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Face recognition and picture processing is considered AI?

by Oletros 10y ago

galistoca 10y ago
Yes
daveguy 10y ago
You must be a millennial. Those challenges have been pushing AI research for decades (and still are). In case you haven't noticed, "build an AI" consists of quite a few different problem domains -- not just chatbots and fully formed humanoid robots.
deleted 10y ago
[deleted]
arjie 10y ago
This is the real AI problem. Once an AI problem is solved, whatever solved it is no longer considered an example of AI.
- daveguy 10y ago
  This is starting to become a fallacy rather than a cute tongue in cheek saying by AI researchers. Once a problem that is used to push AI research is solved better than humans then it is usually no longer cutting edge AI research. Chess for example. Minimax search with tweaks for board eval. Done. Handwriting recognition - better than humans by a committee of NNs, but still considered an AI research problem. It is a benchmark for algorithms. That doesn't mean just because an algorithm can do it that we have general artificial intelligence. A general AI will have to identify digits and play a decent game of chess and have a conversation. That doesn't mean the problem domains that drive AI research are not AI after they are solved individually. A lot of researchers think "this is a great problem, surely it will require human level general intelligence". When an algorithm is identified that solves the problem without needing general intelligence, they look for the next problem domain... or keep on improving in that domain (image recognition, but not necessarily of dog breeds, that's solved). This intermediate focus gives direction to AI research while general intelligence gives purpose. None of those researchers are saying solving X means solving AI. None are saying each of these domains is sufficient for AI, rather they might be necessary and are a good place to start to advance the field. About the only behavior or skill, X, that researchers think may be sufficient for AI is an entity that can communicate well enough to pass an unbiased Turing test. Artificial general intelligence is a long way off, no matter how many cats can be identified from a pile of photos. Maybe it is a definitions issue. AI is whatever AI researchers are working on at the cutting edge to advance the field. AGI (general intelligence) is much broader and no algorithm has come close to demonstrating AGI.
  - marcosdumay 10y ago
    Is anybody anywhere working in "human level intelligence"? People like to talk about it, but I doubt any serious researcher claims to be solving it. It's a non-specified problem, I can't even imagine what a paper on it would look like. How would you know you achieved it? In practice AI is those concrete problems. And the fact that they often stop being AI after solved is a real PR problem for the researchers.
    - erichocean 10y ago
      > Is anybody anywhere working in "human level intelligence"? Yes. http://www.abi.auckland.ac.nz/en/about/our-research/animate-technologies.html http://www.abi.auckland.ac.nz/en/about/our-research/animate-...
sandstrom 10y ago
I agree! Six months ago this was called machine learning, now it's all AI. Sort of like BigData and Web 2.0, vague terms used for almost everything.
- eivarv 10y ago
  I don't think that's right, as the techniques are still called machine learning. Though the distinction between the terms "machine learning" and "artificial intelligence" is somewhat unclear (depending on usage) I think a useful one is to see ML as a technique/strategy and AI as the goal. It's also not as though AI is or means the same as "strong AI" or AGI [1]. [1]: https://en.wikipedia.org/wiki/Artificial_general_intelligence https://en.wikipedia.org/wiki/Artificial_general_intelligenc...
- WoodenChair 10y ago
  Machine Learning used to be considered a sub-discipline of AI (open an AI textbook and you'll see a couple chapters on it). It's grown so big that now it's a term used in and of itself outside of AI. It is starting to be seen as distinctive from "traditional" AI in some circles. So the correct understanding is either that Machine Learning is a subset of AI or that Machine Learning is a field that emerged from AI.
MawNicker 10y ago
You're confusing AI and AGI (artificial general intelligence). AGI is a subset of AI focused on introspective systems that are resourceful and don't get stuck. Like humans. Face recognition and picture processing are not AGI.
_pmf_ 10y ago
Yes. And reusing COTS radar sensors by Bosch or Continental or Delphi in a Tesla equals "Silicon Valley breakthrough in autonomous driving".

Face recognition and picture processing is considered AI?

by Oletros 10y ago

Face recognition and picture processing is considered AI?

galistoca 10y ago

Yes

daveguy 10y ago

You must be a millennial. Those challenges have been pushing AI research for decades (and still are). In case you haven't noticed, "build an AI" consists of quite a few different problem domains -- not just chatbots and fully formed humanoid robots.

deleted 10y ago

[deleted]

arjie 10y ago

This is the real AI problem. Once an AI problem is solved, whatever solved it is no longer considered an example of AI.

daveguy 10y ago
This is starting to become a fallacy rather than a cute tongue in cheek saying by AI researchers. Once a problem that is used to push AI research is solved better than humans then it is usually no longer cutting edge AI research. Chess for example. Minimax search with tweaks for board eval. Done. Handwriting recognition - better than humans by a committee of NNs, but still considered an AI research problem. It is a benchmark for algorithms. That doesn't mean just because an algorithm can do it that we have general artificial intelligence. A general AI will have to identify digits and play a decent game of chess and have a conversation. That doesn't mean the problem domains that drive AI research are not AI after they are solved individually. A lot of researchers think "this is a great problem, surely it will require human level general intelligence". When an algorithm is identified that solves the problem without needing general intelligence, they look for the next problem domain... or keep on improving in that domain (image recognition, but not necessarily of dog breeds, that's solved). This intermediate focus gives direction to AI research while general intelligence gives purpose. None of those researchers are saying solving X means solving AI. None are saying each of these domains is sufficient for AI, rather they might be necessary and are a good place to start to advance the field. About the only behavior or skill, X, that researchers think may be sufficient for AI is an entity that can communicate well enough to pass an unbiased Turing test. Artificial general intelligence is a long way off, no matter how many cats can be identified from a pile of photos. Maybe it is a definitions issue. AI is whatever AI researchers are working on at the cutting edge to advance the field. AGI (general intelligence) is much broader and no algorithm has come close to demonstrating AGI.
- marcosdumay 10y ago
  Is anybody anywhere working in "human level intelligence"? People like to talk about it, but I doubt any serious researcher claims to be solving it. It's a non-specified problem, I can't even imagine what a paper on it would look like. How would you know you achieved it? In practice AI is those concrete problems. And the fact that they often stop being AI after solved is a real PR problem for the researchers.
  - erichocean 10y ago
    > Is anybody anywhere working in "human level intelligence"? Yes. http://www.abi.auckland.ac.nz/en/about/our-research/animate-technologies.html http://www.abi.auckland.ac.nz/en/about/our-research/animate-...

sandstrom 10y ago

I agree! Six months ago this was called machine learning, now it's all AI. Sort of like BigData and Web 2.0, vague terms used for almost everything.

eivarv 10y ago
I don't think that's right, as the techniques are still called machine learning. Though the distinction between the terms "machine learning" and "artificial intelligence" is somewhat unclear (depending on usage) I think a useful one is to see ML as a technique/strategy and AI as the goal. It's also not as though AI is or means the same as "strong AI" or AGI [1]. [1]: https://en.wikipedia.org/wiki/Artificial_general_intelligence https://en.wikipedia.org/wiki/Artificial_general_intelligenc...
WoodenChair 10y ago
Machine Learning used to be considered a sub-discipline of AI (open an AI textbook and you'll see a couple chapters on it). It's grown so big that now it's a term used in and of itself outside of AI. It is starting to be seen as distinctive from "traditional" AI in some circles. So the correct understanding is either that Machine Learning is a subset of AI or that Machine Learning is a field that emerged from AI.

MawNicker 10y ago

You're confusing AI and AGI (artificial general intelligence). AGI is a subset of AI focused on introspective systems that are resourceful and don't get stuck. Like humans. Face recognition and picture processing are not AGI.

_pmf_ 10y ago

Yes. And reusing COTS radar sensors by Bosch or Continental or Delphi in a Tesla equals "Silicon Valley breakthrough in autonomous driving".