智能爆炸的动力学
The Dynamics of Intelligence Explosions
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中文总结 AI 辅助
本文研究智能爆炸的动力学，发现奇异增长比经济学模型预期的更难实现，快于指数增长却无垂直渐近线的增长率被忽视，生成时间是决定智能爆炸行为的关键参数。
中文摘要 AI 辅助
AI正越来越多地被用于辅助AI研发。在特定条件下，这种反馈循环可能引发智能爆炸，使AI能力迅速升级。本文探究了最具爆炸性可能性的数学模型，以理解驱动该动力学的因素。研究表明，奇异增长（趋向垂直渐近线）比近期受经济学启发的模型所预期的更难实现，且存在一类重要但被忽视的增长率，其快于指数增长却不会导致垂直渐近线。本文指出，生成时间（完成一次反馈循环的时间）是被忽视的关键参数，对决定智能爆炸的行为起核心作用——除非生成时间迅速趋近于零，否则无法实现奇异增长。
英文摘要
AI is increasingly being used to help with AI R&D. Under certain conditions this feedback loop might be able to produce an intelligence explosion, with rapidly escalating AI capabilities. I explore the mathematics of the most explosive possibilities, with an eye to understanding what drives the dynamics. I show that singular growth (towards a vertical asymptote) is harder to achieve than would be expected from recent economics-inspired modelling, and that there is an important but neglected class of growth rates that are faster than exponential but don't lead to a vertical asymptote. I draw out the generation time (the time to go around the feedback loop) as a neglected parameter that plays a pivotal role in determining the behaviour of any intelligence explosion --- one cannot have singular growth unless the generation time rapidly approaches zero.
