alt Hacker NewsWhere do the features come from, feature engineering? That's the method that failed the bitter lesson. Why would you use genetic programming when you can do gradient descent?
Where do the features come from, feature engineering? That's the method that failed the bitter lesson. Why would you use genetic programming when you can do gradient descent?
> Where do the features come from, feature engineering? That's the method that failed the bitter lesson.
That would be the whole point of genetic programming. You don't have to do feature engineering at all.
Genetic programming is a more robust interpretation of the bitter lesson than transformer architecture and DNNs. You have less clever tricks you need to apply to get the job done. It is more about unmitigated raw compute than anything out there.
In my experiments, there are absolutely zero transformation, feature engineering, normalization, tokenization, etc. It is literally:
1. Copy input byte sequence to program data region
2. Execute program
3. Copy output byte sequence from program data region
Half of this problem is about how you search for the programs. The other half is about how you measure them. There isn't much other problem to worry about other than how many CPUs you have on hand.