success and failure, as if the nature of the result can be captured by a singular datapoint, are self-contradictory, and meaningful only as a reflection of the individual's limitation of understanding. > if you'd like to see that perspective defended by someone with authority. We're talking about wisdom here, so the only authority is a perfectly enlightened being, not an ordinary human being who has knowledge but no way to confirm the degree of exactness of their own ability to make confirmations. No one without enlightenment perceives the causes of why things happen to them. If you want to convince me someone is an authority on how a good and a bad thing happens then I will need to see any proof at all they realize the principle by which the world operates. Otherwise you should realize that's merely their own ideas, of which some percentage may be correct, despite their inability to confirm it.
ianai 8y ago
Bubbles (last I checked) don’t have a firm empirical definition. But the ebb and flow that you’re arguing for is very dramatic. Society could have made those discoveries without leaving large swaths of people and places unemployed. Further, anything that impacts the populous negatively makes a bigger, deeper, and longer lasting, negative impact on national wealth than anything a few companies could ever achieve in similar constraints.
- zamalek 8y ago
  > Society could have made those discoveries without leaving large swaths of people and places unemployed I am currently a proponent of self-driving cars, as I believe that human reflexes are designed to operate at, on average, 6mph. Almost anything could be better than us, at least in theory. Testing the limits of self-driving cars is how we determine what we can't do with them (and asking too much is how we zero-in on the failure point). This has complex moral consequences. Will more people be killed due to failure, or fewer? Thats great if it works out, but horrific if it doesn't. It's incredibly difficult to draw a line given that we don't know what the whole landscape is. This bubble is worsening unemployment. One ripple arising from that is UBI. Another is a positive-sum world. ML is currently successful in medicine. It's not all doom and gloom - we are already reaping long-term benefits.
  - 80x25 8y ago
    > This bubble is worsening unemployment. By what measure?
    - zamalek 8y ago
      By the measure of the parent comment, and, I think globally. It's often best to accommodate an argument when you have more than one way to make your case. If someone believes that unemployment is on the rise, despite the facts that you (specifically) may have, let them win it - because they have seen the same facts and don't care.
  - AstralStorm 8y ago
    Our reflexes are fine at about 100 Hz. That gives up to 2m distance at rival urban speeds before action and drivers shouldn't rely just on reflexes anyway. The problem is not reflexes, the problem is some drivers being dumb and a bunch of others distracted. You could mandate a very limited systento prevent both without solving the self driving car problem at all. (I recommend looking at trains for this solution.) It is being done because it is attractive, not because it is necessary.
gaius 8y ago
The DotCom bubble burst, but we wound up with [arguably] useful results in the long run (agile, or whatever comes next, might be the biggest ripple). The outcome of the dotcom bubble was the build-out of the infrastructure (dark fibre). A similar bubble built out the railway infrastructure the century before that. Agile is a bubble in and of itself.
deleted 8y ago
[deleted]

rckclmbr 8y ago

It's down, here's a cache. http://webcache.googleusercontent.com/search?q=cache:hunch.net/?p%3D9604328&num=1&strip=1&vwsrc=0 http://webcache.googleusercontent.com/search?q=cache:hunch.n...

epsilonoptions 8y ago

If this bubble is to burst it will be followed by a "trough of disillusionment" (see the gartner hype cyle). But then hopefully the "slope of enlightenment" - unfortunately many of the early companies won;t survive the disillusionment phase.

Jedi72 8y ago
This curve was invented to justify why consultant BS shifters are always wrong.
- epsilonoptions 8y ago
  :-) Point taken. It was first invented after the 2000-2001 dot com bubble I think. However i think it has some merit. Some of the things that were part of that period's hype (eg migration of retail to ecommerce) did . Eventually (nearly 20 years so far)....

tlear 8y ago

I would argue that we might be in a Research bubble(who knows.. I don't have a clue) but we are definitely not in "using the ML for practical problems bubble". Amount of industries and businesses that can benefit not from the state of the art but from stuff that been known for years now and just works because it was developed for harder problems is huge. The big return/promise companies are vacuuming up all the talent while niches all over the place can benefit from someone spending few month cleaning up data and using some transfer learning to save them a ton of $$. For these application you don't need PhD you need an engineer who knows how to ship stuff but on other hand also knows how to work with current DL frameworks.

ackbar03 8y ago
This sounds good on paper but I don't feel we see all that many real examples of this sort of model (engineer + niche problem) or at least haven't heard of them. But then again if we did I guess that opportunities already gone or saturated.
- tlear 8y ago
  Different areas of manufacturing for example. All that computer vision, now apply it to X-rays of metal parts used to try and detect failures(not it is a guy looking at them all day using a dozen primitive filters, 8 hours a day every day). These are very domain specific, like liners of internal combustion engines, turbine blades etc On app side.. Cookpad added this neat feature last year, where it scans your pictures and adds to you cfood/cook log if it is food. The had a PhD do it, but this is because they want to do a lot more with it later I guess so building expertise and team. Food in general I think has a lot of neat computer vision apps that will happen eventually.
Jedi72 8y ago
There is a lot of old tech out there that could be implemented and would probably provide ROI, but isnt. So many businesses are still running on paper! My point is that industry isnt just sitting around waiting for new tech so they can get higher efficiency, there are reasons why not everyone is doing the latest and greatest (including ML) and they're usually valid.

raverbashing 8y ago

The AI bubble was caused by researchers being trapped on a local minimum and their focus on gradient descent meant they couldn't get out of that.

deleted 8y ago

[deleted]

grosjona 8y ago

Right now most AI experts in the industry are financially incentivized. They are more passionate about the money that they can make than about the research. It attracts the wrong kind of experts. The real experts are those who are working for universities and getting paid peanuts. Those who value knowledge above money.

hikarudo 8y ago
There are "real experts" in industry too. Industry doesn't need only good algorithms with solid foundations, which are invented in universities (say, SVM), but also people who understand the domain and can code that knowledge into algorithms and data (e.g. feature engineering).

therealmarv 8y ago

nah, there is no bubble. We just need to combine it with blockchain technology and then we have something shiny, rock stable which will change the industry ;)

greaseball 8y ago

I get the sense reading this article that the main concern raised is whether or not enough value is being generated by companies and researchers that "use machine learning to solve problems related to X" to justify the investment. The author doesn't touch upon whether using ML could be exacerbating the very problems these implementations are trying to solve. Inappropriate implementations of classification algorithms and predictive analysis that create false positives has the potential to inflate this sort of a bubble even further.