In many industries cost decreases by some factor with every doubling of cumulative production. This is how solar eventually became economically viable.
I guess the cost-quality tradeoff makes AI progress even better described as that of a normal technology. As economies of scale reduce cost, they should also be increasing quality (somewhat interchangeably). It’s just harder to quantify, and so most of the discussion will be in terms of cost. But for the purposes of raising the ceiling on adoption (total addressable market), higher quality works as well as lower cost, so the lowering of costs is directly relevant.
In this framing, logarithmic improvement of quality with more resources isn’t an unusual AI-specific thing either. What remains is the inflated expectations for how quality should be improving cheaply (which is not a real thing, and so leads to the impressions of plateauing with AI, where for other technologies very slow quality improvement would be the default expectation). And Moore’s law of price-performance, which is much faster than economic growth. The economies of scale mostly won’t be able to notice the growth of the specific market for some post-adoption technology that’s merely downstream of the growth of the overall economy. But with AI, available compute would be growing fast enough to make a difference even post-adoption (in 2030s).
In many industries cost decreases by some factor with every doubling of cumulative production. This is how solar eventually became economically viable.
I guess the cost-quality tradeoff makes AI progress even better described as that of a normal technology. As economies of scale reduce cost, they should also be increasing quality (somewhat interchangeably). It’s just harder to quantify, and so most of the discussion will be in terms of cost. But for the purposes of raising the ceiling on adoption (total addressable market), higher quality works as well as lower cost, so the lowering of costs is directly relevant.
In this framing, logarithmic improvement of quality with more resources isn’t an unusual AI-specific thing either. What remains is the inflated expectations for how quality should be improving cheaply (which is not a real thing, and so leads to the impressions of plateauing with AI, where for other technologies very slow quality improvement would be the default expectation). And Moore’s law of price-performance, which is much faster than economic growth. The economies of scale mostly won’t be able to notice the growth of the specific market for some post-adoption technology that’s merely downstream of the growth of the overall economy. But with AI, available compute would be growing fast enough to make a difference even post-adoption (in 2030s).