2025+中国学界对大语言建模的采购性思考人用工智能+AGI+的多渠道调查研究报告(英)-29正式版

ExecutiveSummaryLargelanguagemodelshavegarneredinterestworldwideowingtotheirremarkableabilityto“generate”human-likeresponsestonaturallanguagequeries—athresholdthatatonetimewasconsidered“proof”ofsentience—andperformothertime-savingtasks.Indeed,LLMsareregardedbymanyasa,orthe,pathwaytogeneralartificialintelligence(GAI)—thathypothesizedstatewherecomputersreach(orevenexceed)humanskillsatmostoralltasks.ThelureofachievingAI’sholygrailthroughLLMshasdrawninvestmentinthebillionsofdollarsbythosefocusedonthisgoal.IntheUnitedStatesandEuropeespecially,bigprivatesectorcompanieshaveledthewayandtheirfocusonLLMshasovershadowedresearchonotherapproachestoGAI,despiteLLM’sknowndownsidessuchascost,powerconsumption,unreliableor“hallucinatory”output,anddeficitsinreasoningabilities.Ifthesecompanies’betsonLLMsfailtodeliveronexpectationsofprogresstowardGAI,westernAIdevelopersmaybepoorlypositionedtorapidlyfallbackonalternateapproaches.Incontrast,Chinafollowsastate-driven,diverseAIdevelopmentplan.LiketheUnitedStates,ChinaalsoinvestsinLLMsbutsimultaneouslypursuesalternatepathstoGAI,includingthosemoreexplicitlybrain-inspired.ThisreportdrawsonpublicstatementsbyChina’stopscientists,theirassociatedresearch,andonPRCgovernmentannouncementstodocumentChina’smultifacetedapproach.TheChinesegovernmentalsosponsorsresearchtoinfuse“values”intoAIintendedtoguideautonomouslearning,provideAIsafety,andensurethatChina’sadvancedAIreflectstheneedsofthepeopleandthestate.ThisreportconcludesbyrecommendingU.S.governmentsupportforalternativegeneralAIprogramsandforcloserscrutinyofChina’sAIresearch.CenterforSecurityandEmergingTechnology|17.JINFeihu(金飞虎),ZHANGJiajun(张家俊),“UnifiedPromptLearningMakesPre-trainedLanguageModelsBetterFew-shotLearners,”IEEEInternationalConferenceonAcoustics,SpeechandSignalProcessing,June2023.8.LIHengli(李珩立),ZHUSongchun(朱松纯),ZHENGZilong(郑子隆),“DiPlomat:ADialogueDatasetforSituatedPragmaticReasoning,”37thConferenceonNeuralInformationProcessingSystems(NeurIPS2023).9.LIJiaqi(李佳琪),ZHENGZilong(郑子隆),ZHANGMuhan(张牧涵),“LooGLE:CanLong-ContextLanguageModelsUnderstandLongContext?”arXivpreprintarXiv:2311.04939v1(2023).10.LIYuanchun(李元春),ZHANGYaqin(张亚勤),LIUYunxin(刘云新),“PersonalLLMAgents:InsightsandSurveyabouttheCapability,EfficiencyandSecurity,”arXivpreprintarXiv:2401.05459v2(2024).11.MAYuxi(马煜曦),ZHUSongchun(朱松纯),“BraininaVat:onMissingPiecestowardsArtificialGeneralIntelligenceinLargeLanguageModels,”arXivpreprintarXiv:2307.03762v1(2023).12.NIBolin(尼博琳),PENGHouwen(彭厚文),CHENMinghao,ZHANGSongyang(张宋扬),LINGHaibin(凌海滨),“ExpandingLanguage-imagePretrainedModelsforGeneralVideoRecognition,”arXivpreprintarXiv:2208.02816v1(2022).13.PENGYujia(彭玉佳),ZHUSongchun(朱松纯),“TheTongTest:EvaluatingArtificialGeneralIntelligencethroughDynamicEmbodiedPhysicalandSocialInteractions,”Engineering34,(2024).14.SHENGuobin(申国斌),ZENGYi(曾毅),“Brain-inspiredNeuralCircuitEvolutionforSpikingNeuralNetworks,”PNAS39(2023).15.TANGXiaojuan(唐晓娟),ZHUSongchun(朱松纯),LIANGYitao(梁一韬),ZHANGMuhan(张牧涵),“LargeLanguageModelsAreIn-contextSemanticReasonersRatherthanSymbolicReasoners,”arXivpreprintarXiv:2305.14825v2(2023).16.WANGJunqi(王俊淇),PENGYujia(彭玉佳),ZHUYixin(朱毅鑫),FANLifeng(范丽凤),“EvaluatingandModelingSocialIntelligence:aComparativeStudyofHumanandAICapabilities,”arXivpreprintarXiv:2405.11841v1(2024).17.XUFangzhi(徐方植),LIUJun(刘军),ErikCambria,“AreLargeLanguageModelsReallyGoodLogicalReasoners?”arXivpreprintarXiv:2306.09841v2(2023).18.XUZhihao(徐智昊),DAIQionghai(戴琼海),FANGLu(方璐),“Large-scalePhotonicChipletTaichiEmpowers160-TOPS/WArtificialGeneralIntelligence,”Science,April2024.19.YUANLuyao(袁路遥),ZHUSongchun(朱松纯),“CommunicativeLearning:aUnifiedLearningFormalism,”Engineering,March2023.CenterforSecurityandEmergingTechnology|1120.ZHANGChi(张驰),ZHUYixin(朱毅鑫),ZHUSongchun(朱松纯),“Human-levelFew-shotConceptInductionthroughMinimaxEntropyLearning,”ScienceAdvances,April2024.21.ZHANGTielin(张铁林),XUBo(徐波),“ABrain-inspiredAlgorithmthatMitigatesCatastrophicForgettingofArtificialandSpikingNeuralNetworkswithLowComputationalCost,”ScienceAdvances,August2023.22.ZHANGYue(章岳),CUILeyang(崔乐阳),SHIShuming(史树明),“Siren’sSongintheAIOcean:aSurveyonHallucinationinLargeLanguageModels,”arXivpreprintarXiv:2309.01219v2(2023).23.ZHAOZhuoya(赵卓雅),ZENGYi(曾毅),“ABrain-inspiredTheoryofMindSpikingNeuralNetworkImprovesMulti-agentCooperationandCompetition.”Patterns,August2023.24.ZOUXu(邹旭),YANGZhilin(杨植麟),TANGJie(唐杰),“ControllableGenerationfromPre-trainedLanguageModelsviaInversePrompting,”arXivpreprintarXiv:2103.10685v3(2021).ThestudiescollectivelyaddressthelitanyofLLMdeficitsdescribedinthispaper’ssections1and2,namely,thoseassociatedwiththeoryofmind(ToM)failures,inductive,deductive,andabductivereasoningdeficits,problemswithlearningnewtasksthroughanalogytoprevioustasks,lackofgrounding/embodiment,unpredictabilityoferrorsandhallucinations,lackofsocialintelligence,insufficientunderstandingofreal-worldinput,inparticularinvideoform,difficultyindealingwithlargercontexts,challengesassociatedwiththeneedtofinetuneoutputs,andcostofoperation.Proposedsolutionstotheseproblemsrangefromaddingmodules,emulatingbrainstructureandprocesses,rigorousstandardsandtesting,andreal-worldembedding,toreplacingthecomputingsubstrateoutrightwithimprovedchiptypes.SeveralprominentChinesescientistscitedinthisstudy’ssection2,whomadepublicstatementssupportingalternateGAImodels,includingTangJie,ZhangYaqin,XuBo,ZhuSongchun,andZengYi,areonthebylinesofmanyofthesepapers,addingauthenticitytotheirdeclarations.Inaddition,virtuallyallofChina’stopinstitutionsandcompaniesengagedinGAIresearch,includingtheBeijingAcademyofArtificialIntelligence(北京智源人工智能研究院),theBeijingInstituteforGeneralArtificialIntelligence(北京通用人工智能研究院),theChineseAcademyofSciences’InstituteofAutomation(中国科学院自动化研究所),PekingUniversity(北京大学),TsinghuaUniversity(清华大学),UniversityofChineseCenterforSecurityandEmergingTechnology|12AuthorsWilliamC.HannasisCSET’sleadanalystandformerlytheCIA’sseniorexpertforChinaopen-sourceanalysis.HeiscurrentlyfocusedonU.S.-Chinatechnologycompetition,communityoutreach,anddatadiscoverymethodologies.Huey-MeeiChangisCSET’sseniorChinaS&Tspecialist,co-editorofChinesePowerandArtificialIntelligence:PerspectivesandChallenges(Routledge,2023),andco-authorofseveralpapersonChina’sAIdevelopment.MaximilianRiesenhuber,PhD,isprofessorofneuroscienceatGeorgetownUniversityandcodirectorofitsCenterforNeuroengineering.HisresearchfocusesonunderstandingbrainfunctionandhowtheseinsightscanbetranslatedtoaugmentedcognitionapplicationsandneuromorphicAI.DanielH.ChouisadatascientistatCSET.Hehascollected,enhanced,andanalyzeddataformultiplestudiesonChinaAIandtechnologydevelopmentwhilesupportinggovernmentandprivatesectorprojects.AcknowledgementsTheauthorsaregratefultoCSET’sHelenToner,whoservedas“redteamer,”andtoJohnChenoftheRANDCorporationandDr.MikeWolmetzofJohnsHopkinsUniversity’sAppliedPhysicsLaboratoryforservingasoutsidereviewers.TheauthorsarealsogratefultoCSET’sDr.IgorMikolic-Torriera,Dr.CatherineAiken,MatthewMahoney,SheltonFitch,andBenMurphyfortheirgeneroussupportduringthereviewandpublicationprocess.©2025bytheCenterforSecurityandEmergingTechnology.ThisworkislicensedunderaCreativeCommonsAttribution-NonCommercial4.0InternationalLicense.Toviewacopyofthislicense,visit/licenses/by-nc/4.0/.DocumentIdentifier:doi:10.51593/20230048CenterforSecurityandEmergingTechnology|19Endnotes1Wm.C.Hannas,Huey-MeeiChang,CatherineAiken,DanielChou,“ChinaAI-BrainResearch,”(CenterforSecurityandEmergingTechnology,September2020),50,/publication/china-ai-brain-research/.2Weavoidtheterm“artificialgeneralintelligence”(AGI)hereduetoitshistoricalassociationwithfeaturesofbiologicalbrainsandminds(suchasemotionalandsocialintelligence,affect,consciousness)thatmayormaynotbenecessaryelementsofa“general”AI.SeeWm.C.Hannas,Huey-MeeiChang,DanielChou,BrianFleeger,“China’sAdvancedAIResearch,”(CSET,July2022),1-3,foradescriptionoftheterminologicalambiguitieswith“AGI”overallandasrelatestoChina,/publication/chinas-advanced-ai-research/.ThestandardChineseterm通用人工智能

equatesliterallyto“generalartificialintelligence.”AsummaryofrecentChinesepolicydocumentsissuedbytheCentrefortheGovernanceofAInoteseditoriallythat“通用人工智能

issometimes,dependingoncontext,translatedas‘artificialgeneralintelligence’(AGI),sometimesas‘generalartificialintelligence,’andsometimesas‘general-purposeartificialintelligence’.”Thisdescriptiongelswithourownobservations.FynnHeide,“BeijingPolicyInterestinGeneralArtificialIntelligenceIsGrowing,”(CentrefortheGovernanceofAI,June8,2023),ernance.ai/post/beijing-policy-interest-in-general-artificial-intelligence-is-growing.3GeoffreyHinton,conversationwithJoelHellermark,April2024,/watch?v=tP-4njhyGvo&t=660s.4RobertHart,“Meta’sAIChief:AIModelsLikeChatGPTWon’tReachHumanIntelligence,”Forbes,May22,2024,/sites/roberthart/2024/05/22/metas-ai-chief-ai-models-like-chatgpt-wont-reach-human-intelligence/.5BenGoertzel,TheConsciousnessExplosion(prepublicationcopy,2024),12.“Thissortoftechnology[largelanguagemodels],onitsown,seemsclearlynotcapableofproducingHLAGI[human-levelAGI]butitdoesseemverypromisingasacomponentofintegratedmulti-moduleAGIsystems.”Alsosee,TWIMLAIPodcast(09:03),/watch?v=MVWzwIg4Adw&list=TLPQMDUwODIwMjPPUBk12t2hDg&index=8.6“In2023venture-capitalinvestorspouredover$36bnintogenerativeAI,morethantwiceasmuchasin2022.”GuyScriven,“GenerativeAIWillGoMainstreamin2024,”TheEconomist,November13,2023,/the-world-ahead/2023/11/13/generative-ai-will-go-mainstream-in-2024.7JonKleinbergandManishRashavan,“AlgorithmicMonocultureandSocialWelfare,”PNAS118,no.22(February2021),/doi/10.1073/pnas.2018340118.8Hannas,Chang,Chou,andFleeger,“China’sAdvancedAIResearch.”9Huey-MeeiChang,“China’sBidtoLeadtheWorldinAI,”TheDiplomat,July6,2024,/2024/07/chinas-bid-to-lead-the-world-in-ai/.CenterforSecurityandEmergingTechnology|2010“Bigdata,smalltask”referstothedesignphilosophyofLLMs,whicharetrainedonlargedatasets(ontheorderoftrillionsof“tokens”)withasimpletask,viz.topredictthenextwordinatext.ThisisincontrasttotraditionalAIsystemstrainedonspecifictaskssuchasrecognizingfaces,witharchitecturesoptimizedfortheproblemdomain—whichenabledthesesystemstolearnfromsmallerdatasets.11Notethatthescopeofthisreportislimitedtotext-basedmodels.Yet,allconsiderationsregardingtext-basedLLMsaspathstoGAIalsodirectlyapplytotheirmultimodalextensionsthatprocessnotjusttextbutalsoimages,videoandaudio,whicharedifferencesininput/outputmodalitiesthatdonotfundamentallyaugmentthemodels’“intelligence.”12AshishVaswani,NoamShazeer,NikiParmar,JakobUszkoreit,etal.,“AttentionIsAllYouNeed,”arXivpreprintarXiv:1706.03762v7(2023).13KyleMahowald,AnnaA.Ivanova,IdanA.Blank,NancyKanwisher,etal.,“DissociatingLanguageandThoughtinLanguageModels,”TrendsinCognitiveSciences28,no.6(March2024);BoshiWang,XiangYue,HuanSun,“CanChatGPTDefenditsBeliefinTruth?EvaluatingLLMReasoningviaDebate,”FindingsoftheAssociationforComputationalLinguistics,EMNLP(2023).14NouhaDziri,XimingLu,MelanieSclar,XiangLorraineLi,etal.,“FaithandFate:LimitsofTransformersonCompositionality,”37thConferenceonNeuralInformationProcessingSystems,NeurIPS(2023).15E.g.,WolframGPT.See/.16S.M.Rivera,A.L.Reiss,M.A.EckertandV.Menon,“DevelopmentalChangesinMentalArithmetic:EvidenceforIncreasedFunctionalSpecializationintheLeftInferiorParietalCortex,”CerebralCortex15(November2005).17GeoffreyHinton,conversationwithJoelHellermark.18WinnieStreet,JohnOliverSiy,GeoffKeeling,AdrienBaranes,etal.,“LLMsAchieveAdultHumanPerformanceonHigh-orderTheoryofMindTasks,”arXivpreprintarXiv:2405.18870v2(2024).19TomerD.Ullman,“LargeLanguageModelsFailonTrivialAlterationstoTheory-of-MindTasks,”arXivpreprintarXiv.2302.08399v5(2023).20JieHuang,XinyunChen,SwaroopMishra,HuaixiuStevenZheng,etal.,“LargeLanguageModelsCannotSelf-CorrectReasoningYet,”arXivpreprintarXiv:2310.01798v1(2023).21LexinZhou,WoutSchellaert,FernandoMartinez-Plumed,YaelMoros-Daval,etal.,“LargerandMoreInstructableLanguageModelsBecomeLessReliable,”Nature,September25,2024.22Chaeffer,BrandoMiranda,SanmiKoyejo,“AreEmergentAbilitiesofLargeLanguageModelsaMirage?”37thConferenceonNeuralInformationProcessingSystems,NeurIPS(2023).23AdriandeWynter,“Awes,Laws,andFlawsfromToday’sLLMResearch,”arXivpreprintarXiv:2408.15409v2(2024).CenterforSecurityandEmergingTechnology|2124WhileLLMsexcelonstandardizedteststhataresimilartothoseinitsmassivetrainingset(e.g.,theSATorthebarexam),recentresearchhasshownthatfiguringoutnoveltasksbasedononeortwoexamples—somethinghumansarequitegoodat—continuestopresentachallengeforLLMs.Forinstance,theinfluential“AbstractionandReasoningCorpus”notesthathumanscansolveanaverageof80%ofARC’spatternmatchingtasks,whilethebestAIsystemsperformataround30%,https://lab42.global/arc/.25Goertzel,“GenerativeAIvs.AGI:TheCognitiveStrengthsandWeaknessesofModernLLMs,”arXivpreprintarXiv:2309.10371v1(2023),63.26DougLenatandGaryMarcus,“GettingfromGenerativeAItoTrustworthyAI:WhatLLMsMightLearnfromCyc,”arXivpreprintArXiv:2308:04445(2023).27JuliaAngwin,“PressPauseontheSiliconValleyHypeMachine,”TheNewYorkTimes,May15,2024,/2024/05/15/opinion/artificial-intelligence-ai-openai-chatgpt-overrated-hype.html.28DwarkeshPatel,“FrancoisChollet,MikeKnoop–LLMsWon’tLeadtoAGI-$1,000,000PrizetoFindTrueSolution,”DwarkeshPodcast,June11,2024.Cholletadded“IseeLLMsasmoreofanoff-ramponthepathtoAGIactually.AllthesenewresourcesareactuallygoingtoLLMsinsteadofeverythingelsetheycouldbegoingto.”/p/francois-chollet.29LiuYangnan(刘杨楠),“BeforeAchievingAGI,GlobalAILeadersAreArguingoverThese4KeyIssues”(实现

AGI之前，全球

AI大佬在这

4个关键问题上吵起来了),S(搜狐),June13,2023,/a/684748834_100016644.30Zhipu(智谱)wasfoundedin2019,hasastaffof800,andamarketvaluationof$2.5billionasofMay2024.ItranksatthetopofChina’s260generativeAIcompanies.EleanorOlcott,“FourStart-upsLeadChina’sRacetoMatchOpenAI’sChatGPT,”FinancialTimes,May2,2024,/content/4e6676c8-eaf9-4d4a-a3dc-71a09b220bf8.31BAAI(北京智源人工智能研究)wasfoundedin2018byHuangTiejun(seebelow),vice-deanatPekingUniversity’sInstituteforArtificialIntelligence(人工智能研究院),withagoalofbuildingstrongAI./research_report/5f44cbf13c99ce0ab7bc8db9?download=false.32SeeTangJie’sCVat/jietang/.33CelesteBiever,“Chian’sChatGPT:WhyChinaIsBuildingItsOwnAIChatbots,”Nature,May22,2024,/articles/d41586-024-01495-6.34Aruleofthumb,similartoMoore’sLawforsemiconductordensity,whichholdsthatthepowerofaneuralnetworkincreasesinproportiontoitssize,trainingdata,andcomputationalresources.CenterforSecurityandEmergingTechnology|2235“TsinghuaUniversity’sTangJie:FromGPTtoGPTZeroWillBeaMajorMilestoneThisYear”(清华大学唐杰:从

GPT到

GPTZero会是今年重大阶段性成果),TencentNetwork(腾讯网),March1,2024,/rain/a/20240301A06U9500.36TangJie(唐杰),“BigModelsandSuperintelligence”(大模型与超级智能),CommunicationsofCCF(中国计算机学会通讯)20,no.6,(2024),alsosee/view/37642.37Chineseorthographylacksworddivision,i.e.,whitespacebetweenwords.Accordingly,thesedistinctionsmustbemadeonthefly,complicatingtheprocessofnominatingthe“tokens”onwhichLLMsoperate.38LiAnqi(李安琪),“Kai-FuLeeandYa-QinZhangFiresideChat:China’sBigModelsHaveMoreOpportunitiesontheC-end,andTechnologyWillNotBringPermanentLeadership”(李开复、张亚勤炉边谈话:中国大模型在

C端的机会更多,技术不会带来永久领先),TencentTechnology(腾讯科技),June14,2024,/articles/3717247.39LiuYangnan,“BeforeachievingAGI.”40“Take-AwaysfromWAICKeynoteSpeechesbyLeadingFiguresattheScienceFrontierConference”(WAIC科学前沿会议大佬演讲干货!),(智东西),July6,2024,https://36/p/2849481785170817.41“HuangTiejun,theEarliestPromoterofChina'sLarge-scaleModel:TheWorldMayOnlyNeedThreeLLMEcosystems”(中国大模型的最早推行者黄铁军：全球可能只需要三个大模型生态),TencentTechnology(腾讯科技),June9,2023,/articles/3690752.42CAS’sInstituteofAutomationisoneofChina’stopinstitutesdevelopingGAIthroughLLMandbrain-inspiredresearch.ItsscientistsaretiedwithPekingUniversityforthehighestnumberofGAI-relatedstudies.Wm.CHannas,Huey-MeeiChang,MaxRiesenhuber,andDanielH.Chou,“China’sCognitiveAIResearch:EmulatingHumanCognitionontheWaytoGeneralPurposeAI,”(CenterforSecurityandEmergingTechnology,July2023),11,/publication/chinas-cognitive-ai-research/.43CEBSITisanumbrellaorganizationforsome39researchinstitutesinChina.See/yjsjj/zzjg/.44BoXuandMumingPoo,“LargeLanguageModelsandBrain-inspiredGeneralIntelligence,”NationalScienceReview,October2023,/nsr/article/10/10/nwad267/7342449.45ChangandHannas,“SpotlightonBeijingInstituteforGeneralArtificialIntelligence.”46ZhuSongchun(朱松纯),“ZhuSongchun:WilltheRapidDevelopmentofArtificialIntelligenceDefinitelyPoseaThreat?”(朱松纯:人工智能高速发展一定会产生威胁吗?),ScienceNet(科学网),September12,2023,/htmlnews/2023/9/508316.shtm;HanYangmei(韩扬眉),“ZhuSongchun:20YearsofExplorationHasGivenChinaanAdvantageinMovingtowardstheEraofCenterforSecurityandEmergingTechnology|23GeneralArtificialIntelligence”(朱松纯:20年探索,为我国迈向通用人工智能时代赢得先机),ChinaScienceDaily(中国科学

报),July25,2024,/htmlnews/2024/7/527056.shtm.47SeeZengYi’shomepageathttps://braincog.ai/~yizeng/.Seealsowork/cn.48“TheChineseAcademyofSciencesTeamIsDeterminedtoInvestintheNext20YearsorEvenLongertoBuildaGeneralBrain-likeArtificialIntelligenceInfrastructure”(中科院团队:决心投入未来

20年乃至更长时间,打造通用类脑人工智能基础设施),Science&TechnologyReview(科技导报),October10,2022,/news/a/HJB51HH40511DC8A.html.49“ShenXiangyang:RethinkingtheHuman-machineRelationshipintheEraofGeneralPurposeLargeModels”(沈向洋:通用大模型时代

重新思考人机关系),EastM(东方财富网),March23,2024,/a/202403233021954617.html.50“TongjipresidentZhengQinghua:BigModelsHaveBecomethePinnacleofCurrentArtificialIntelligence,butTheyStillHaveFourMajorFlaws”(同济校长郑庆华:大模型已成当前人工智能巅峰,但存四大缺陷),Sohu(搜狐),April23,2024,/a/773698839_100016406.51“FocusComment:BigModelsandGeneralArtificialIntelligence|TuringConferenceSIGAIRoundtableForumheldinWuhan”(焦点评论:大模型与通用人工智能

|图灵大会

SIGAI圆桌论坛在武汉举行),BeijingInstituteforGeneralArtificialIntelligence,July30,2024,https://www.bigai.ai/blog/news/焦点评论：大模型与通用人工智能

-图灵大会

bigai圆桌/.52"SeveralMeasuresforPromotingtheInnovationandDevelopmentofGeneralArtificialIntelligenceinBeijing"(北京市促进通用人工智能创新发展的若干措施),May30,2023./zhengce/zhengcefagui/202305/t20230530_3116869.html.53“WuZhaohuiAppointedasvicepresidentoftheChineseAcademyofSciences”(吴朝晖任中国科学院副院长),April11,2024,/csen/2024/0416/c38564a2902027/page.htm.54JiaoYifei(缴翼飞),“WuZhaohui,ViceMinisteroftheMinistryofScienceandTechnology:BigModelsPushArtificialIntelligencetowardthe3.0Stage,andWeNeedtoExploretheDevelopmentofGeneralArtificialIntelligencethroughMultiplePaths”(科技部副部长吴朝晖：大模型推动人工智能迈向

3.0阶段要多路径探索通用人工智能发展),21stCenturyBusinessHerald(21世纪经济报道),March24,2024,/article/20240324/herald/18cf65156b7d67322a4d0b3a9d98a47b.html.55Thefiguresomituniversitiesandgovernment-sponsoredinstitutesengagedinAIresearchinHaidian.56SunYing(孙颖)andWangHaixin(王海欣),“BeijingReleasesThree-yearPlanandLaysOutSixMajorActionstoBuildaNationalEmbodiedIntelligenceInnovationHighland”(发布三年计划、布局六大行动,北京打造全国具身智能创新高地),BeijingDaily(北京日报),April27,2024,/2024/04/27/10758397.shtml.57Forexample,LLMsbyZhipu,BAAI,iFlytek,Huawei,Baidu,ShanghaiArtificialIntelligenceLaboratory(上海人工智能实验室),BaichuanAI(百川智能),MoonshotAI(月之暗面),etc.withdeclaredGAIgoals.See“2023H1‘China'sTop50MostValuableAGIInnovationInstitutions’OfficiallyReleased”(2023H1「中CenterforSecurityandEmergingTechnology|24国最具价值

AGI创新机构

TOP50」正式发布),GeekPark(极客公园),July27,2023,/news/322354.58Hannas,Chang,Riesenhuber,andChou,“China’sCognitiveAIResearch.”59WilliamCHannas,Huey-MeeiChang,RishikaChauhan,DanielH.Chou,etal.,“BibliometricAnalysisofChina’sNon-TherapeuticBrain-ComputerInterfaceResearch,”(CenterforSecurityandEmergingTechnology,March2024),/publication/bibliometric-analysis-of-chinas-non-therapeutic-brain-computer-interface-research/.60CSETmergedcorpusofscholarlyliteratureincludingWebofScience,OpenAlex,SemanticScholar,TheLens,arXiv,andPapersWithCode.SearchesincludedEnglishandChinesevariantsoftheterms.TheLLMkeywordswere:大语言模型,大型语言模型,largelanguagemodel,LLM,GPT,LLaMA;theAGIkeywordswere:通用人工智能,artificialgeneralintelligence,人工通用智慧,强人工智能

strongartificialintelligence,strongAI,AGI,GAI.61OnlinesourceswereprimarilyChineseinstituteandscientificresearch(科研)websites.62Thesepapers’bylinestypicallylistahalf-dozenormoreauthors.Forbrevityweprovideonlytheleadauthor,lastauthor(oftenasenioradvisor),thecorrespondingauthorifdifferentfromthefirstandlastauthors,andfinallyallauthorsclaiminganon-Chinaaffiliation(markedinitalics).63YONGSilong’spinyinspelling(“si”for)isidiosyncratic.Seehttps://www.bigai.ai/blog/news/子

联结场景理解和具身智能，首个智能体具身推理能/.64Herearethescores:BAAI(3papers),BIGAI(10),CASIA(5),otherBeijing-locatedCASinstitutes(10),PekingUniversity(18)andTsinghuaUniversity(11)—foratotalof57appearancesversus18forallotherChineseinstitutescombined,i.e.,76percentofthecitedaffiliations.PriorCSETanalysisofChineseGAIresearchusingadifferent(andmuchlarger)corpusshowedBeijing-basedinstituteson70percentofthepapers.SeeHannas,Chang,Riesenhuber,andChou,“China’sCognitiveAIResearch,”12.Some6foreignorganizationswereamongthecorpus’scitedaffiliations,mostprominentlyCarnegieMellonUniversity(3)andMicrosoftResearchAsia(2).65Hannas,Chang,AikenandChou“China’sAI-BrainResearch;”Hannas,Chang,ChouandFleeger“China’sAdvancedAIResearch;”Hannas,Chang,RiesenhuberandChou,“China’sCognitiveAIResearch;”Huey-MeeiChangandWm.C.Hannas,“SpotlightonBeijingInstituteforGeneralArtificialIntelligence,”(CenterforSecurityandEmerigingTechnology,May2023),/publication/spotlight-on-beijing-institute-for-general-artificial-intelligence/;Wm.C.Hannas,Huey-MeeiChang,RishikaChauhan,DanielH.Chou,etal.,“BibliometricAnalysisofChina’sNon-TherapeuticBrain-ComputerInterfaceResearch”(CenterforSecurityandEmergingTechnology,March2024),/publication/bibliometric-analysis-of-chinas-non-therapeutic-brain-computer-interface-research/.CenterforSecurityandEmergingTechnology|2566LeonardodeCosmo,“GoogleEngineerClaimsAIChatbotIsSentient:WhyThatMatters,”ScientificAmerican,(July2022),/article/google-engineer-claims-ai-chatbot-is-sentient-why-that-matters/.67DavidJ.Chalmers,“CouldaLargeLanguageModelBeConscious?”arXivpreprintarXiv:2303.07103(2024).68TangXiaojuan,ZhuSongchun,LiangYitao,ZhangMuhan,“LargeLanguageModelsAreIn-contextSemanticReasonersRatherthanSymbolicReasoners,”arXivpreprintarXiv:2305.14825v2(2023).69JasonWei,XuezhiWang,DaleShuurmans,MaartenBosma,etal.,“Chain-of-ThoughtPromptingElicitsReasoninginLargeLanguageModels,”arXivpreprintarXiv:2201.11903(2022).70YiheDeng,WeitongZhang,ZixiangChen,QuanquanGu,“RephraseandRespond:LetLargeLanguageModelsAskBetterQuestionsforThemselves,”arXivpreprintarXiv:2311.04205(2024).71ShunyuYao,DianYu,JeffreyZhao,IzhakShafran,etal.,“TreeofThoughts:DeliberateProblemSolvingwithLargeLanguageModels,”arXivpreprintarXiv:2305.10601(2023).72MaciejBesta,NilsBlach,AlesKubicek,RobertGerstenberger,etal.,“GraphofThoughts:SolvingElaborateProblemswithLargeLanguageModels,”arXivpreprintarXiv:2308.09687(2024).73Forarecentsurvey,seeS.M.TowhidulIslamTonmoy,S.M.MehediZaman,VinijaJain,AnkuRani,etal.,“AComprehensiveSurveyofHallucinationMitigationTechniquesinLargeLanguageModels,”arXivpreprintarXiv:2401.01313(2024).74SébastienBubeck,VarunChandrasekaran,RonenEldan,JohannesGehrke,etal.,“SparksofArtificialGeneralIntelligence:EarlyExperimentswithGPT-4,”arXivpreprintarXiv:2303.12712(2023).75BrianOwens,“RageagainstMachineLearningDrivenbyProfit,”Nature