• kredditacc@lemmygrad.ml
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    13 days ago

    Well just add more data points (7, 11, 13, etc) until the simplest solution is a prime solution. Would this program be smart enough to generate the right algorithm?

    Of course, an AI would just generate a prime algorithm because it’s well known, but not all problems are well known. In fact, most problems I’m solving everyday are not. So for the AI, it may as well be the prime lookup problem for Barliman.

    • cfgaussian@lemmygrad.ml
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      13 days ago

      That’s the problem with “AI” isn’t it? At least at the stage it is today. It can only really solve the kinds of problems that have already been solved. Maybe with some variations in the parameters, but the general structure of a problem needs to be one that it has already encountered in its training.

    • cfgaussian@lemmygrad.ml
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      13 days ago

      Well just add more data points (7, 11, 13, etc) until the simplest solution is a prime solution.

      As i said, i don’t know anything about this program, but conceptually i think you first need to define what you mean by “simplest solution”. Because at least for me a polynomial is the simplest solution regardless how many data points there are because then the problem is reducible to a set of linear equations that a computer can easily solve.

      However if we specify that the solution needs to be one with the lowest number of parameters possible, then it gets interesting. Then you can have an algorithm start to iteratively test solutions, and try to reduce complexity until it hopefully arrives at something resembling a prime number generator. Or it may not. I don’t know if this is even possible because one well known problem with the “gradient descent” approach is that your algorithm can get stuck in a local valley. It thinks it’s found the optimal solution but it’s stuck in a false minimum because it does not have the “imagination” to start to test an entirely different class of solutions that may at first be much less efficient.