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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 u
by bmh100 10y ago
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.
- jacquesm 10y agoGenetic algorithms are not neural nets though.
- xapata 10y agoAnd they're generally worse than simulated annealing.
- dkarapetyan 10y agoI 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.html 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.