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If everyone sophisticated enough to be on this site would just use the term “applied computational statistics” (even just in their own thoughts) instead of “dee

If everyone sophisticated enough to be on this site would just use the term “applied computational statistics” (even just in their own thoughts) instead of “deep learning” or AI, the world would be a better place. Gradient descent finds some fun minimia (my current venture is heavily based on that idea) but to assign more agency to Adam or RMSProp than they merit is just an exercise in feeding the trolls.

mbeex 7y ago
Couldn’t agree more. All these delusional discussions: Is it intelligence? Is it true intelligence? How far is it to become true...? Skynet rising? To be fair: The last question is certainly adequate regarding the application of unverified/-able algorithms in a life-changing incarnation as a virtually unsupervised decision making quality. This is horrible. But it is another question (and better answered skipping the pseudo-philosphical part)
YeGoblynQueenne 7y ago
Could you please explain in what sense deep learning is "applied computational statistics"? What about classical planning, SAT solvers, automated theorem proving, game-playing agents and classical search? Could you please explain how one or more of those are "applied computational statistics"? Further- I don't understand the comment about "agency". Could you clarify? Why is "agency" required for a technique or an algorithm to be considered an AI technique?
- plaidfuji 7y ago
  I don’t know anything about the underlying algorithms for the examples you rattled off, but deep learning trains a graph of neuron weights such that they are statistically optimized to minimize error in computed output labels for some domain of input data. Very much “applied computational statistics”.
  - YeGoblynQueenne 7y ago
    The examples I gave are classic AI algorithms that are very easy to look up on wikipedia. They do not compute any statistics. I'm not sure what you mean about "neuron weights that are statistically optimised". Modern-era, deep neural nets train their weights with backpropagation, which is basically an application of the chain rule, from calculus. They do not use statistics for that. For example, calculating the mean of a set of values or calculating the pearson correlation coefficient of two variables are computations typical in statistics. Could you please clarify what you mean by (applied) "computational statistics", so that I don't have to double-guess you? Edit: Do you really not know what a SAT solver is? Not to be rude but if that is the case, from where do you draw your confidence about the correct terminology to use for AI?
    - tnecniv 7y ago
      He means that neural networks are applied statistics in that they solve a statistical regression problem. It's not conceptually different from classical methods of regression like least squares. The phrase "statistically optimized" is certainly a funky one, but regression is certainly as much a part of statistics as the two problems you mentioned.
      - deleted 7y ago
        [deleted]
      - YeGoblynQueenne 7y ago
        That doesn't sound like what the OP was saying.
theferalrobot 7y ago
There are non-statistical methods for training neural nets (no backprop) so 'applied computational statistics' really wouldn't capture it. Beyond that what is wrong with the term deep learning? I can at least understand objections to the use of the term AI (even though it was originally used to refer to narrow AI but was appropriated by hollywood) but deep learning seems like a fine term to me.

mbeex 7y ago

Couldn’t agree more. All these delusional discussions: Is it intelligence? Is it true intelligence? How far is it to become true...? Skynet rising? To be fair: The last question is certainly adequate regarding the application of unverified/-able algorithms in a life-changing incarnation as a virtually unsupervised decision making quality. This is horrible. But it is another question (and better answered skipping the pseudo-philosphical part)

YeGoblynQueenne 7y ago

Could you please explain in what sense deep learning is "applied computational statistics"? What about classical planning, SAT solvers, automated theorem proving, game-playing agents and classical search? Could you please explain how one or more of those are "applied computational statistics"? Further- I don't understand the comment about "agency". Could you clarify? Why is "agency" required for a technique or an algorithm to be considered an AI technique?

plaidfuji 7y ago
I don’t know anything about the underlying algorithms for the examples you rattled off, but deep learning trains a graph of neuron weights such that they are statistically optimized to minimize error in computed output labels for some domain of input data. Very much “applied computational statistics”.
- YeGoblynQueenne 7y ago
  The examples I gave are classic AI algorithms that are very easy to look up on wikipedia. They do not compute any statistics. I'm not sure what you mean about "neuron weights that are statistically optimised". Modern-era, deep neural nets train their weights with backpropagation, which is basically an application of the chain rule, from calculus. They do not use statistics for that. For example, calculating the mean of a set of values or calculating the pearson correlation coefficient of two variables are computations typical in statistics. Could you please clarify what you mean by (applied) "computational statistics", so that I don't have to double-guess you? Edit: Do you really not know what a SAT solver is? Not to be rude but if that is the case, from where do you draw your confidence about the correct terminology to use for AI?
  - tnecniv 7y ago
    He means that neural networks are applied statistics in that they solve a statistical regression problem. It's not conceptually different from classical methods of regression like least squares. The phrase "statistically optimized" is certainly a funky one, but regression is certainly as much a part of statistics as the two problems you mentioned.
    - deleted 7y ago
      [deleted]
    - YeGoblynQueenne 7y ago
      That doesn't sound like what the OP was saying.

theferalrobot 7y ago

There are non-statistical methods for training neural nets (no backprop) so 'applied computational statistics' really wouldn't capture it. Beyond that what is wrong with the term deep learning? I can at least understand objections to the use of the term AI (even though it was originally used to refer to narrow AI but was appropriated by hollywood) but deep learning seems like a fine term to me.