[brandoncarl]

While I'm following you ideologically, I'm not sure that this idea bears fruit in evidence. The computer science community still uses large numbers of algorithms (via libraries) that were written by academics, in peer-reviewed journals, in Fortran, in the 1970s.

Even currently, a tremendous amount of the cutting-edge work in optimization and others is done at the university level: METIS for graph partitioning, and convex optimization work being done by Stephen Boyd et al. They care deeply about the implementation because quality and speed of solution are of utmost importance. A number (like Geoffrey Hinton and Sebastian Thrun) have moved into the private sector, but after contributing a lot via academia.

[14113]

I thing the problem here is you're comparing apples to oranges - the people writing code in the 70's are not the same type of people teaching students to code now.

In the 70's it would have been physicists, mathematicians or engineers writing code to solve a problem for them and their colleagues. Their code needed to be maintainable so they could share it in their academic community, and get things done with it.

Today, the people teaching computer science view code as the proof of concept. Much of the work is in the idea behind the code, and the code is just proof that it can be implemented in practice - and most importantly, isn't designed to be actually used.

The idea that the code is just the proof of concept then carries over to the students, and the mindset becomes not, "let's build this thing to do X', but "can we build a thing, in way Y to do X".

[seanmcdirmid]

Have you ever seen Hinton's code before? It's all Matlab :) And when you are designing/prototyping algorithms, that is quite good enough.