Title: "Why Math is (Still) Hard: Challenges in Mathematical Computing."

Abstract: Almost all interesting mathematical algorithmic questions relate to NP-hard questions and such computation is prone to explode exponentially. More space, more speed and processors, and even say massive parallelism will have an impact but it will be largely at a `micro not macro' level.

We anticipate the greatest benefit accruing from mathematical platforms that allow for highly computer assisted insight generation (more `aha's' per cycle), not from solution of grand challenge problems.

This talk is based on: J.M. Borwein and P.B. Borwein, ``Challenges in Mathematical Computing," Computing in Science & Engineering, May/June 3 (2001), 48-53.