[bmh100]

It would actually be very straightforward to do so if the costs of testing solutions weren't so high. CPU architecture and JIT code can both be represented as unstructured (non-tabular) data. I even recall a circuit having been optimized by a genetic algorithm a while ago in an experiment. I also recall using LSTM to generate valid code from IIRC examples in Linux. Superiptimizatiom is also a relevant topic.

We just need better simulation tools or more resources.

[dkarapetyan]

I have also seen genetic algorithms used for these kinds of optimization problems. In fact there is a module in postgres that uses genetic algorithms to optimize query plans (https://www.postgresql.org/docs/9.6/static/geqo-pg-intro.htm...).

But I don't put genetic algorithms in the same bucket. Genetic algorithms are a different breed of optimization algorithm compared to neural nets and gradient descent which is what the modern crop of AI is basically all about.

[jacquesm]

Genetic algorithms are not neural nets though.

[xapata]

And they're generally worse than simulated annealing.