Even more importantly, we only measured the AIs at software tasks and don’t know what the trend is for other domains like math or law, it could be wildly different.
You probably mention this somewhere, but I’ll ask here, are you currently researching whether these results hold for those other domains? I’m personally more interested about math than law.
It’s expensive to construct and baseline novel tasks for this (we spent well over $100k on human baselines) so what we are able to measure in the future depends on whether we can harvest realistic tasks that naturally have human data. You could do a rough analysis on math contest problems, say assigning GSM8K and AIME questions lengths based on a guess of how long expert humans take, but the external validity concerns are worse than for software. For one thing, AIME has much harder topics than GSM8K (we tried to make SWAA not be artificially easier or harder than HCAST); for another, neither are particularly close to the average few minutes of a research mathematician’s job.
You probably mention this somewhere, but I’ll ask here, are you currently researching whether these results hold for those other domains? I’m personally more interested about math than law.
It’s expensive to construct and baseline novel tasks for this (we spent well over $100k on human baselines) so what we are able to measure in the future depends on whether we can harvest realistic tasks that naturally have human data. You could do a rough analysis on math contest problems, say assigning GSM8K and AIME questions lengths based on a guess of how long expert humans take, but the external validity concerns are worse than for software. For one thing, AIME has much harder topics than GSM8K (we tried to make SWAA not be artificially easier or harder than HCAST); for another, neither are particularly close to the average few minutes of a research mathematician’s job.