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> There had been Stanford faculty running around claiming "strong AI real soon now" to Congress. That would be Ed Feigenbaum, the man who (IMHO) almost single-

> There had been Stanford faculty running around claiming "strong AI real soon now" to Congress. That would be Ed Feigenbaum, the man who (IMHO) almost single-handedly brought on the AI winter of the 80s. Because of him we had to call all the AI research we did in the 90s something other than "AI" lest it get shut down instantly.

Animats 5y ago
Um, yes. His book. "The Fifth Generation - Artificial Intelligence and Japan's Computer Challenge to the World" lays out his position. For a short version, here's his testimony before a congressional committee, asking for funding.[1] "The era of reasoning machines is inevitable. It is the "manifest destiny" of computing." He was taken seriously at the time. Chief Scientist of the USAF at one point. Turing Award. [1] https://stacks.stanford.edu/file/druid:mv321kw4621/mv321kw4621.pdf https://stacks.stanford.edu/file/druid:mv321kw4621/mv321kw46...
- listenallyall 5y ago
  > The era of reasoning machines is inevitable. It is the "manifest destiny" of computing." Isn't this pretty much the current opinion of the majority of the thousands of AI researchers and programmers today? Maybe this guy was early to the party but his vision seems in alignment with today's practitioners.
  - dreamcompiler 5y ago
    Yes; if anything the hype is even stronger today. The difference is that neural nets on modern hardware really do quite a few useful things, while expert systems on 80s hardware mostly did not. The reason the hype of today is more dangerous is what I call the grandmother issue: In the 80s we dreamed of a program that would recognize your grandmother when she walked in the room. That was one of our holy grails. Good news: The grandmother recognizer was finally built with deep neural nets in the 2000s and it works pretty well. It's not perfect but if you tell it to play grandma's favorite song when she walks in the room it's no big deal if it occasionally fails to recognize her, or if it plays the song when someone other than your grandma walks in the room. Bad news: We now have people who (effectively) want to attach the grandmother recognizer to a machine gun with instructions to shoot your grandmother and only your grandmother, and never to fail to shoot her if she walks in the room. Suddenly the Type 1 and Type 2 errors are a whole lot more consequential. Modern NNs are simply not fit for that job. We have pretty good AI for low-consequence purposes, but it cannot be used for high-consequence purposes without a lot more fundamental research. Incremental improvements to deep learning are not going to get us there.
    - giardini 5y ago
      Wellllll, um, not really.... Any NN recognizer can be fooled and your neighbor's dog may as likely be shot by the "granny gun AI". You need to read up on the validity of facial recognition software. It ain't nearly human!

Animats 5y ago

Um, yes. His book. "The Fifth Generation - Artificial Intelligence and Japan's Computer Challenge to the World" lays out his position. For a short version, here's his testimony before a congressional committee, asking for funding.[1] "The era of reasoning machines is inevitable. It is the "manifest destiny" of computing." He was taken seriously at the time. Chief Scientist of the USAF at one point. Turing Award. [1] https://stacks.stanford.edu/file/druid:mv321kw4621/mv321kw4621.pdf https://stacks.stanford.edu/file/druid:mv321kw4621/mv321kw46...

listenallyall 5y ago
> The era of reasoning machines is inevitable. It is the "manifest destiny" of computing." Isn't this pretty much the current opinion of the majority of the thousands of AI researchers and programmers today? Maybe this guy was early to the party but his vision seems in alignment with today's practitioners.
- dreamcompiler 5y ago
  Yes; if anything the hype is even stronger today. The difference is that neural nets on modern hardware really do quite a few useful things, while expert systems on 80s hardware mostly did not. The reason the hype of today is more dangerous is what I call the grandmother issue: In the 80s we dreamed of a program that would recognize your grandmother when she walked in the room. That was one of our holy grails. Good news: The grandmother recognizer was finally built with deep neural nets in the 2000s and it works pretty well. It's not perfect but if you tell it to play grandma's favorite song when she walks in the room it's no big deal if it occasionally fails to recognize her, or if it plays the song when someone other than your grandma walks in the room. Bad news: We now have people who (effectively) want to attach the grandmother recognizer to a machine gun with instructions to shoot your grandmother and only your grandmother, and never to fail to shoot her if she walks in the room. Suddenly the Type 1 and Type 2 errors are a whole lot more consequential. Modern NNs are simply not fit for that job. We have pretty good AI for low-consequence purposes, but it cannot be used for high-consequence purposes without a lot more fundamental research. Incremental improvements to deep learning are not going to get us there.
  - giardini 5y ago
    Wellllll, um, not really.... Any NN recognizer can be fooled and your neighbor's dog may as likely be shot by the "granny gun AI". You need to read up on the validity of facial recognition software. It ain't nearly human!