4 ms·

I know about enough ML to train a model. I cannot make sense of what the author means by symbol manipulation. Is there a good resource

melony 5y ago
Rules engines and GOFAIs, discrete algorithms.
r-zip 5y ago
By this (I think) the author just means logical rules. Think regular software.
- Jtsummers 5y ago
  More 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 ago
    Ah, 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 ago
  Aside 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 ago
    The 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?
octoberfranklin 5y ago
> I cannot make sense of what the author means by symbol manipulation. He means basically all of what was called "AI" between Minsky's days and the recent neural network renaissance (~2013ish). If you weren't in CS, or too young, before 2013, you probably don't remember this. Neural networks were extremely uncool for a very very long time. They were derided as "connectionist AI". LISP was created as an "AI language". If that seems weird to you, read up on the history, it will do you good. The history of CS is about as un-"modern" as it gets. Those who aren't aware of it are doomed to repeat it.
paradite 5y ago
I guess it's something similar to the concept of expert systems / rule-based system.
YeGoblynQueenne 5y ago
Yes, there is: Artificial Intelligence: A Modern Approach, 4th US ed. http://aima.cs.berkeley.edu/ http://aima.cs.berkeley.edu/ See Chapters I through IV.

melony 5y ago

Rules engines and GOFAIs, discrete algorithms.

r-zip 5y ago

By this (I think) the author just means logical rules. Think regular software.

Jtsummers 5y ago
More 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 ago
  Ah, 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 ago
Aside 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 ago
  The 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?

octoberfranklin 5y ago

> I cannot make sense of what the author means by symbol manipulation. He means basically all of what was called "AI" between Minsky's days and the recent neural network renaissance (~2013ish). If you weren't in CS, or too young, before 2013, you probably don't remember this. Neural networks were extremely uncool for a very very long time. They were derided as "connectionist AI". LISP was created as an "AI language". If that seems weird to you, read up on the history, it will do you good. The history of CS is about as un-"modern" as it gets. Those who aren't aware of it are doomed to repeat it.

paradite 5y ago

I guess it's something similar to the concept of expert systems / rule-based system.

YeGoblynQueenne 5y ago

Yes, there is: Artificial Intelligence: A Modern Approach, 4th US ed. http://aima.cs.berkeley.edu/ http://aima.cs.berkeley.edu/ See Chapters I through IV.