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Seems like a cool concept. At the same time, it seems like one encounters a fundamental problem with going from a deep learning paradigm to a learning paradigm

Seems like a cool concept. At the same time, it seems like one encounters a fundamental problem with going from a deep learning paradigm to a learning paradigm. For regular deep learning, you gather enough data to allow you to massive, brute-force curve-fitting that reproduces the patterns within the data. But even with this, you encounter problem of finding bogus patterns as well as useful patterns in the data and also the problem of the data changing over time. Now, in adding "learning to learning" approaches to deep learning, you are also do brute-force, curve-fitting to discover the transformation between data-pair or similar things that are involved in change, new-stuff arriving. But this too is dependent on the massive data-set, it might learn wrong-things and the kind of change involved might itself change. But that's a more fundamental problem for the learning-to-learn system, because these systems are the one that are expected to deal with new data. I've heard one-shot/zero-shot learning still hasn't found many applications for these reasons. Maybe the answer is systems using truly massive dataset like Gpt-3.

BobbyJo 5y ago
"Learning to learn" with massive amounts of data feels like it might be more inline with nature. Human learning is based on millions of different learning strategies that were encoded into the neurons of each of our ancestors and applied to billions and billions of lifetimes of data. The structure of our brain, and therefore how we learn, was itself learned over millions of generation of trial and error.
- joe_the_user 5y ago
  People every day deal with effectively with new and unknown situations. Some are new as in never-seen-before, some are new as in a variation of what came before and some are combination. Maybe it took millions of years to come up with this algorithm but it seems like the approach is more than just some long incremental thing. Deer are the product of millions of years of evolution also. Deer never learn to look both ways before cross a highway, though they can learn a significant number of other things.
  - space_fountain 5y ago
    I'm not sure what the point is. Are you saying that because deer don't have what you might call generalized intelligence a data driven learned approach can't or won't? I think most people agree that humans are smarter than deer and there is probably some importance to the conditions that molded us, but it still seems like our intelligence is still "just" the result of learning to learn
    - joe_the_user 5y ago
      "Are you saying that because deer don't have what you might call generalized intelligence a data driven learned approach can't or won't?" Won't necessarily, A data driven approach won't necessarily work. I'm sure that given the proper learn and virtually any "program" or algorithm, there's version data-driven training that would be able install such a program., so in the abstract data-driven training would able to do "anything". But you'd need to know what to do. But poster above said "Human learning is based on millions of different learning strategies that were encoded into the neurons of each of our ancestors". And it seems like many of those millions of years actually produced more narrow (if extremely powerful and impressive) behaviors while the generality of human intelligence is relatively more recent. Of course, human beings "learned to learn" somehow. It's just that I think it's plausible that a specific set of circumstances were necessary. I would say the evolution of both language and complex social interactions were part of this.
      - srean 5y ago
        I agree. Natural selection wields significant influence. Too much too soon and it may go extinct. If its just right, the intelligence to cross roads might give them a reproductive advantage.
  - BobbyJo 5y ago
    True, but the cost function deer are optimizing for diverged from our own millions of years ago. Whose to say how much of our intelligence comes from the prior epoch, and how much comes from the latter.

BobbyJo 5y ago

"Learning to learn" with massive amounts of data feels like it might be more inline with nature. Human learning is based on millions of different learning strategies that were encoded into the neurons of each of our ancestors and applied to billions and billions of lifetimes of data. The structure of our brain, and therefore how we learn, was itself learned over millions of generation of trial and error.

joe_the_user 5y ago
People every day deal with effectively with new and unknown situations. Some are new as in never-seen-before, some are new as in a variation of what came before and some are combination. Maybe it took millions of years to come up with this algorithm but it seems like the approach is more than just some long incremental thing. Deer are the product of millions of years of evolution also. Deer never learn to look both ways before cross a highway, though they can learn a significant number of other things.
- space_fountain 5y ago
  I'm not sure what the point is. Are you saying that because deer don't have what you might call generalized intelligence a data driven learned approach can't or won't? I think most people agree that humans are smarter than deer and there is probably some importance to the conditions that molded us, but it still seems like our intelligence is still "just" the result of learning to learn
  - joe_the_user 5y ago
    "Are you saying that because deer don't have what you might call generalized intelligence a data driven learned approach can't or won't?" Won't necessarily, A data driven approach won't necessarily work. I'm sure that given the proper learn and virtually any "program" or algorithm, there's version data-driven training that would be able install such a program., so in the abstract data-driven training would able to do "anything". But you'd need to know what to do. But poster above said "Human learning is based on millions of different learning strategies that were encoded into the neurons of each of our ancestors". And it seems like many of those millions of years actually produced more narrow (if extremely powerful and impressive) behaviors while the generality of human intelligence is relatively more recent. Of course, human beings "learned to learn" somehow. It's just that I think it's plausible that a specific set of circumstances were necessary. I would say the evolution of both language and complex social interactions were part of this.
    - srean 5y ago
      I agree. Natural selection wields significant influence. Too much too soon and it may go extinct. If its just right, the intelligence to cross roads might give them a reproductive advantage.
- BobbyJo 5y ago
  True, but the cost function deer are optimizing for diverged from our own millions of years ago. Whose to say how much of our intelligence comes from the prior epoch, and how much comes from the latter.