I’m trying to look at how increasing model time-horizons amplifies AI researcher productivity, for example, if a researcher had a programming agent which could reliably complete programming tasks of length up to a week, would the researcher be able to just automate 1000s of experiments in parallel using these agents? Like, come up with a bunch of possibly-interesting ideas and just get the agent to iterate over a bunch of variations of each idea? Or are experiments overwhelmingly compute constrained rather than programming-time constrained?
I’m trying to look at how increasing model time-horizons amplifies AI researcher productivity, for example, if a researcher had a programming agent which could reliably complete programming tasks of length up to a week, would the researcher be able to just automate 1000s of experiments in parallel using these agents? Like, come up with a bunch of possibly-interesting ideas and just get the agent to iterate over a bunch of variations of each idea? Or are experiments overwhelmingly compute constrained rather than programming-time constrained?