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He couch surfed and wrote papers with others his entire life and became the most prolific published mathematician ever. He also loved to teach kids serious math and not underestimate their thinking.
Also I believe his name is pronounced like air-dish.
after going through the google docs for resources, i get a sense of some high level topics. however, i am confused about the current paradigms. are ml models being used to reduce the search space or as a way to let computers bring about serendipity?
it seems like these approaches are like graphing libraries or monte carlo sims that help the user see the bigger picture and then put in their own thinking.
My experience with CoPilot shows that it fails at the most simple logical tasks:
When presented with an integer sequence it often does not even recognize the number of elements given. It just claims that we are looking for the 10th element when the current sequence only has three. Results are also wrong all the time.
Spatial reasoning of CoPilot is not very good. I wonder if early expert systems written in the Lisp era would outperform it.
It fails at tasks that require textual awareness like palindromes.
What it does very well is confabulating bland short stories and poems. It is great at understanding the input questions.
All in all, I am more impressed with Wolfram Alpha, which looks more like a traditional expert system.