norvig

Thanks for the comment, brockf. I'm sorry the essay didn't make sense to you. Let me try again on a few points.

Are you saying that one statistical error in a probabilistic model makes the entire model wrong? Then you'd equally have to say that one logical error in a categorical model makes it equally wrong. And manifestly, there are many logical errors in all grammars. So I'm not sure what your point is here.

I'm interested to know: I quoted Chomsky: "That's a notion of [scientific] success that's very novel. I don't know of anything like it in the history of science." Do you agree with him? If so, do you judge all the Science and Cell articles as not being about accurately modeling the world and only about providing insight? Or do you think Chomsky meant something else by that?

I understand that there are two goals, accurately representing the world, and finding satisfactorily simple explanations. I think Chomsky has gone too far in ignoring the first, but I acknowledge that both are part of science. I further think that statistical/probabilistic models of language are better for both goals. This is obvious to me after working on the problem for 30 years, so maybe it is hard for me to explain why. I think Manning, Pereira, Abney, and Lappin/Shreiber do a good job of it. Also, I don't see how a system that successfully learns language could be anything other than statistical and probabilistic. I agree it is a long ways away ...

-Peter Norvig

Sorry about the intermittent access. My hosting service provides me with sufficient bandwidth, but only provides a version of Apache that forks a new process for every GET, and thus runs out of processes and denies access to a portion of visitors when I get slashdotted/redditted/hacker-newsified. If anyone can suggest a more reasonable hosting service, let me know. -Peter Norvig

Yes. I've been meaning to update the aima-python code to the third edition and finish the unfinished bits. Volunteers to help would be greatly appreciated.

Oh come on ... the right question is http://www.wolframalpha.com/input/?i=ceil%28log2+%28+%28dist... , to which the answer is of course: 42

I think Ravi and Ciaran and the other contributors have done a great job with this project, and I thank them for their efforts. If you are interested in AI, and if you program in Java, then probably it will be worth your time to take a look at this project. That is true whether you regard Java as a 60-pound weight or as the greatest thing since sliced bread. Remember, a programming language is just a tool, not a religion.

Peter Norvig here. I came to Python not because I thought it was a better/acceptable/pragmatic Lisp, but because it was better pseudocode. Several students claimed that they had a hard time mapping from the pseudocode in my AI textbook to the Lisp code that Russell and I had online. So I looked for the language that was most like our pseudocode, and found that Python was the best match. Then I had to teach myself enough Python to implement the examples from the textbook. I found that Python was very nice for certain types of small problems, and had the libraries I needed to integrate with lots of other stuff, at Google and elsewhere on the net.

I think Lisp still has an edge for larger projects and for applications where the speed of the compiled code is important. But Python has the edge (with a large number of students) when the main goal is communication, not programming per se.

In terms of programming-in-the-large, at Google and elsewhere, I think that language choice is not as important as all the other choices: if you have the right overall architecture, the right team of programmers, the right development process that allows for rapid development with continuous improvement, then many languages will work for you; if you don't have those things you're in trouble regardless of your language choice.