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> Even though I’m one of the beneficiary of this AI craze, I can’t help but thinking this will burst. I don't think it will. Level off - maybe. I've started m

> Even though I’m one of the beneficiary of this AI craze, I can’t help but thinking this will burst. I don't think it will. Level off - maybe. I've started my work in Computer Vision with classical algorithms (SIFT features, geometry, correlation filters and things alike people were researching for decades). These really worked like garbage, it was a nightmare. Then we jumped on DL bandwagon - and CV just clicked for me. Now I see it working, not perfectly, not at human level yet, but it works, it's better than everything else and it certainly brings value - not just in CV! Maybe there will be some expectations delayed or even ruined (AGI, fully self-driving cars, dunno), but the tech isn't going anywhere. At it requires at least some experience and a specific mindset, slightly unusual for a generic programmer. So I don't see a problem with experts, courses, degrees and the like.

visarga 9y ago
Computer vision is the part of DL that is most suited to produce economic value. CV will be worth trillions of dollars in a couple of decades. All those cars, drones, agricultural equipment, medical scanners, robots and security cameras will be able to understand what they see and act intelligently. It's like the most universally useful thing since the invention of the wheel.
- rubidium 9y ago
  "It's like the most universally useful thing since the invention of the wheel." I'll choose refrigeration, combustion engine, concrete, and probably hundreds of other things before computer vision.
  - visarga 9y ago
    I said universally useful - a refrigerator is just that. A CV system can be used in hundreds of totally different applications. Like the wheel and yes, the engine. The engine is universal as well, you could see it as the upgrade of the wheel.
pron 9y ago
> not at human level yet Not even at insect level yet. There's no doubt things will improve, and there's already great value, but I hate calling ML "AI". It's been over 70 years of ML research (specifically neural networks) and I don't know how long it's going to take to reach insect-level behavior (which is still far from basic intelligence) let alone so-called AGI (which, BTW, people in the '50s were certain is just around the corner), even though I think we'll get there eventually. We'd better stop using the term "AI" to mean anything other than a field of research or an aspiration, and definitely stop using it to describe existing software.
- IanCal 9y ago
  What do you mean by insect level here?
  - sdenton4 9y ago
    We can't make things as smart as bees.
- alexcnwy 9y ago
  Actually Andrej Karpathy showed human level error on imagenet is around 5% while the winning model from 2017 had an error rate of just 2.25%.
  - pron 9y ago
    Computers were able to perform some tasks better than humans since they were first built in the 40s. Computers are only used for things they are better at than humans. There is nothing to suggest, however, that there is anything closer to "intelligence" in recognizing images as in compiling census statistics, and no software is as adept in "general problem solving" as insects.
    - alexcnwy 9y ago
      Honestly I think you're playing a language game. I'm sure you're familiar with the line of reasoning that if you asked someone 50 years ago to describe tasks that require intelligence, they'd for sure say recognizing objects in images is one of them. Now that computers can do that, it's no longer 'intelligence' and the goalposts get moved. In what sense is no software 'as adept in "general problem solving" as insects'?
jcoffland 9y ago
Pattern matching is the one thing DL is good for. Which is why it's a good match for CV. Calling DL AI in the first place was a mistake or at least over zealous marketing. Playing go or chess or matching patterns are all things intelligent begins can do but that does not imply that doing those thing means you are intelligent.
- PeterisP 9y ago
  One can argue that the parts of our brain that make us intelligent, the prefrontal cortex that is so much bigger than in "lesser" animals, is essentially an overgrown, glorified pattern matching engine. Pattern matching is the one thing our brains are good for - there's good reason to suppose that quite many intelligence-related tasks can be reduced to a form of pattern matching.
  - jcoffland 9y ago
    One could argue a lot of things. Humans once argued quite seriously that the human brain was composed of microscopic gears because that was the technology of the time.
- p1esk 9y ago
  Ok, so what ability is worthy of "AI" name?
  - jcoffland 9y ago
    Getting the nations of the world to stop bickering and balance our resource usage fairly and with in the capacity of our planet.
    - p1esk 9y ago
      "Fairly" according to whom? One of the nations? Some individual? Or do you want the AI to come up with the definition of "fair"? What if some people disagree? What if the majority of people disagree? In any case, this could be achieved with extreme violence. Do you really want "AI" imposing its (or someone's) will on the world?
gaius 9y ago
I don't think it will. Level off - maybe. https://en.m.wikipedia.org/wiki/AI_winter https://en.m.wikipedia.org/wiki/AI_winter
- ansible 9y ago
  Eh, we've reached a crossover point already. Various products and services have shown that DL and other ML techniques are useful and profitable to implement. And corporations can see the benefits of incremental improvements. That alone will continue the momentum, even without amazing breakthroughs.
  - gaius 9y ago
    Various products and services have shown that DL and other ML techniques are useful and profitable to implement. Very few organisations are seeing ROI on these projects. I've seen figures showing average for every million spent the return is less than half, for the quarter of them that actually get into production...
bitL 9y ago
This. I don't think people even get a hint of what is possible nowadays with DL in CV, NLP etc. I am actually depressed when I talk to some friends and they are so pitifully outdated, and then even after showing them how to do some magic in 100 lines, observing they are still not getting it and continuing in their old ways :(
- deleted 9y ago
  [deleted]
- CalRobert 9y ago
  Just out of curiosity, where would you recommend starting for those outdated people? Machine Learning, Deep Learning, AI (for lack of a more specific acronym), NLP - these things are kind of daunting for newcomers, if only due to the acronym du jour changing constantly.
  - mncharity 9y ago
    > where would you recommend starting [emphasis mine] Play with http://playground.tensorflow.org/ http://playground.tensorflow.org/ . Read today's https://news.ycombinator.com/item?id=14992865 https://news.ycombinator.com/item?id=14992865 about https://pair-code.github.io/deeplearnjs/ https://pair-code.github.io/deeplearnjs/ .
    - CalRobert 9y ago
      Thank you! much appreciated.
  - 31reasons 9y ago
    Great thing about Deep Learning is that decades of "old school" machine learning research that was way too math intensive is far inferior now. DL is actually pretty approachable and intuitive.
    - rocqua 9y ago
      To someone mathy like me, that kinda sucks. It's part of why I don't like deep learning.
dmreedy 9y ago
This is precisely the pattern of past winters. The technical achievements don't go anywhere. But the hype dwindles, and funding and public interest accordingly, as disappointment and skepticism grows. It doesn't permanently stop progress, just as a burst economic bubble doesn't necessarily kill an economy. Just dramatically slows it, at great cost.
tnecniv 9y ago
> I don't think it will. Level off - maybe. I mean, the dotcom bubble popped but websites are still here and more profitable than ever. The bubble popping doesn't mean that DL is going to go away. People will just have more reasonable expectations about what it can do.
nabla9 9y ago
These two things are not exclusive: 1. Something works past all expectations. 2. There is craze, overhype, bubble and bust. The markets have the ability to overvalue things that are great successes. In fact overinvestment and bubbles are often the result of real success. If something generates 100X return, its completely feasible that markets value it in level that would require 200X return to be profitable investment.

visarga 9y ago

Computer vision is the part of DL that is most suited to produce economic value. CV will be worth trillions of dollars in a couple of decades. All those cars, drones, agricultural equipment, medical scanners, robots and security cameras will be able to understand what they see and act intelligently. It's like the most universally useful thing since the invention of the wheel.

rubidium 9y ago
"It's like the most universally useful thing since the invention of the wheel." I'll choose refrigeration, combustion engine, concrete, and probably hundreds of other things before computer vision.
- visarga 9y ago
  I said universally useful - a refrigerator is just that. A CV system can be used in hundreds of totally different applications. Like the wheel and yes, the engine. The engine is universal as well, you could see it as the upgrade of the wheel.

pron 9y ago

> not at human level yet Not even at insect level yet. There's no doubt things will improve, and there's already great value, but I hate calling ML "AI". It's been over 70 years of ML research (specifically neural networks) and I don't know how long it's going to take to reach insect-level behavior (which is still far from basic intelligence) let alone so-called AGI (which, BTW, people in the '50s were certain is just around the corner), even though I think we'll get there eventually. We'd better stop using the term "AI" to mean anything other than a field of research or an aspiration, and definitely stop using it to describe existing software.

IanCal 9y ago
What do you mean by insect level here?
- sdenton4 9y ago
  We can't make things as smart as bees.
alexcnwy 9y ago
Actually Andrej Karpathy showed human level error on imagenet is around 5% while the winning model from 2017 had an error rate of just 2.25%.
- pron 9y ago
  Computers were able to perform some tasks better than humans since they were first built in the 40s. Computers are only used for things they are better at than humans. There is nothing to suggest, however, that there is anything closer to "intelligence" in recognizing images as in compiling census statistics, and no software is as adept in "general problem solving" as insects.
  - alexcnwy 9y ago
    Honestly I think you're playing a language game. I'm sure you're familiar with the line of reasoning that if you asked someone 50 years ago to describe tasks that require intelligence, they'd for sure say recognizing objects in images is one of them. Now that computers can do that, it's no longer 'intelligence' and the goalposts get moved. In what sense is no software 'as adept in "general problem solving" as insects'?

jcoffland 9y ago

Pattern matching is the one thing DL is good for. Which is why it's a good match for CV. Calling DL AI in the first place was a mistake or at least over zealous marketing. Playing go or chess or matching patterns are all things intelligent begins can do but that does not imply that doing those thing means you are intelligent.

PeterisP 9y ago
One can argue that the parts of our brain that make us intelligent, the prefrontal cortex that is so much bigger than in "lesser" animals, is essentially an overgrown, glorified pattern matching engine. Pattern matching is the one thing our brains are good for - there's good reason to suppose that quite many intelligence-related tasks can be reduced to a form of pattern matching.
- jcoffland 9y ago
  One could argue a lot of things. Humans once argued quite seriously that the human brain was composed of microscopic gears because that was the technology of the time.
p1esk 9y ago
Ok, so what ability is worthy of "AI" name?
- jcoffland 9y ago
  Getting the nations of the world to stop bickering and balance our resource usage fairly and with in the capacity of our planet.
  - p1esk 9y ago
    "Fairly" according to whom? One of the nations? Some individual? Or do you want the AI to come up with the definition of "fair"? What if some people disagree? What if the majority of people disagree? In any case, this could be achieved with extreme violence. Do you really want "AI" imposing its (or someone's) will on the world?

gaius 9y ago

I don't think it will. Level off - maybe. https://en.m.wikipedia.org/wiki/AI_winter https://en.m.wikipedia.org/wiki/AI_winter

ansible 9y ago
Eh, we've reached a crossover point already. Various products and services have shown that DL and other ML techniques are useful and profitable to implement. And corporations can see the benefits of incremental improvements. That alone will continue the momentum, even without amazing breakthroughs.
- gaius 9y ago
  Various products and services have shown that DL and other ML techniques are useful and profitable to implement. Very few organisations are seeing ROI on these projects. I've seen figures showing average for every million spent the return is less than half, for the quarter of them that actually get into production...

bitL 9y ago

This. I don't think people even get a hint of what is possible nowadays with DL in CV, NLP etc. I am actually depressed when I talk to some friends and they are so pitifully outdated, and then even after showing them how to do some magic in 100 lines, observing they are still not getting it and continuing in their old ways :(

deleted 9y ago
[deleted]
CalRobert 9y ago
Just out of curiosity, where would you recommend starting for those outdated people? Machine Learning, Deep Learning, AI (for lack of a more specific acronym), NLP - these things are kind of daunting for newcomers, if only due to the acronym du jour changing constantly.
- mncharity 9y ago
  > where would you recommend starting [emphasis mine] Play with http://playground.tensorflow.org/ http://playground.tensorflow.org/ . Read today's https://news.ycombinator.com/item?id=14992865 https://news.ycombinator.com/item?id=14992865 about https://pair-code.github.io/deeplearnjs/ https://pair-code.github.io/deeplearnjs/ .
  - CalRobert 9y ago
    Thank you! much appreciated.
- 31reasons 9y ago
  Great thing about Deep Learning is that decades of "old school" machine learning research that was way too math intensive is far inferior now. DL is actually pretty approachable and intuitive.
  - rocqua 9y ago
    To someone mathy like me, that kinda sucks. It's part of why I don't like deep learning.

dmreedy 9y ago

This is precisely the pattern of past winters. The technical achievements don't go anywhere. But the hype dwindles, and funding and public interest accordingly, as disappointment and skepticism grows. It doesn't permanently stop progress, just as a burst economic bubble doesn't necessarily kill an economy. Just dramatically slows it, at great cost.

tnecniv 9y ago

> I don't think it will. Level off - maybe. I mean, the dotcom bubble popped but websites are still here and more profitable than ever. The bubble popping doesn't mean that DL is going to go away. People will just have more reasonable expectations about what it can do.

nabla9 9y ago

These two things are not exclusive: 1. Something works past all expectations. 2. There is craze, overhype, bubble and bust. The markets have the ability to overvalue things that are great successes. In fact overinvestment and bubbles are often the result of real success. If something generates 100X return, its completely feasible that markets value it in level that would require 200X return to be profitable investment.