谷歌：2026从通用人工智能（AGI）通向超级人工智能（ASI）的四条演进路径研究报告（英文版）（57页）.pdf

1、From AGI to ASITim Genewein1,Matija Franklin1,Alexander Lerchner1,Laurent Orseau1,Samuel Albanie1,Adam Bales1,ColeWyeth1,2,Stephanie Chan1,Iason Gabriel1,Joel Z.Leibo1,Allan Dafoe1,Marcus Hutter1,3,Thore Graepel1,4and Shane Legg11Google DeepMind,2University of Waterloo(work conducted while at Google

2、 DeepMind),3Australian National University,4University College LondonOver the last decade,building human-level artificial general intelligence has moved from far-fetchedspeculation to being a concrete next-decade target for many of the largest AI organisations.Achievingthis goal would have profound

3、and far-reaching impacts on human society,which raises many complexquestions for the decade ahead.This report investigates how AI itself might continue to develop in apost-AGI world along the continuum of machine intelligence.The endpoint of this continuum,UniversalAI,is theoretically well understoo

4、d,which provides some formal grounding for the main focus of thisreport:the transition from human-level AGI to artificial general superintelligence,which,intuitively,can be understood as a system that is more intelligent and cognitively capable than large organisationsof humans.After characterizing

5、ASI,the report discusses four potential pathways from AGI to ASI:scaling AGI,AI paradigm shifts,recursive improvement,and ASI emerging from large-scale multi-agent collectives.The report then discusses possible frictions and bottlenecks along these pathways.Determining whether the impact of these fr

6、ictions will be negligible or substantial raises a numberof concrete open research questions.Due to large uncertainties for predicting ASI progress,it cannotbe ruled out that AI progress might continue to accelerate over the next years.This could imply thatthe image of a single transformative step c