The federal threshold is 100 yottaflops. So figure a system with training hardware the equivalent of about a million Radeon 7900 XTXes.
I have to say that I’m not sure that the training capacity is likely the strongest metric to use – I think that you could probably generate human-level intelligence with a plain old desktop CPU in a reasonable amount of time, given the right software and available training information that exists in 2024 – but it also probably isn’t too intrusive and it’s an easy bar to evaluate.
Measuring how much data your brain stores is kinda hard – some of that is an encoding that has to provide for redundancy – but I don’t think that it’s too controversial to say that it’s probably within what a hard drive or at most a small array of drives can do today.
Estimates of the storage capacity of the brain vary from 10^10 to 10^15 binary digits. I incline to the lower values and believe that only a very small fraction is used for the higher types of thinking.
– Alan Turing, Computing Machinery and Intelligence
The brain probably stores around 10-100TB of data.
You can get a 10TB hard drive these days. So for training you’re talking about maybe touching every bit on a hard drive at least once. Question is how much actual computational work in preprocessing is required. Might not be a lot.
As for runtime, your brain does have a lot of parallel capacity, but it also has a “clock” on the order of 100 Hz, which isn’t all that fast at serial computation. A lot of problems are constrained by serial computation capacity, and you can trivially serialize any parallel computation, but cannot parallelize all serial computations.