Hey "agi" (formerly Jim Bromer, just kidding buddy :) I like this comment of yours:
"The misunderstanding that a 'predictor' is the same as absolute > knowledge that is always right has no basis in the world that might be known > from common sense." This captures the tension between the mathematical-algorithmic-information-theory school and less mathematical psychology/philosophy approaches. People tend to fall in one school or the other. Mike A On 8/13/19, agi <[email protected]> wrote: > "Suppose you have a simple learner that can predict any computable sequence > of symbols with some probability at least as good as random guessing. Then I > can create a simple sequence that your predictor will get wrong 100% of > the time. My program runs a copy of your program and outputs something > different from your guess." > > This kind of program is an example of narrow AGI, and the application of the > theory as a proof that a universal learner is impossible is irrelevant. It > does not apply to all forms of knowledge, in particular, the kind of > knowledge that we work with all of the time. There is no basis that the > prediction made by a program like this could be absolutely right all of the > time. The misunderstanding that a 'predictor' is the same as absolute > knowledge that is always right has no basis in the world that might be known > from common sense. This is not a proof that a universal learner is > impossible because the foundation of knowledge is not the striving for > perfect knowledge of the future. ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T1ff21f8b11c8c9ae-M315ee1488b208c022e170412 Delivery options: https://agi.topicbox.com/groups/agi/subscription
