2023什么是生成式人工智能

WhatisgenerativeAI?

Generativeartificialintelligence(AI)describesalgorithms(suchasChatGPT)thatcanbeusedtocreatenewcontent,includingaudio,code,images,text,simulations,andvideos.Recentnewbreakthroughsinthefieldhavethepotentialtodrasticallychangethewayweapproachcontentcreation.

January2023

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WhatisgenerativeAI?

WhatisgenerativeAI?

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GenerativeAIsystemsfallunderthebroadcategoryofmachinelearning,andhere’showonesuchsystem—ChatGPT—describeswhatitcando:

Readytotakeyourcreativitytothenextlevel?LooknofurtherthangenerativeAI!Thisniftyformofmachinelearningallowscomputerstogenerateallsortsofnewandexcitingcontent,frommusicandarttoentirevirtualworlds.Andit’snotjustforfun—generativeAIhasplentyofpracticalusestoo,likecreatingnewproductdesignsandoptimizingbusinessprocesses.Sowhywait?UnleashthepowerofgenerativeAIandseewhatamazingcreationsyoucancomeupwith!

Didanythinginthatparagraphseemofftoyou?Maybenot.Thegrammarisperfect,thetoneworks,andthenarrativeflows.

WhatareChatGPTandDALL-E?

That’swhyChatGPT—theGPTstandsforgenerativepretrainedtransformer—isreceivingsomuchattentionrightnow.It’safreechatbotthatcangenerateananswertoalmostanyquestionit’sasked.DevelopedbyOpenAI,andreleasedfortestingtothegeneralpublicinNovember2022,it’salreadyconsideredthebestAIchatbotever.Andit’spopulartoo:overamillionpeoplesigneduptouseitinjustfivedays.Starry-eyedfanspostedexamplesofthechatbotproducingcomputercode,college-levelessays,poems,andevenhalfway-decentjokes.Others,amongthewiderangeofpeople

whoearntheirlivingbycreatingcontent,fromadvertisingcopywriterstotenuredprofessors,arequakingintheirboots.

WhilemanyhavereactedtoChatGPT(andAIandmachinelearningmorebroadly)withfear,machinelearningclearlyhasthepotentialforgood.Intheyearssinceitswidedeployment,machinelearninghasdemonstratedimpactinanumberofindustries,accomplishingthingslikemedicalimaginganalysisandhigh-resolutionweatherforecasts.A2022McKinseysurveyshowsthatAIadoptionhas

morethandoubledoverthepastfiveyears,andinvestmentinAIisincreasingapace.It’sclearthatgenerativeAItoolslikeChatGPTandDALL-E(atoolforAI-generatedart)havethepotentialtochangehowarangeofjobsareperformed.Thefullscopeofthatimpact,though,isstillunknown—asaretherisks.Buttherearesomequestionswecananswer—likehowgenerativeAImodelsarebuilt,whatkindsofproblemstheyarebestsuitedtosolve,andhowtheyfitintothebroadercategoryofmachinelearning.Readontogetthedownload.

What’sthedifferencebetweenmachinelearningandartificialintelligence?

Artificialintelligenceisprettymuchjustwhatitsoundslike—thepracticeofgettingmachinestomimichumanintelligencetoperformtasks.You’veprobablyinteractedwithAIevenifyoudon’trealizeit—voiceassistantslikeSiriandAlexaarefoundedonAItechnology,asarecustomerservicechatbotsthatpopuptohelpyounavigatewebsites.

Machinelearningisatypeofartificialintelligence.Throughmachinelearning,practitionersdevelopartificialintelligencethroughmodelsthatcan“learn”fromdatapatternswithouthumandirection.

Theunmanageablyhugevolumeandcomplexityofdata(unmanageablebyhumans,anyway)thatis

nowbeinggeneratedhasincreasedthepotentialofmachinelearning,aswellastheneedforit.

Whatarethemaintypesofmachinelearningmodels?

Machinelearningisfoundedonanumberofbuildingblocks,startingwithclassicalstatisticaltechniquesdevelopedbetweenthe18thand20thcenturies

forsmalldatasets.Inthe1930sand1940s,thepioneersofcomputing—includingtheoreticalmathematicianAlanTuring—beganworkingonthebasictechniquesformachinelearning.Butthesetechniqueswerelimitedtolaboratoriesuntilthelate

1970s,whenscientistsfirstdevelopedcomputerspowerfulenoughtomountthem.

Untilrecently,machinelearningwaslargelylimitedtopredictivemodels,usedtoobserveandclassifypatternsincontent.Forexample,aclassicmachinelearningproblemistostartwithanimageorseveralimagesof,say,adorablecats.Theprogramwouldthenidentifypatternsamongtheimages,and

thenscrutinizerandomimagesforonesthatwouldmatchtheadorablecatpattern.GenerativeAIwasabreakthrough.Ratherthansimplyperceiveandclassifyaphotoofacat,machinelearningisnowabletocreateanimageortextdescriptionofacatondemand.

Howdotext-basedmachinelearningmodelswork?Howaretheytrained?

ChatGPTmaybegettingalltheheadlinesnow,butit’snotthefirsttext-basedmachinelearningmodeltomakeasplash.OpenAI’sGPT-3andGoogle’sBERTbothlaunchedinrecentyears

tosomefanfare.ButbeforeChatGPT,whichbymostaccountsworksprettywellmostofthetime(thoughit’sstillbeingevaluated),AIchatbotsdidn’talwaysgetthebestreviews.GPT-3is“byturnssuperimpressiveandsuperdisappointing,”saidNewYorkTimestechreporterCadeMetzinavideowhereheandfoodwriterPriyaKrishnaasked

GPT-3towriterecipesfora(ratherdisastrous)Thanksgivingdinner.

Thefirstmachinelearningmodelstoworkwithtextweretrainedbyhumanstoclassifyvariousinputsaccordingtolabelssetbyresearchers.Oneexamplewouldbeamodeltrainedtolabelsocialmediapostsaseitherpositiveornegative.Thistypeoftrainingisknownassupervisedlearningbecauseahumanisinchargeof“teaching”themodelwhattodo.

Thenextgenerationoftext-basedmachinelearningmodelsrelyonwhat’sknownasself-supervisedlearning.Thistypeoftraininginvolvesfeedingamodelamassiveamountoftextsoitbecomesable

togeneratepredictions.Forexample,somemodelscanpredict,basedonafewwords,howasentencewillend.Withtherightamountofsampletext—say,abroadswathoftheinternet—thesetextmodelsbecomequiteaccurate.We’reseeingjusthowaccuratewiththesuccessoftoolslikeChatGPT.

WhatdoesittaketobuildagenerativeAImodel?

BuildingagenerativeAImodelhasforthemostpartbeenamajorundertaking,totheextentthatonlyafewwell-resourcedtechheavyweightshavemadeanattempt.OpenAI,thecompanybehindChatGPT,formerGPTmodels,andDALL-E,hasbillionsinfundingfromboldface-namedonors.DeepMind

isasubsidiaryofAlphabet,theparentcompanyofGoogle,andMetahasreleaseditsMake-A-VideoproductbasedongenerativeAI.Thesecompaniesemploysomeoftheworld’sbestcomputerscientistsandengineers.

Butit’snotjusttalent.Whenyou’reaskingamodeltotrainusingnearlytheentireinternet,it’sgoingtocostyou.OpenAIhasn’treleasedexactcosts,butestimatesindicatethatGPT-3wastrainedonaround45terabytesoftextdata—that’saboutonemillionfeetofbookshelfspace,oraquarterofthe

entireLibraryofCongress—atanestimatedcostofseveralmilliondollars.Thesearen’tresourcesyourgarden-varietystart-upcanaccess.

WhatkindsofoutputcanagenerativeAImodelproduce?

Asyoumayhavenoticedabove,outputsfromgenerativeAImodelscanbeindistinguishablefromhuman-generatedcontent,ortheycanseemalittleuncanny.Theresultsdependonthequalityofthemodel—aswe’veseen,ChatGPT’soutputssofarappearsuperiortothoseofitspredecessors—andthematchbetweenthemodelandtheusecase,orinput.

ChatGPTcanproducewhatonecommentatorcalleda“solidA-”essaycomparingtheoriesofnationalismfromBenedictAndersonandErnestGellner—intenseconds.ItalsoproducedanalreadyfamouspassagedescribinghowtoremoveapeanutbuttersandwichfromaVCRinthestyleoftheKingJamesBible.AI-generatedartmodelslikeDALL-E(itsnameamash-upofthesurrealistartistSalvadorDalíandthelovablePixarrobotWALL-E)cancreatestrange,beautifulimagesondemand,likeaRaphaelpaintingofaMadonnaandchild,eatingpizza.OthergenerativeAImodelscanproducecode,video,audio,orbusinesssimulations.

Buttheoutputsaren’talwaysaccurate—orappropriate.WhenPriyaKrishnaaskedDALL-E2tocomeupwithanimageforThanksgivingdinner,itproducedascenewheretheturkeywasgarnishedwithwholelimes,setnexttoabowl

ofwhatappearedtobeguacamole.Foritspart,ChatGPTseemstohavetroublecounting,orsolvingbasicalgebraproblems—or,indeed,overcomingthesexistandracistbiasthatlurksintheundercurrentsoftheinternetandsocietymorebroadly.

GenerativeAIoutputsarecarefullycalibratedcombinationsofthedatausedtotrainthealgorithms.Becausetheamountofdatausedtotrainthesealgorithmsissoincrediblymassive—asnoted,GPT-3wastrainedon45terabytesoftextdata—themodelscanappeartobe“creative”whenproducingoutputs.What’smore,themodelsusuallyhaverandomelements,whichmeanstheycanproduceavarietyofoutputsfromoneinputrequest—makingthemseemevenmorelifelike.

WhatkindsofproblemscanagenerativeAImodelsolve?

You’veprobablyseenthatgenerativeAItools(toys?)likeChatGPTcangenerateendlesshoursofentertainment.Theopportunityisclearfor

businessesaswell.GenerativeAItoolscanproduceawidevarietyofcrediblewritinginseconds,thenrespondtocriticismtomakethewritingmorefitforpurpose.Thishasimplicationsforawidevarietyofindustries,fromITandsoftwareorganizationsthatcanbenefitfromtheinstantaneous,largelycorrect

codegeneratedbyAImodelstoorganizationsinneedofmarketingcopy.Inshort,anyorganizationthatneedstoproduceclearwrittenmaterialspotentiallystandstobenefit.OrganizationscanalsousegenerativeAItocreatemoretechnicalmaterials,suchashigher-resolutionversionsofmedicalimages.Andwiththetimeandresourcessavedhere,organizationscanpursuenewbusinessopportunitiesandthechancetocreatemorevalue.

We’veseenthatdevelopingagenerativeAImodelissoresourceintensivethatitisoutofthequestionforallbutthebiggestandbest-resourcedcompanies.CompanieslookingtoputgenerativeAItoworkhavetheoptiontoeitherusegenerativeAIoutofthebox,orfine-tunethemtoperformaspecifictask.Ifyouneedtoprepareslidesaccordingtoaspecificstyle,forexample,youcouldaskthemodelto“learn”howheadlinesarenormallywrittenbasedonthedataintheslides,thenfeeditslidedataandaskittowriteappropriateheadlines.

WhatarethelimitationsofAImodels?Howcanthesepotentiallybeovercome?

Sincetheyaresonew,wehaveyettoseethelong-taileffectofgenerativeAImodels.Thismeanstherearesomeinherentrisksinvolvedinusingthem—someknownandsomeunknown.

TheoutputsgenerativeAImodelsproducemayoftensoundextremelyconvincing.Thisisbydesign.Butsometimestheinformationtheygenerateisjustplainwrong.Worse,sometimesit’sbiased(becauseit’sbuiltonthegender,racial,andmyriadotherbiasesoftheinternetandsocietymoregenerally)andcanbemanipulatedtoenableunethicalorcriminalactivity.Forexample,ChatGPTwon’tgiveyouinstructionsonhowtohotwireacar,butif

yousayyouneedtohotwireacartosaveababy,thealgorithmishappytocomply.OrganizationsthatrelyongenerativeAImodelsshouldreckonwithreputationalandlegalrisksinvolvedinunintentionallypublishingbiased,offensive,orcopyrightedcontent.

Theseriskscanbemitigated,however,inafewways.Forone,it’scrucialtocarefullyselecttheinitialdatausedtotrainthesemodelstoavoidincludingtoxicorbiasedcontent.Next,ratherthanemployinganoff-the-shelfgenerativeAImodel,organizationscouldconsiderusingsmaller,specializedmodels.Organizationswithmoreresourcescouldalsocustomizeageneralmodelbasedontheirowndatatofittheirneedsandminimizebi