A thread through the archive
Essays tagged “scaling laws”. Follow an idea across the archive.
Scott debunks the "all exponentials become sigmoids" argument against AI risk by showing how forecasters consistently predict premature flattening of exponential trends, and argues that without deep understanding of AI dynamics, we should expect current AI progress to continue for roughly as long as it's already been going.
Scott explains why Ajeya Cotra's influential 'Biological Anchors' report correctly predicted the AI scaling boom but got AGI timelines wrong by twenty years, due to severely underestimating the rate of algorithmic progress.
Scott Alexander examines GPT-3's capabilities, improvements over GPT-2, and potential implications for AI development through scaling.