Disclaimer: I don’t know anything about designing programming languages.
I don’t think this programming language can neatly precede the AI design, like your example of chesslang. In fact, it might be interesting to look at history to see which tended to come first—support for features in programming languages, or applications that implemented those features in a more roundabout way.
Like the proof reasoning support, for example, might or might not be in any particular AI design.
Another feature is support for reasoning about probability distributions, which shows up in probabilistic programming languages. Maybe your AI is a big neural net and doesn’t need to use your language to do its probabilistic reasoning.
Or maybe it’s some trained model family that’s not quite neural nets—in which case it’s probably still in python, using some packages designed to make it easy to write these models.
Basically, I think there are a lot of possible ways to end up with AI, and if you try to shove all of them into one programming language, it’ll end up bloated—your choice of what to do well has to be guided by what the AI design will need. Maybe just making good python packages is the answer.
Disclaimer: I don’t know anything about designing programming languages.
I don’t think this programming language can neatly precede the AI design, like your example of chesslang. In fact, it might be interesting to look at history to see which tended to come first—support for features in programming languages, or applications that implemented those features in a more roundabout way.
Like the proof reasoning support, for example, might or might not be in any particular AI design.
Another feature is support for reasoning about probability distributions, which shows up in probabilistic programming languages. Maybe your AI is a big neural net and doesn’t need to use your language to do its probabilistic reasoning.
Or maybe it’s some trained model family that’s not quite neural nets—in which case it’s probably still in python, using some packages designed to make it easy to write these models.
Basically, I think there are a lot of possible ways to end up with AI, and if you try to shove all of them into one programming language, it’ll end up bloated—your choice of what to do well has to be guided by what the AI design will need. Maybe just making good python packages is the answer.
I agree that if the AI is just big neural nets, python (or several other languages) are fine.
This language is designed for writing AI’s that search for proofs about their own behavior, or about the behavior of arbitrary pieces of code.
This is something that you “can” do in any programming language, but this one is designed to make it easy.
We don’t know for sure what AI’s will look like, but we can guess enough to make a language that might well be useful.