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I guess my concern isn't that these are "science fiction technologies" but that they're rather simple. AI has a history of over-promising and under-delivering a

I guess my concern isn't that these are "science fiction technologies" but that they're rather simple. AI has a history of over-promising and under-delivering and even if a few "self-driving" cars have made it on the road, how long until people begin trying to use them in scenarios they're not really ready for? All of that progress can disappear overnight if there are a few bad accidents. I guess when I look around, I don't see a comparison between AI now and the Internet then, I see a comparison between AI now and AI then (70's).

nostrademons 10y ago
AI has this effect where whenever an approach starts working, it ceases to be AI: https://en.wikipedia.org/wiki/AI_effect https://en.wikipedia.org/wiki/AI_effect It's worth remembering that many of the actual technologies developed in 1970s AI - A*, beam search, pattern matching, constraint solving, rules engines - are now basic CS algorithms that most programmers are just expected to know, and they have continued applicability to a wide variety of domains. We just don't call them "AI" anymore, because the technology has been commoditized enough that they are "business rules", or "single-player games", or "layout engines", or other examples of the actual problem domain that's solved. Ditto 1990s AI - fuzzy logic, SVMs, Bayesian networks, collaborative filtering, perceptrons. It just got good enough that it became the standard way you solve a certain class of problems with computers, and now it's called "fraud detection", "Zestimates (tm)", "recommendation engines", "stream ranking", and so on. Deep learning is the same. The hype cycle will eventually bust, because all hype cycles eventually bust. But in the meantime, it has opened up whole classes of problems in computer vision, speech recognition, recommendation, machine translation, and several other domains that were not amenable to computerized treatment before.
- frgtpsswrdlame 10y ago
  I guess that's sort of my point though isn't it? A, SVMs, etc. aren't really called AI because they're not. Because AI carries a connotation and once you understand A it's obvious that it's not really AI. Won't the same be true of today's neural networks? Granted they've been given a name which should add some longevity but when a layperson thinks "AI" they think a robot which acts like a human, they think AGI. If someone had an AI algorithm which could start to demonstrate more AGI leanings I bet the AI effect wouldn't apply.
  - nojvek 10y ago
    When cars came out they killed quite a number of people in accidents and mechanical failures. They were just so much better than horses we kept on improving them. That's how I see AI. People will surely get injures and even die in Accidents. We are a humanist society where human life is valued above everything else, so I'm very optimistic that AI will get better and give their humans more divine powers and longer life over time.

nostrademons 10y ago

AI has this effect where whenever an approach starts working, it ceases to be AI: https://en.wikipedia.org/wiki/AI_effect https://en.wikipedia.org/wiki/AI_effect It's worth remembering that many of the actual technologies developed in 1970s AI - A*, beam search, pattern matching, constraint solving, rules engines - are now basic CS algorithms that most programmers are just expected to know, and they have continued applicability to a wide variety of domains. We just don't call them "AI" anymore, because the technology has been commoditized enough that they are "business rules", or "single-player games", or "layout engines", or other examples of the actual problem domain that's solved. Ditto 1990s AI - fuzzy logic, SVMs, Bayesian networks, collaborative filtering, perceptrons. It just got good enough that it became the standard way you solve a certain class of problems with computers, and now it's called "fraud detection", "Zestimates (tm)", "recommendation engines", "stream ranking", and so on. Deep learning is the same. The hype cycle will eventually bust, because all hype cycles eventually bust. But in the meantime, it has opened up whole classes of problems in computer vision, speech recognition, recommendation, machine translation, and several other domains that were not amenable to computerized treatment before.

frgtpsswrdlame 10y ago
I guess that's sort of my point though isn't it? A, SVMs, etc. aren't really called AI because they're not. Because AI carries a connotation and once you understand A it's obvious that it's not really AI. Won't the same be true of today's neural networks? Granted they've been given a name which should add some longevity but when a layperson thinks "AI" they think a robot which acts like a human, they think AGI. If someone had an AI algorithm which could start to demonstrate more AGI leanings I bet the AI effect wouldn't apply.
- nojvek 10y ago
  When cars came out they killed quite a number of people in accidents and mechanical failures. They were just so much better than horses we kept on improving them. That's how I see AI. People will surely get injures and even die in Accidents. We are a humanist society where human life is valued above everything else, so I'm very optimistic that AI will get better and give their humans more divine powers and longer life over time.