
Program Induction and Synthesis at ICML 18 - gfrison1
https://gfrison.com/2018/08/02/program-induction-synthesis-icml-2018/
======
ArtWomb
>>> Neural networks belong to the differentiable realm, while code generation
belongs to the discrete

Even a GAN discriminator step to simulate or even compile and run generated
program may never produce the desired output. Getting 99.9% accuracy simply
won't do in this domain. Even down to the final curly bracket, the program
must be perfect.

Thing is we have an excellent model already. Composed of the architectures,
instruction sets, binaries and code. A massive search space for x86-64. But
perhaps solvable for 8-bit AVR on modern gpu cloud clusters.

------
catnaroek
Two words: loop invariant. Implement a system that figures out the right loop
invariant given a problem description (expressed however you want), and you
will have made a lot of progress.

