Curiously, humans don't seem to require reading the entire internet in order to perform at human level on a wide variety of tasks... Nature suggests that there's a lot of headroom in algorithms for learning on existing sources. Indeed, we had models trained on the whole internet a couple years ago, now, yet model quality has continued to improve.
Meanwhile, on the hardware side, transistor counts in GPUs are in the tens of billions and still increasing steadily.
This is a time horizon thing though. Over the course of future human history AI development might look exponential but that doesn’t mean there won’t be significant plateaus. We don’t even fully understand how the human brain works so whilst the fact it does exist strongly suggests it’s replicable (and humans do it naturally) that doesn’t make it practical in any time horizon that matters to us now. Nor does there seem to be fast movement in that direction since everyone is largely working on the same underlying architecture that isn’t similar to the brain.
Meanwhile, on the hardware side, transistor counts in GPUs are in the tens of billions and still increasing steadily.