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Until our current big data AI revolution, AI was one investment catastrophe after another. Now money finally is flowing into AI again, and intuitions like this

by tinco 11y ago

Until our current big data AI revolution, AI was one investment catastrophe after another. Now money finally is flowing into AI again, and intuitions like this idea, backed by a little big data power can be explored again. So even though the idea is fairly simple, I think anyone who thinks about AI for any trivial amount of time will come up with the idea that AI's somehow have to automatically generate imperfect generalizations, the final result might be a truly innovative product. Actually building an AI that does this on a scale that results in useful applications is something that probably has not been practical for a long time, and might or might not be now.

0xdeadbeefbabe 11y ago
Do you have reference for one investment catastrophe after the other? I know it failed to deliver on the promise of translating human language, for example.
- fractallyte 11y ago
  This article lays out those failures: https://en.wikipedia.org/wiki/AI_winter https://en.wikipedia.org/wiki/AI_winter
- minort 11y ago
  I saw it first hand at an investment management firm in the late 1990s. They hired a team of Neural Nets experts out of academia. Never produced much useful, cost millions and wasted lots of peoples time. My understanding is that there were many other similar situations at other firms around that time. As far as I know there were no great successes.
mindcrime 11y ago
Until our current big data AI revolution, AI was one investment catastrophe after another. Maybe from the point of view of the investors themselves, in most cases, if they were expecting a big, immediate financial return. But the technology has been improving steadily (ish) throughout the years. As AI people sometimes say "AI is whatever computers can't to $today". That is, as soon as AI reaches a point where it can do something useful, people stop considering it AI. I saw an example of this yesterday while having a conversation with somebody much younger than me (I'm 42) when we got on this topic. I was saying that things like the voice recognition in that Google Now, Siri, Cortana (sp?), etc. use would be good examples of what would have been mind-blowing AI capabilities 20 or 30 years ago and he said "Oh, that's AI?" No, it's not AI now, because now it's common-place. :-) Of course, none of that is to say that we aren't still a long way away from a true "AGI". But AI research has been yielding useful techniques for quite a long time, even if we didn't get "there yet" for AGI.

by tinco 11y ago

0xdeadbeefbabe 11y ago

Do you have reference for one investment catastrophe after the other? I know it failed to deliver on the promise of translating human language, for example.

fractallyte 11y ago
This article lays out those failures: https://en.wikipedia.org/wiki/AI_winter https://en.wikipedia.org/wiki/AI_winter
minort 11y ago
I saw it first hand at an investment management firm in the late 1990s. They hired a team of Neural Nets experts out of academia. Never produced much useful, cost millions and wasted lots of peoples time. My understanding is that there were many other similar situations at other firms around that time. As far as I know there were no great successes.

mindcrime 11y ago

Until our current big data AI revolution, AI was one investment catastrophe after another. Maybe from the point of view of the investors themselves, in most cases, if they were expecting a big, immediate financial return. But the technology has been improving steadily (ish) throughout the years. As AI people sometimes say "AI is whatever computers can't to $today". That is, as soon as AI reaches a point where it can do something useful, people stop considering it AI. I saw an example of this yesterday while having a conversation with somebody much younger than me (I'm 42) when we got on this topic. I was saying that things like the voice recognition in that Google Now, Siri, Cortana (sp?), etc. use would be good examples of what would have been mind-blowing AI capabilities 20 or 30 years ago and he said "Oh, that's AI?" No, it's not AI now, because now it's common-place. :-) Of course, none of that is to say that we aren't still a long way away from a true "AGI". But AI research has been yielding useful techniques for quite a long time, even if we didn't get "there yet" for AGI.