msri-math

We might have an entire cabinet with a secret stash of Hagoromo chalk at MSRI - a mathematician's dream!

You can find the Freakonomics podcast with John here, and the USA Today article here.

We live to make mathematicians happy - tea and snacks every day at 3pm, hiking trails and a view of the San Francisco Bay, and of course, an abundance of chalkboards and cozy nooks to gather round and talk math. The Fulltouch chalk is a special bonus. :)

We enjoy Numberphile, too. (No bias, of course.)

Terence Tao's blog post - excerpted below:

One of the secrets to mathematical problem solving is that one needs to place a high value on partial progress, as being a crucial stepping stone to fully solving the problem. This can be a rather different mindset than what one commonly sees in more "real world" situations such as business, sports, engineering, or politics, where actual success or failure often matters much more than what one can salvage from a partial success. I think the basic reason for this is that in the purely theoretical world of mathematics, there is basically a zero cost in taking an argument that partially solves a problem, and then combining it with other ideas to make a complete solution; but in the real world, it can be difficult, costly, or socially unacceptable to reuse or recycle anything that is (or is perceived to be) even a partial failure. [EDIT: as pointed out in comments, software engineering is an exception to this general rule, as it is almost as easy to reuse software code as it is to reuse a mathematical argument.]

For beginning maths students, who have not yet adopted the partial progress mindset, it is common to try a technique to solve a problem, find out that it "fails", and conclude that one needs to try a completely different technique (or to give up on the problem altogether). But in practice, what often happens is that one's first solution attempt is able to solve some portion of the problem, and one needs to then look to combine that argument with techniques that can solve complementary portions of the problem in order to reach the final solution. ...