4 ms·

Finding patterns in answers is solving problems.

• _0ffh 9y ago
  Maybe more precisely finding patterns in answers in relation to the inputs.
• freyir 9y ago
  But it doesn't show its work.
• TheOtherHobbes 9y ago
  No, it's not. Humans seem to solve problems with a combination of learned stock knowledge, induction, and constrained improvisation. Constrained improvisation is the most interesting part of that process, and the one we know least about. It's one thing building a system that asymptotically improves over millions of trials, and then sending out a press release claiming your system is as smart as a human. It's another building a system that learns a domain as efficiently as a human. Compare the relatively small number of games played/analysed by a Go master on their way to master status, compared with the number of simulated games played/analysed by AlphaGo. ML is still a rather naive form of constrained brute forcing. It's a long way short of efficient learning.
  • xapata 9y ago
    You're describing a technique for finding patterns. There are many possible techniques and machines can (probably) use any of them. The constraint would be if the technique involved kinetic or quantum mechanics.
  • digitalzombie 9y ago
    > ML is still a rather naive form of constrained brute forcing. It's a long way short of efficient learning. Uh... Bayesian can do the above at in term of expert domain. They call it elicitation in the Bayesian world. I think you're overall generalizing all learning techniques. And also it's not like we actually really know how the human brain learn. Psychology is a field with huge uncertainties and you can see that in their research papers with correlation values. So the concept of learning may be out dated and/or we are still learning about what makes us learn.