AI brief
An analysis reports that the cost of reaching a fixed AI performance benchmark is falling about 13 times per year, while MIT estimates annual algorithmic progress at roughly 3 times after accounting for hardware gains and competition.
Why it matters: Rapidly falling costs to reach a given AI performance level could make AI capabilities cheaper to deploy over time.
Written by AI from The Decoder's published text. Read the original for full details.