Ben Goertzel <[email protected]> wrote: Regarding Solomonoff induction, it's the conceptual basis underlying any work done in machine learning that uses a simplicity bias (e.g. MOSES with an Occam bias ... any Minimum Description Length work, etc.). I don't think it's the golden path to AGI but it's certainly relevant.
The combination of a compression method with a learning and recognition method is interesting. I think that is something that is needed. But, I do not think that Solomonoff induction or neural networks are strong enough. Solomonoff Induction is a general method to compress narrow reference objects. Ok, if it were a feasible AGI method that might mean that other applications of the reference could be used to refer to greater collections of relevant material but there are obvious contradictions that supposition. It is as if you can understand what I am saying but just refuse to spend the time to think about it. Jim Bromer ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
