4 ms·

Philosophy and Theoretical Computer Science (MIT Course 6.893)

52 points by nadahalli 15y ago

madamepsychosis 15y ago
Also mentioned here: http://www.scottaaronson.com/blog/?p=755 http://www.scottaaronson.com/blog/?p=755
michaelchisari 15y ago
It's days like these I wish I went to MIT. Here's to hoping this shows up on OpenCourseWare.
- amalcon 15y ago
  No kidding. I've been thinking about this sort of thing ever since I first learned that there was such a thing as computation theory, but I've never heard of any proper treatment of the various subjects.
- reemrevnivek 15y ago
  Looks like a no on that front: The professor has said in comments to his blog that he will not. http://www.scottaaronson.com/blog/?p=755#comment-27693 http://www.scottaaronson.com/blog/?p=755#comment-27693. > Regarding recording, the main concern was that I didn’t want to inhibit open-ended discussion by recording everyone’s umms, uhhs, and half-baked thoughts for posterity. In addition, there didn’t seem like a pressing need for recording, since I’ve already essentially written a “course textbook” in the form of my essay (http://www.scottaaronson.com/papers/philos.pdf http://www.scottaaronson.com/papers/philos.pdf). But as I said, we will have student reaction essays for each class session and they will go up on the website.
mtraven 15y ago
Looks really interesting, but seems limited (maybe wisely) to analytic philosophy. There is a whole strain of work from the 80s that was partly inspired by Heidegger and phenomenology AND the realization that some classical AI problems were computationally intractable. This work was controversial, to say the least, but influential in its way. I'd suggest that any course on this topic ought to at least touch on this work. http://mit.dspace.org/bitstream/handle/1721.1/6947/AITR-802.pdf http://mit.dspace.org/bitstream/handle/1721.1/6947/AITR-802.... http://leidlmair.at/doc/WhyHeideggerianAIFailed.pdf http://leidlmair.at/doc/WhyHeideggerianAIFailed.pdf
- mshron 15y ago
  I can see why the Dreyfus article would be controversial, but so far (first ten pages or so) I found it very enlightening. This really struck a chord with me: > What the learner acquires through experience is not represented at all but is presented to the learner as more and more finely discriminated situations, and, if the situation does not clearly solicit a single response or if the response does not produce a satisfactory result, the learner is led to further refine his discriminations, which, in turn, solicit more refined responses. Comparing that to the meaning of "learn" commonly used in ML to mean "finding optimal weights for some features" and you can see the gulf pretty starkly.

52 points by nadahalli 15y ago

madamepsychosis 15y ago

Also mentioned here: http://www.scottaaronson.com/blog/?p=755 http://www.scottaaronson.com/blog/?p=755

michaelchisari 15y ago

It's days like these I wish I went to MIT. Here's to hoping this shows up on OpenCourseWare.

amalcon 15y ago
No kidding. I've been thinking about this sort of thing ever since I first learned that there was such a thing as computation theory, but I've never heard of any proper treatment of the various subjects.
reemrevnivek 15y ago
Looks like a no on that front: The professor has said in comments to his blog that he will not. http://www.scottaaronson.com/blog/?p=755#comment-27693 http://www.scottaaronson.com/blog/?p=755#comment-27693. > Regarding recording, the main concern was that I didn’t want to inhibit open-ended discussion by recording everyone’s umms, uhhs, and half-baked thoughts for posterity. In addition, there didn’t seem like a pressing need for recording, since I’ve already essentially written a “course textbook” in the form of my essay (http://www.scottaaronson.com/papers/philos.pdf http://www.scottaaronson.com/papers/philos.pdf). But as I said, we will have student reaction essays for each class session and they will go up on the website.

mtraven 15y ago

Looks really interesting, but seems limited (maybe wisely) to analytic philosophy. There is a whole strain of work from the 80s that was partly inspired by Heidegger and phenomenology AND the realization that some classical AI problems were computationally intractable. This work was controversial, to say the least, but influential in its way. I'd suggest that any course on this topic ought to at least touch on this work. http://mit.dspace.org/bitstream/handle/1721.1/6947/AITR-802.pdf http://mit.dspace.org/bitstream/handle/1721.1/6947/AITR-802.... http://leidlmair.at/doc/WhyHeideggerianAIFailed.pdf http://leidlmair.at/doc/WhyHeideggerianAIFailed.pdf

mshron 15y ago
I can see why the Dreyfus article would be controversial, but so far (first ten pages or so) I found it very enlightening. This really struck a chord with me: > What the learner acquires through experience is not represented at all but is presented to the learner as more and more finely discriminated situations, and, if the situation does not clearly solicit a single response or if the response does not produce a satisfactory result, the learner is led to further refine his discriminations, which, in turn, solicit more refined responses. Comparing that to the meaning of "learn" commonly used in ML to mean "finding optimal weights for some features" and you can see the gulf pretty starkly.