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By this (I think) the author just means logical rules. Think regular software.
by r-zip 5y ago
By this (I think) the author just means logical rules. Think regular software.
- Jtsummers 5y agoMore like classical AI, much of which, yes, has been subsumed under the category "regular software" (AI goalposts have always shifted, once a problem is solved, it's no longer AI and becomes "just" software). Think things like theorem provers.
- octoberfranklin 5y ago> once a problem is solved, it's no longer AI ... or remains unsolved despite grand AI promises. Also, when AI fall comes everybody quickly changes their resumes to say "ML" before AI winter arrives. Then they change things back in AI spring. And then the cycle repeats. All the CS professors tell their grad students about this cycle. Well, all of them except the AI faculty, who only tell their students about the part relevant to the current season.
- mannykannot 5y agoAh, the 'moving goalposts' argument. The thing is, though, if one makes that argument, then what position should you take on whether strong AI or AGI has been already achieved? If you say no, then you are tacitly acknowledging that the goalposts were in the wrong place. If, on the other hand, you say this is it, the naysayers will have good grounds to disagree, and say "told you so!" while doing so.
- fulafel 5y agoAside from what other replies said, there's also the statistics, learning and prediction (aka ML?) that's the basis of classic compression algorithms. In fact one of the current leading brain theories is named a lot like terminology from that world: https://en.wikipedia.org/wiki/Predictive_coding https://en.wikipedia.org/wiki/Predictive_coding
- r-zip 5y agoThe term "symbol" is indeed used in that context as well, but that's not what I took Marcus to mean in the article. Maybe I'm missing something?