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I think the quote does a great job at explaining why a lot of people have been critical of labeling the recent breakthroughs in Machine learning as real intelli

I think the quote does a great job at explaining why a lot of people have been critical of labeling the recent breakthroughs in Machine learning as real intelligence. Most people define intelligence in comparison to humans. Things like being the best GO player in the world are so specialized that they don't seem very human at all. Most people will not be impressed by a machine that can master backgammon, chess and poker, despite it being a great technical feat. They would be impressed by one that can successfully teach a 5th grade math class, even though there are hundreds of thousands of people who can do this. This would require more than teaching the kids math, but also how to deal with the kid who loses a parent during the school year. How to deal with bullying in the class, with misbehaving students. None of it is "specialized knowledge" like playing GO. And we are nowhere even remotely close to this.

philipkglass 10y ago
I used to think that the rarity of human mastery of games, and games' abstraction from the physical world, were what prevented most humans from perceiving machine intelligence as intelligence. Then the 2005 DARPA Grand Challenge for self-driving vehicles showed that machines could perform a task that most adult Americans can perform, that no non-human animals have ever been taught to perform, and that requires significant awareness of the physical world. But AFAICT it didn't cause a sea change in how most people think about intelligence, human and otherwise. There has been an uptick in people pondering the economic implications of driverless vehicles and a more robotic future. That discussion seems kind of oddly isolated from re-considering the nature of intelligence, human and otherwise. It's as if after the Industrial Revolution people kept narrowly scoping the meaning of "power" to "muscle power" rather than acknowledging mechanical forms. Oh, yes, that coal fired pump can remove water from the mine faster than I can... but it just uses clever tricks for faking power.
- laughinghan 10y ago
  > a task that most adult Americans can perform, that no non-human animals have ever been taught to perform Woah wait what? Non-human animals successfully navigate >7 miles of mountain terrain all the time. Machine intelligence doesn't seem like "real" intelligence because it just doesn't seem as generalizable. Taking the engines and hydraulics used to great effect in water pumps and applying them to construction cranes required engineering work, sure, but no new physics. But you can't just take the convolutional neural nets that are breaking new ground in computer vision and apply them to natural language processing, you need new computer science research to develop long short-term memory networks. The cool thing about AlphaGo, from my understanding, was that it was able to train the deep learning-based heuristics for board evaluation by playing a ton of games against itself. This is especially awesome because those heuristics are (were?) our main edge over machines [1]. But in CV and NLP, playing against yourself isn't really a thing, so again, this work doesn't automatically generalize the way engines and hydraulics did. [1]: https://en.wikipedia.org/wiki/Anti-computer_tactics https://en.wikipedia.org/wiki/Anti-computer_tactics
- deleted 10y ago
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philipkglass 10y ago

I used to think that the rarity of human mastery of games, and games' abstraction from the physical world, were what prevented most humans from perceiving machine intelligence as intelligence. Then the 2005 DARPA Grand Challenge for self-driving vehicles showed that machines could perform a task that most adult Americans can perform, that no non-human animals have ever been taught to perform, and that requires significant awareness of the physical world. But AFAICT it didn't cause a sea change in how most people think about intelligence, human and otherwise. There has been an uptick in people pondering the economic implications of driverless vehicles and a more robotic future. That discussion seems kind of oddly isolated from re-considering the nature of intelligence, human and otherwise. It's as if after the Industrial Revolution people kept narrowly scoping the meaning of "power" to "muscle power" rather than acknowledging mechanical forms. Oh, yes, that coal fired pump can remove water from the mine faster than I can... but it just uses clever tricks for faking power.

laughinghan 10y ago
> a task that most adult Americans can perform, that no non-human animals have ever been taught to perform Woah wait what? Non-human animals successfully navigate >7 miles of mountain terrain all the time. Machine intelligence doesn't seem like "real" intelligence because it just doesn't seem as generalizable. Taking the engines and hydraulics used to great effect in water pumps and applying them to construction cranes required engineering work, sure, but no new physics. But you can't just take the convolutional neural nets that are breaking new ground in computer vision and apply them to natural language processing, you need new computer science research to develop long short-term memory networks. The cool thing about AlphaGo, from my understanding, was that it was able to train the deep learning-based heuristics for board evaluation by playing a ton of games against itself. This is especially awesome because those heuristics are (were?) our main edge over machines [1]. But in CV and NLP, playing against yourself isn't really a thing, so again, this work doesn't automatically generalize the way engines and hydraulics did. [1]: https://en.wikipedia.org/wiki/Anti-computer_tactics https://en.wikipedia.org/wiki/Anti-computer_tactics
deleted 10y ago
[deleted]