How quickly are AI capabilities improving, and is there credible evidence that the pace of progress is slowing?

AI capabilities are improving rapidly, with sources describing "very fast improvements" [5] and ongoing advancements that are accelerating progress through feedback loops, such as AI writing code at companies like Anthropic, potentially leading to autonomous AI development within 1-2 years [3]. This growth is evident in AI's "spiky" intelligence, excelling in expert-level tasks across many areas while showing deficiencies in others [7], and causing market disruptions as capabilities expand [8]. However, the pace is not exponential; a METR report claiming such growth since 2019 is challenged by data showing no support for it, even short-term [1]. There is credible evidence suggesting the pace of progress may be slowing or hitting limits. Productivity gains remain scarce despite fast improvements and vast investments [2,10], with tensions arising from exploding costs outpacing returns [6]. Challenges like regulatory hurdles, talent shortages, and funding constraints could slow infrastructure expansion [11], and alternative AI approaches are emerging as large language models (LLMs) are seen as approaching a "wall," though this diversifies pathways forward [4]. Jagged abilities also limit short-term utility, tempering adoption speed [9].