When dealing with resources on the internet, you’re running into the “trading off something cheap for something expensive” issue again. I could *right now* spend several days/ weeks write a program that dynamically looks up how expensive it is to run some algorithm on arbitrary cloud providers and run on the cheapest one (or wait if the price is too high), but it would be much faster for me to just do a quick Google search and hard-code to the cheapest provider right now. They might not always be the cheapest but it’s probably not worth thousands of dollars of my time to optimize this more than that.
Regarding writing a program to dynamically lookup more complicated resources like algorithms and data.. I don’t know how you would do this without a general-purpose programmer-equivalent AI. I think maybe your view of programming seriously underestimates how hard this is. Probably 95% of data science is finding good sources of data, getting them into a somewhat-machine-readable-form, cleaning them up, and doing various validations that the data makes any sense. If it was trivial for programs to use arbitrary data on the internet, there would be much bigger advancements than agoric computing.
When dealing with resources on the internet, you’re running into the “trading off something cheap for something expensive” issue again. I could *right now* spend several days/ weeks write a program that dynamically looks up how expensive it is to run some algorithm on arbitrary cloud providers and run on the cheapest one (or wait if the price is too high), but it would be much faster for me to just do a quick Google search and hard-code to the cheapest provider right now. They might not always be the cheapest but it’s probably not worth thousands of dollars of my time to optimize this more than that.
Regarding writing a program to dynamically lookup more complicated resources like algorithms and data.. I don’t know how you would do this without a general-purpose programmer-equivalent AI. I think maybe your view of programming seriously underestimates how hard this is. Probably 95% of data science is finding good sources of data, getting them into a somewhat-machine-readable-form, cleaning them up, and doing various validations that the data makes any sense. If it was trivial for programs to use arbitrary data on the internet, there would be much bigger advancements than agoric computing.