bcg -首席执行官们如何应对生成式人工智能的新地缘政治格局 How CEOs Can Navigate the New Geopolitics of GenAI

HowCEOsCanNavigatetheNewGeopoliticsofGenAI

DECEMBER09,2024

By

NikolausLang

,LeonidZhukov,

DavidZuluagaMartínez

,

Marc

Gilbert

,MeenalPore,andEtienneCavin

READINGTIME:15MIN

Asthe

generativeAI

maptakesshape,theUSandChinaareassertingtheirdominance.Tech

companiesfromtheseGenAIsuperpowershavebuiltasubstantialleadinthecreationandlarge-

scalecommercializationoftop-performinglargelanguagemodels(LLMs).InaworldwhereGenAIisquicklybecomingacriticalresource,theUSandChinaarecurrentlyonpacetocontrolthesupply.

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Butsomethinginterestingishappeninginparallel.Asmallgroupofcountries—the“GenAImiddlepowers”—isemerging,eachwithitsowndistinctstrengthsthatmayenableittocompeteona

regionalandevenglobalscaleasasupplierofthetechnology.Theimplicationsforcompaniesaresignificant.

ForcorporateleaderswhoareintegratingGenAIintoanincreasingshareoftheirproductsandservices,andwhoareoperatingacrossmultiplegeographies,relyingsolelyonGenAIsuppliedbycompaniesintheUSorChinacouldposeseriouschallenges,withlocalregulations,data

requirements,andtheavailabilityofLLMsallsubjecttoshi代singovernmentpolicy.AlthoughamoremultipolarsupplyofGenAIincreasescomplexity,itwouldalsocreatecriticaloptionality.

CEOsneedtounderstandthisdynamic—andbeabletonavigatetheevolvinggeopoliticsofGenAI.Thetraditionalapproach—determiningwhichcountrycanacquirethemostadvanced

semiconductors,forexample,orwhichhasthemostfavorableregulatoryenvironment—won’t

suffice.CompanyleaderscanassesstherelativestrengthofGenAIsuperpowersandmiddlepowersacrossthesixkeyenablersofGenAIsupply:capitalpower,talent,intellectualproperty(IP),

data

,

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energy,andcomputingpower.

SuperpowersandMiddlePowers:TheEmergingGenAILandscape

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90

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50

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Relativeperformanceacrossenablers,onanormalizedscaleof0to

US

CHINA

EU

JAPAN

SOUTHKOREA

UAE

SAUDIARABIA

CapitalpowerTalentIPDataEnergyComputi

ngpower

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Thisisnotaboutacountry’srateofGenAIadoption,whichcano代enbedecoupledfromitsabilitytosupplythetechnology.TheformerwasassessedinarecentBCGstudyof73globaleconomies’

exposuretoandreadinesstodeployGenAI

.(Seethesidebar“TheAdoptionAdvantage”)

THEADOPTIONADVANTAGE

ThisanalysisisfocusedonthesupplyofgenerativeAI,whichwillbeparamountinshapingthegeopoliticaldynamicsofthetechnology.Buttheflipsideofsupply—theactualadoptionofthetechnology—isalsoofcriticalimportance.Rapidand

extensiveadoptioncanpositivelyimpactcompetitivenessandproductivity,leadingtobroadereconomicprosperity.Formanycountryleaders,promotingadoptionofAI

acrosstheeconomymaybetherightpolicypriority.

BCG’srecentAIMaturityIndex

offersacomprehensiveassessmentofcountries’exposuretoAI-driveneconomicdisruptionacrossindustriesaswellastheir

readinesstoseizetheeconomicadvantagethetechnologymakesavailable.

AsgenerativeAImatures,foundationLLMswillincreasinglybeputtousethroughindustry-orfunction-specificapplications.RobustecosystemsofcompaniesworkingonthisapplicationlayerofthetechnologywillbeanimportantdriverofsuccessforcountrieslookingtomaketheirindustriesmorecompetitivethroughAI.

Indiaisapowerfulexampleofacountrythatiswell-positionedtofostersuchan

ecosystem.Thegovernment’sIndiaAIMissioniscommittedtosupportingextensiveadoptionthroughthecreationofcentersofAIexcellence,whichaimtointegratethe

technologyintokeysectorslikeagricultureandeducation.Indiaalsobenefitsfromitshistoricalstrengthintechtalent,asitishometoalargepoolof215,000AI

specialists.

WhileIndiancompanieshavealreadyreleasedsomeLLMs,thecountryislikelyto

increasinglyfocusonfosteringanecosystemofcompaniesheavilyinvestedinindustry-specificGenAIapplications,suchasSetu’sSesameforfinanceand

insurance,Fractal’sVaidya.aiforhealthcare,andLexlegis’Lexlegis.aiforlegalservices.

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FocusingourresearchonsupplyenablesustohelpCEOsdeterminehowtoensuretheircompanyhasreliableandflexibleaccesstothisgame-changingtechnology.Hereisacloserlookatthemajorplayersandtheothercontenders.

TheGenAISuperpowers

TheUSandChinaarecurrentlytheonlyplayerswithrobustaccesstoandcontroloversizeable

portionsofthewholeGenAIvaluechain.TheyproducethemostIPandtheyhavethelargestAI

talentpools;theyhavesomeoftherichestdataecosystemsintheworldandthemostdatacenterinfrastructurecapacity,andtheyleadincapitalaccess.

Today’sDefaultIs“MadeintheUSA”

TheUShashadapronouncedheadstartonGenAI,buildingondecadesof

AI

leadership.Nearly

2

70%oftheworld’snotableAImodelssince1950havebeendevelopedbyorinpartnershipwithUS-basedcompaniesoracademicinstitutions,ashave57%oftop-performingLLMs.(SeeExhibit1.)

:TheUSishometosome60%ofthetop2,000AIscholarsintheworldandattractedroughlyone-

quarterofallAIspecialiststhatrelocatedgloballybetween2022and2024;itstotalAItalentpoolhasgrowntonearlyhalfamillionpeople,thelargestintheworld.AndUS-basedAIscholarshave

contributed35%oftheworld’smostinfluentialpapersinthefieldofAIsinceits

inception.3

US-basedGenAIstartupshavealsoreceivedunparalleledprivateinvestment:atotalof$65billion

since2019.Inaddition,AI-directedcapitalexpenditureswithinestablishedtechfirmslikeAlphabet,Amazon,Meta,andMicroso代areexpectedtoexceed$200billionfor2024.Withmassivecomputingcapacity,afull-stackapproachextendingtohardwarecodesign,deeppockets,globalreach,accesstotheworld’stoptalent,andin-housemodeldevelopersordeeppartnershipwithoutsidedevelopers,

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thesecompaniesaresingularlypositionedtosupportUSleadershipinGenAIintheforeseeablefuture.

Beyondtalentandcapital,theUSalsohastheinfrastructuretosupportinferenceatscale—thatis,tosupplyGenAIonanongoingbasistomodelusers.Itisthelargestdatacenterhubintheworld,withanestimatedcapacityofapproximately45gigawattsin2024.TheUShasreliableaccessto

cutting-edgehardware(throughUS-basedNvidiaandstronggeopoliticaltiestoTaiwan-based

TSMC)tosupportdatacenterexpansion,thoughlongleadtimestoconnecttotheelectricalgridmaycreatechallenges.

Made-in-ChinaModelsAreCatchingUp

SomesignsindicatethatChinaiscatchinguptotheUSonsomekeyenablersandmakingrapid

progressintheproductionoftopLLMs.TwoChinesecompanies,AlibabaandtheGenAIstartup

01.AI,contributeoverone-quarteroftheworld’stopopen-sourcemodels.Establishedtechgiants

BaiduandTencenthavealsoreleasedhigh-performingmodels,ashaveanewgenerationofGenAIstartups,theso-calledAItigers:ZhipuAI,BaichuanAI,MoonshotAI,andMiniMaxAI.TopChinesemodelshavesubstantiallyreducedthegapcomparedtostate-of-the-artalternativesinthelastyear.

(SeeExhibit2.)AndtopChinesemodelshaveeffectivelyclosedthegapinChineselanguagebenchmarks.

:

TheChineseGenAIecosystemhasbenefittedfromaccesstoforeignopen-sourceoropen-weights

foundationmodels:01.AI’sYimodelfamily,forexample,isbasedonMeta’sLlama.(Seethesidebar“

ALandscapeofOpen-SourceandClosedModels

”)TheChinesegovernmenthassignaleditsintenttoensureanamplesupplyofdomesticopen-sourceoptionsthatplayasimilarroleinthefuture,

supportingagrowingnumberofsmallercompaniesastheyrampuptheirtechnicalcapabilities.

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AlthoughittrailstheUS,ChinastillhasastrongAItalentbench—andpotentnationalresearch

championslikeTsinghuaUniversityandShanghaiJiaoTongUniversity.ThefourAItigersareall

foundedbyTsinghuafacultyoralumni.China’sstrengthinAItalentisapparentinitsleadershiponpatents,withmorethan76,000AIpatentsfiledwiththeWorldIntellectualPropertyOrganization

between2019and2023,aboutfourtimesasmanyastheUS.

Chinaalsohasampledatacenterinfrastructure,withapproximately20gigawattsofcapacity,andsignificantcapitalthroughitspublicR&Dbudget,whichhasaveraged$50billionperyearbetween2016and2023.Infact,governmentventurecapitalfundsdemonstrateChina’scommitmentto

boostingAIinnovationthroughpublicinvestment.GovernmentVCshaveinvestednearlyaquarterof

theirtotalfundsinAIfirms,exceeding$180billionintotalsince2000,ofwhichroughly$100billion

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wasinvestedbetween2019and2023.Andprivateinvestment,domesticaswellasforeign,hasactivelydrivenprogressamongtheAItigers,whichtogetherwith01.AIhaveraisedmorethan$6billioninthelastfewyears—includingfromChinesehyperscalers,notablyAlibaba.

METHODOLOGY

OurresearchdrawsonanextensivequantitativecomparisonoftherelativestrengthoftheUS,China,andGenAImiddlepowersacrossthekeyenablersofGenAIsupply.Thiscomparisonwasusedasabasisforfurtheranalysis,ratherthanasastrict

index;itenabledustoidentifythecountriesandregionswiththemostopportunityandthesalientstrengthsandchallengesofeach.

Thequantitativeassessmentofrelativestrengthacrossenablersdrawsinpartonthehistoryofcountries’strengthsinandcontributiontoAIasabroadfamilyof

technologies,ofwhichGenAIisonlyasubset.Thisinpartreflectslimitationsin

reliabletransnationaldata,giventherecencyofGenAI’sriseinimportance.But,moreimportantly,indicatorsassociatedwiththelongarcofthehistoryofAIspeaktotheenduranceofcriticalcapabilities,particularlyontalentandinnovation

ecosystems.

Sinceourprimaryobjectivewastodeveloparelativesenseofstrengthacross

enablers,wedevelopednormalizedscoresbyenablercountryorregionpairsinthefollowingway:

•Eachindicatorleadstoanabsolutevaluebycountryorregion.Thesevaluesarenotnormalizedbypopulation,sizeoftheeconomy,orothersuchfactors

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becausecompetitioninthesupplyofGenAIislargelyafunctionofscale.

•Valuesforeachindicatorarethen(linearly)normalizedintocountryorregionscoresonascalefrom0to1,where1equalsthehighestactualcountryvalueinourdatasetand0issetasabsolute0(exceptfortheenergyenabler,which

reflectsindustrialelectricityprices:inthiscase,0equalsthelowestactualprice.

•Then,foreachcountryorregion,wetaketheaveragenormalizedscoreacrossindicatorstogeneratetheenablerscore.Acountrywouldonlyhaveascoreof1inanenablerifithadthehighestabsolutevalueofallcountriesinourdatasetforallindicatorsassociatedwiththeenablerinquestion.

Thefollowingaretheindicatorsweusedtodevelopthestage-settinganalysisofrelativestrengthacrosstheenablersofGenAIsupply,withthesourcesforeach

indicatedinparentheses.Forfurtherdetailsoftheanalysisanddatausedinthisstudy,pleasecontacttheauthors.

Talent:

•Shareofthetop2,000AIresearchersworldwide,basedonthelocationoftheauthorsofleadingAIpublications.(AMiner)

•Shareofthetop300AIinstitutions,alsobasedonthelocationofauthorsofleadingAIpublications.(AMiner)

•SizeoftheAI-specializedtalentpoolworkingwithinacountry(thoughnotnecessarilyemployedbyalocalcompany).(BCGTalentTracker)

IntellectualProperty:

•Shareofnotablemachinelearningmodelsdevelopedsince1959by,orin

partnershipwith,researchersorinstitutionsfromaparticularcountry.(EpochAI)

•TotalnumberofAIpublicationsproducedbyauthorsand/orinstitutionsfromaparticularcountrybetween2019and2023.(SCImago)

•TotalnumberofcitationsofAIpublicationsproducedbyauthorsand/or

institutionsineachcountrybetween2019and2023,excludingself-citations.

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(SCImago)

•TotalnumberofAIpatentsfiledthroughtheWIPObetween2019and2023.

(WIPO)

Data:

•RankingintheUnitedNationse-GovernmentDevelopmentIndex,whichmeasuresgovernmentdigitization.(UnitedNations)

•Totalnumberofactivehandset-basedandcomputer-based(i.e.,connectedbyUSB/dongle)mobile-broadbandsubscriptions,togaugerelativemagnitudesofdigitaldatageneration.(InternationalTelecommunicationUnion)

Thesemetricsaredirectionallyindicativeofthedegreeofdigitizationaswellasthevolumeof(digital)dataproducedineachcountry.Theydonot,however,accountforotherimportantfactors,suchastheregulatoryflexibilityofdatausesor(relatedly)thelevelofcontextualizationofdata(i.e.,howeasilydataofdifferenttypesand

sourcescanbeusedinanintegratedfashion).

Energy:

•Thecostofelectricityforatypicalcommercial/industrialuserperkilowatt-hour,basedonthe“largestbusinesscity”withineachcountry.(fDiBenchmark)

Acriticalcomponentofenergyasanenablerisleadtimetogridinterconnectionfordatacenterbuildouts,awidelyacknowledgedchallengeinmostgeographies.

Unfortunately,thisisanindicatorforwhichreliablycomparablecross-countrymetricsarenotreadilyavailable,whichiswhythequantitativedimensionofourcomparativeanalysisislimitedtothecostofelectricity.

ComputingPower:

•Existingdatacentercapacity,includinghyperscaler,colocation,andenterprise

facilities,measuredingigawatts.TheonlyexceptionisChina,forwhichdemand

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hasbeenusedinstead,asoverallcapacityinChinaisdifficulttoestimate.(BCGHendersonInstituteanalysisofcountryandindustryreports)

•Binaryscoreforaccesstocutting-edgesemiconductorsoptimizedforAI

workloads,suchasNvidia’sA100orH100chips.Countriesandregionswithnoformalaccessbarriersreceiveascoreof1;thosefacingsuchbarriers(inthe

formofexportrestrictions,forexample)receiveascoreof0.(USDepartmentofCommerce;BCGHendersonInstituteanalysis)

•Binaryscoreforaccesstotier2semiconductors.Allcountriesinouranalysisreceivedascoreof1,astheyallhaveformallyopenaccesstothistypeof

hardware.(BCGHendersonInstituteanalysis)

CapitalPower:

•Venturecapitalfunding,from2019to2024,basedontheobservedAI-directed

shareofinvestmentsbyventurecapitalfunds,bycountry(including,inthecaseofChina,thesizeablepoolofgovernmentVCfundsdevotedtoAI).(Pitchbook)

•CorporateR&Dspendingbythe20largestpubliclytradedtechcompanies,bycountry.(EuropeanCommission;BCGHendersonInstitute)

•Sovereignwealthandpublicpension-fundinvestmentpower,adjustedforthe

shareofassetsundermanagementinequitiesandalternativeinvestments

(thereforeexcludingbonds,realestateandinfrastructureinvestments,andrisk-freeassets).(BCGHendersonInstitute)

CurrentlimitationsinChina’saccesstostate-of-the-artchipsforAImodeltrainingandinferencearelikelytodelayratherthanimpedefurtherprogress.ManyChinesecompaniesreportedlyretain

accesstochips,andNvidiahasdesignedmodelsnotcoveredbyUStraderestrictions;Chinesecompaniesacquired$5billionworthofthesechipsin2023.

Furthermore,Chinaisinvestingaggressivelyinitsdomesticchipmanufacturingcapacity:the

governmenthaspledgedapproximately$40billion,andHuaweirecentlyreleaseditsAscend910

chips,optimizedforAIworkloads.RegardlessofwhetheritcancompetewithNvidiaatthecutting

edgeofcomputinghardware—andespeciallytheso代warelayerontopofit—Huaweihasreachedamilestoneinrecentmonthswiththetrainingofahigh-performingLLM,iFlytek’sXinghuo4,entirelyonitsAscendplatform.

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Chinesecompaniesalsohaveambitionsoutsidetheirhomemarket.Alibaba,forexample,is

expandingitsdatacenterfootprintinMalaysia,Philippines,Thailand,SouthKorea,andMexico—extendingthereachofitsQwenfamilyofgenerativeAImodels.

GenAIMiddlePowersontheRise

ThisUS–Chinastoryhasfueledthe“twosuperpowers”narrative—andconvincinglyso.But

momentumisbuildinginotherpartsoftheworld.TheEU,forexample,hasstrongcomplementarityamongmemberstateswithestablishedstrengths.IntheGulf,highlyconcentratedandagilecapital,coupledwithaffordableenergy,isacceleratingprogressevenintheabsenceofarobust,establishedtechsector.SouthKoreaandJapanbothhavestrongtechnologysectors,withthecapitaltoscale.

MadeintheEuropeanUnion

Forsome,whatmaybeoutofreachattheindividualcountrylevelbecomesfeasibleatthebloclevel.TheEUstandstobenefitfromthecomplementarityofenablersamongmemberstatesandthescaleitcanachieveasaunifiedmarket.

BuildingonDistributedStrength.TheEUisalreadyhometoanascentGenAIstartupecosystem.France-basedMistralhascontributedsevenoftheworld’stopLLMsandhasreceived$1.2billioninfundingtodate.TheGermanstartupAlephAlphahasalsodevelopedpowerfulfoundationmodels

(twooftheworld’stopLLMs),thoughithasmostrecentlypivotedtoindustry-specificapplications.

SmallerGenAIstartupsarealsoattractinginvestment.Kyutai,foundedin2023,hasreceivedaround$350millionandalreadyreleaseditsMoshiAImodel,specializedinadvancedspeech;with$220

millioninseedcapital,Hispushingtodevelopproductivity-enhancingAIagents;Poolside,

meanwhile,hasreceivedinvestmentsworth$626milliontobuildaleadingmodelforcode

generation;andBlackForestLabshasobtainedaround$150milliontofurtheritstext-to-imagefoundationmodel.

WhilethesecompaniesaremodestinsizeandfundingcomparedtoUSandChinesecounterparts,theyhaveastrongfoundationoftalentonwhichtobuild.TheEUhasanextensiveandgrowingpoolofAIspecialists,ofwhichtherearemorethan100,000inFranceandGermanyalone.(SeeExhibit3.)

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:TheEUalsohastheadvantageofbeingamassivemarket,withacombinedGDPof$18trillion.It’s

solargethatitscomparativelydemandingregulatoryframeworkforAI,includingtheGeneralData

ProtectionRegulation(GDPR)andtherecentlyenactedEUAIAct,isunlikelytodissuadeGenAI

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suppliersfromoperatingthere.Infact,itsregulationscouldcreatedemandforEU-developedand-hostedintelligence,whichmaybeviewedasmoretrustworthyandprotectiveofusers’data.

TheEUhastheworld’sthird-largestdatacentercapacity,a代ertheUSandChina,with8gigawattsin

2024.Whileelectricitypricesintheregionarehigh,considerablevariabilitycanbeexploited:

industrialelectricitycancost20%lessinFrance,andcloseto60%lessinSwedenandFinland,thaninGermany.Moreover,companieslookingtosupplyGenAImodelstotheEUmarketmayhaveno

alternativetoscalingdatacenterstherefortheaforementionedregulatoryreasons.

Buildingontheabovestrengths,wealreadyseecomplementarityinaction:Mistral’smodels,for

example,aredesignedinFrance,trainedonItaliansupercomputers,andservedtoclientslargelyoutofSwedishdatacenters—poweredbythechipsmanufacturedusingEUVlithographyequipment

producedexclusivelybyNetherlands-basedASML.

BridgingtheFundingGap.TheEU’sgreatestchallengeliesinsecuringtheinvestmentsnecessarytokeepupwithmodelscalingandexpanddatacenterinfrastructure(whichincludesupgradingthepowergrid).TheEUhasahistoryoflagginginvestmentinthetechsector,andthereforeithasbeenunabletoscaletechchampions:whileUSGDPis1.5timesgreaterthanthatoftheEU,themarket

capoftheUSshareoftheworld’s1,000largestpublictechcompaniesiscloseto18timesgreater

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thantheEUshare.

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Asaresult,EU-basedtechnologyfirmshaveonlyafractionoftheinvestmentmuscleoftheirUS

counterparts:The20largestEUtechcompaniesspentacombined$40billiononR&Din2022,

comparedto$200billionforthe20largesttechcompaniesintheUS.Unsurprisingly,GenAIstartupsintheEUhaveonlyreceived$3.5billionininvestmentssince2019,or5%oftheprivateinvestment

receivedbyUS-basedGenAIstartups.

Therearesignsofpositivemomentum,however.TheDraghireportonEuropeancompetitiveness

andrecentannouncementsbytheEuropeanInvestmentBankandtheEuropeanCommissionall

stresstheneedforastrongerEUtechecosystem—withthefundingnecessaryforstartupstoscale

withinthebloc.TherearepoolsofresourcestheEUcouldtapinto,notablypublicR&Dspending

acrossmemberstates,whichaveragedabout$40billionperyearbetween2016and2022—butdoingsowillrequireaconcertedeffortinacomplexenvironmentofdistributeddecisionmaking.

Precedentsforsuchcollaborationexist,particularlyinjointeffortslikethecreationoftheEuropeanairplaneconsortiumAirbus.Butorchestrationacrossnationalboundarieshasalsoattimesbeen

challenging,aswiththeGaiaXinitiativetodeveloptrustworthyandsovereigncloudinfrastructurefortheEU.Itremainstobeseenwhetherthepresentpolicymomentumtranslatesintotimelyaction.

MadeinSaudiArabiaortheUAE

Becauseofthehighcostofbuildingatop-performingGenAIecosystem,somecountriescanuse

publiclyavailableIPandinveststrategicallyintalentandcomputingpower.Countriesmayalsorelyonstrongaccesstocapitaltooutsourcethedevelopmentofmodelswhichtheycanneverthelessownandserveatscale.ThisapproachisbestsuitedtoeconomiessuchasSaudiArabiaandtheUAE,

whichhavecentralizedaccesstosignificantcapitalresourceslikesovereignwealthfunds.

InvestinginGrowth.IntheGulfregion,SaudiArabiaandtheUAEareeachmakingsignificantinvestmentstodiversifytheireconomiesandcontributetotheregion’sbroadertechnological

acceleration.

ThecommitmenttodirectinvestmentstowardAIisclear.TheUAEhaslauncheda$10billionAIVCfund—morethaneighttimesthetotalfundingreceivedtodatebyMistral,forexample.Saudi

Arabia,meanwhile,planstoinvest$40billioninAIdevelopment,ontopofarecentlyannounced

plantoinvest$100billionindatacenterexpansion(ProjectTranscendence)anditsearlier$100

billiontechfund(ProjectAlat).Thesecommittedinvestmentsdrawonmuchlargerpoolsofcapital:

ofthe20largestsovereignwealthfundsworldwide,UAEishometofive,totalingroughly$2trillioninassetsundermanagement,whileSaudiArabia’sPublicInvestmentFund(PIF)manages$920billion.

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:

BothcountrieshaveinvestedheavilyinbuildinganAIR&Decosystemthroughuniversitiesand

sovereign-wealth-backedstartupslikeG42intheUAE.Since2022,theAItalentpoolintheUAEandSaudiArabiahasgrownby36%and17%,respectively,and

incomingnetAItalentmigration

has

grownby40%and70%.(SeeExhibit4.)

DatacenterinfrastructureintheGulfremainssmallinabsoluteterms,withSaudiArabiaandthe

UAEeacharound0.4gigawattsincapacity.Butitisgrowingrapidly,inpartenabledbytheregion’s

lowenergycosts,whichcanbe30%to50%lowerthanintheUSonaverage.Therecenteasingof

cutting-edgechipexportrestrictionstotheUAE—whichtheSaudigovernmentexpectswilleventuallyextendtoSaudiArabiaaswell—willcontributetosustainedaccesstohardwareoptimizedforAI

workloads.Still,thepaceofactualdatacenterbuildoutisanopenquestion.

Progresstodatehasbeennotable:SaudiArabia’sAramcohasproducedwhatisreportedlythe

largestindustrialGenAImodelintheworld,andtheSaudiDataandAIAuthorityreleasedthe

leadingArabicLLMfamily,ALLaM,thelargestversionsofwhicharebuiltonthebasisofMeta’s

Llama-2.TwooftheEmiratiTechnologyInnovationInstitute’sFalconmodelscon