2026数据中心的未来研究报告：数据与算力篇

Issue04

DataCentreFutures:

DataandCompute

Howtheevolvingnatureofdataandcomputemightredefinethedesignandlocationsofdatacentres

Foresight

June2026

DataCentreFutures–lookingbeyondtheasset

Ifleftunchecked,datacentres

coulddestabilisetheurban

metabolism,crowdingoutresourceflowsthatarevitalforshortand

longtermurbandevelopment.

Datacentresembodyaparadox.Theirrapidgrowthisplacing

increasingstrainonkeyresources,evenasourdependenceon

themcontinuestointensify.

Managingthistensioniscritical.

Twenty-firstcenturylife—from

thesmallesteverydayinteractionstolarge-scaleinternationaland

evenextraterrestrialsystems—isincreasinglyreliantonflowsof

data.Whilewewouldallfeelthe

effectsiftheseflowsweredisrupted,fewofuspausetoreflectonthevitaldigitalinfrastructurethattransformsthisdataintomeaningfulinsights,thecommunications,services,andoperationsthatenhanceour

everydaylives.

Withinan‘urbanmetabolism’,datacentresarehubsthroughwhichflowsofwater,energy,materials,

andpeople—aswellasinformation—move.Andascriticalinfrastructure,whichneedstobeprotected,theycanplayacentralroleinshapingsafe,resilientandregenerativeplaces.

Datacentresarecriticalnodesinoneofthemostprolificinfrastructuralperiodsinhistory.Thinkingofthemmerelyas‘assets’narrowsourfieldofvisionandlimitsthepotentialforwider,positiveimpactthrough

theirdesign.

So,whatdefinesa‘good’data

centreandhowcanthefacilitybebotha‘goodneighbour’anda‘goodancestor’?

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DataCentreFutures–lookingbeyondtheasset

Beingagoodneighbourrequiresarethink

of‘performance’metrics;areframingof

‘efficiency’;arefocusingontheirimpactin

theareasinwhichtheyarebuilt.Howcandatacentresimprovetheirlocalplaceandtheirlocalecosystem?Beingagoodancestorrequires

anawarenessthattheinfrastructureoftodaybecomestherelicsoftomorrow.Italsomeansaccountingfortheimpactofthedecisionswemaketodayonfuturegenerations.

Creatingmeaningfulimpactstartswithlong-termthinkinganddesigningsystemsthatcanadapttochange.Whathappenswhentechnologicalandsocio-culturalevolutionsmakedatacentres,in

theircurrentform,redundant?

Withthisandsubsequentissues,weexploretheFutureofDataCentres,buildinguponouralreadybroadrangeofinsightson

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Weaimnottodefendaposition,butrathertoelevatetheconversationarounddatacentres,encouragingmoreofustoaskbetterquestionsaboutdangerousassumptionsandpossible

futuresinthisfast-evolvinglandscape.

Hitpause,lookupandlookaround.

DataCentreFutures:DataandCompute

DataCentreFuturesseries

IncollaborationwithtechnicalexpertsacrossArup’sglobaloffices,theForesightteampresentstheDataCentreFuturesseries.

Eachissueexploresakeytheme,emergingissues,trendsshapingfuturecontext,criticalreflectionsandinformedspeculationonlonger-term

possibility.

ThisfourthandfinalissueofthisseriesfocusesonDataandCompute.

Weareenteringaperiodofacceleratedtechnologicalchange,drivenbytheemergenceofseveralnewcomputingapproachesandmultiplegeneral-purposetechnologies.Thesedevelopmentsrippleacrossthedatalifecycle.Datanowarrivesinvastvolumes,fromanexpandingarrayofsources,andofteninrealtime.Itisprocessedacrossmultiplearchitecturesandpushedthroughdistributednetworks,allwhilebeingshapedandconstrainedbyheightenedawarenessofsecurityand

sovereignty.

Yet,thisrapidevolutioniscollidingwithaverydifferentreality.Thelonglife,highcostandrelativepermanenceofthephysicalinfrastructurebuilttoenableit.Datacentresarebeingdesignedandfinancedasenduring

assetsattheverymomentthetechnologiestheysupportarebecomingmorefluid,uncertainandcontested.Thiscreatesimportantnear-termrisksofredundancyandlock-insalongsidesignificantfinancialandenvironmentalcostsforoperators,clientsandwidereconomies.

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Mappinguncertainity

Technologyradar

Arupexpertpiece

Driversofchange

Externalexpertpiece

Earlysignsofthefutureinthepresent

Recommendations

Glossary

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DataCentreFutures:DataandCompute

Foresightwouldusuallytakealongerviewtoidentifydeeperpatternsof

change,inthiscase,however,thereisalsoanurgentneedtoconfrontnear-termuncertaintyanddesignforoptionality.Thismomentalsocreatesrealopportunities,givingtoday’sdatacentredesignersthechancetobecome

morespecialised,adaptableandcreativethanthesectorpreviouslyrequired.

Atitsbest,thissectorisbecomingoneofthemostimportantenablingindustriesofthenextdecade,quietlypoweringbreakthroughsinscience,publicservices,andeverydayproductivity.

Wecanshapethenexteraratherthaninheritit.Agooddatacentreismorethananasset:itearnsitssociallicencebysupportinglocalcommunities,

ecosystemsandresourcesystems.Asagoodancestor,itisdesignedfor

long-termvalue,adaptable,resilient,andleavingapositivelegacyratherthanstrandedinfrastructure.

Thisreportexaminestheseshiftsacrossthedatalifecycleandasks:

Howcouldemergingandfuturetechnologicaldevelopmentsdrivefuturedesignandlocationofdatacentres?

Howdoweensurethattoday’sdominantdigitalinfrastructurearchetypedoesn’tlimitthepotentialfornewtypesofcomputingandtechnologies

inthefuture?

Ourfindingspointtotheneedforadaptive,context-specificdatacentredesignandlocationstrategies,movingbeyonduniformmodelstoreflectdistinctdataecosystems.

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DataCentreFutures:DataandCompute

Mappinguncertainty

Technologydriversimpactingdatacentres

Datacentresarecritical,capital-intensiveinfrastructurewithlonglife

cyclesdespiterapidindustrychange.Decisionsmadetodaywillshape

exposuretotechnological,regulatoryandenvironmentalriskfordecades.Thatlifespanisalsoastrategicadvantage:designingforflexibilitynowcankeepsitesusefulacrossmultipletechnologygenerations.

Technologicalchange-whatweknow

Artificialintelligence,advancedanalyticsandpervasivedatacollectionaredrivingasurgeindemandforcomputingpower,makingitoneof

thisdecade’smostcriticalresources1.Asdatasourcesmultiply,from

IoTdevicesandindustrialsensorstoautonomoussystems,thevolume,

velocityanddiversityofdatacontinuetoaccelerate.Demandforcomputeisunlikelytoeaseascapabilitiesexpand,bringingnewapplications,

dependenciesandexpectations.

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Atthesametime,datagovernanceisrisingupthepoliticalagenda,

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particularlyinamoregeopoliticallyfraughtenvironment.Datasecurity,

sovereigntyandassetprotectionareshapinginfrastructuredecisions.

Locationisnolongeronlyaboutcost,connectivityorconvenience,but

alsostrategicresilienceandautonomy.ThesepressuresextendbeyondIThardwaretothewidersystemsdatacentresrelyon,includingenergy,water,landandcriticalmaterials,whicharebecomingmoreconstrainedand

contested,ascoveredin

earlierissues

ofthisseries.

Yetscarcityandpressureoftendriveinnovation,pushingnewformsofefficiency,newdesign

responsesandnewtechnologicalsolutions.

DataCentreFutures:DataandCompute

Whatwedon’tknow

Thecurrentdatacentrelandscapewillstruggletosustainthepaceofprojectedgrowthwithoutmajor

changestopowersupply,capacityexpansion,andoperatingmodels.Thatpressureisalsoaccelerating

innovation,forcingbetterefficiency,clearerworkloadchoices,andmoreadaptableoperatingmodels.

Emergingtechnologiesandevolvingcomputingparadigmswillimpactwhereandhowdata

centresaredesigned,builtandoperated.Butwedon’tyetknowtheprecisetimingornatureofmajorbreakthroughs

Convergenceacrosstechnologyfamiliesandsub-familiesmaygeneratenew

spatial,operationalandinvestment

needsthatarenotyetfullyvisible.

Theuncertaintyalsoextendsbeyond

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technologyitself.Thefutureshapeofdatagovernance,sovereigntyandregulationwillvaryfromplacetoplace,influencinginfrastructuredecisionsindifferentways.

Pastdisruptionssuchasthemovefrom

centralisedserverstocloudarchitecturesortherapidriseofAIworkloadsreliantonspecialisedchips,showhowquicklynewdemandcanoutpaceexistingassumptions.Thismakeslong-termplanningmore

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difficultbutalsoreinforcesthevalueofadaptiveandresilientstrategies.

Toexplorethismixofsignalsand

unknowns,wemapthelandscapeoftechnologiesandsub-technologiesonaradar.Theradardoesnotpredictoutcomes,buthelpsidentifyina

structuredwaywhichemerging

northepaceanddepth oftheiradoptions.

technologiesmightreshapethedesign,location,androleofdatacentres.

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Aglossaryoftermsisprovidedon

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SymbolicreasoningintegrationEdgeAIShortterm

5GWearableAI

ShorttermhIisShortterm

2025-20302025-2030

Self-learningsystems

Bio-integratedsensors

DistributedAI

Quantumsensors

Ultra-denseSSDsAIcomputing

Wearableecosystems

Solidstatestorage

7GHybridclassical-quantum

Quantumcommunication

6G

modelsSpacebaseddatacentres

Braincomputerinterface

Thistechnologyradarmapsemergingandconvergingdataandcomputetechnologiesacrossthedatalifecycleandthree

indicativetimehorizons:shortterm,mid-termandlongterm.Itisnotexhaustive,andviewsmaydifferonthelikelytimingandmaturityofindividualtechnologies.

Personallargeactionmodels

Edgecomputing

Neuromorphic

Longterm

Photoniccomputing

Biocomputing

Largelanguagemodels

Largeaction

Glass-basedstorage

Midterm

Aglossaryoftermsisprovidedonpage19ofthisreport.

Longterm

2035-2040

Longterm

2035-2040

Midterm

2030-2035

Midterm

2030-2035

Stochasticcomputing

OrganoidIntelligence

Quantumcomputing

DNAbasedstorage

EmbodiedAI/Robotics

Livingwearables

computing

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Heterogeneouscompute:Designingforthemulti-paradigmdatacentre

Thecoexistenceofclassical,quantumandother

paradigmssuchasbiocomputingwillfundamentallyfragmentthetraditionaldatacentremodel.Weare

likelytobemovingfromaunifiedfacilitytoacampusofspecialisedzones,astheinfrastructurerequirementsforeachparadigmareradicallydifferent.

Locationstrategywilldiverge.Whileclassical

computingcontinuestorelyonpowergrids,quantumwilldrivefacilitiestowardgeologicallystablezonestomitigatevibration,andmayrequireproximitytoheliumsupplychains.Biocomputing,conversely,willanchoritselftobio-techhubsforaccesstobiologicalreagentsandcontainmentprotocols.

Designandinfrastructurewillbe

definedbyextremesegregation.WecannotplaceaBSL-2biocomputinglabrequiringnegativepressureandHEPAexhaustnexttoaclassical

serveraisle.

Similarly,aquantumprocessor’sneedfor

millikelvintemperaturesandEMIshielding

isincompatiblewiththe‘noisy’electrical

environmentofhigh-densityAIracks.This

forcesalaboratorymodeloverawarehouse

model,requiringdifferentflooring,airhandling,andwastesystemswithinthesamecampus.

Organisationsarealreadydesigningfor

coexistence,notreplacement.Classical

computeremainsdominant,butexistingworkonquantumcomputingfacilitiesandcryogenicenvironmentsshowshowdifferentfuture

paradigmsimposefundamentallydifferent

requirements,vibration,EMI,thermalstability,andpowerquality.That’sdrivingdatacentrestowardmodular,heterogeneouscampusesandmoredeliberatelocationstrategies.

Thedecisiontostopscalingclassicalandswitchtoanotherparadigmisn’tdrivenbyasingle

metriclikeflopsortransistorsize.It’sdrivenbybreakpointswherethephysicsoreconomicsofclassicalcomputingsimplycollapse.

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DataCentreFutures:DataandCompute

First,theoptimisationwall,whereclassicalalgorithmsfacecombinatorialexplosion.Whenaproblemrequiresmillionsofyearsofclassicalcompute,likecomplex

logisticsormaterialssimulation,youswitchtoquantum.

Second,thepowerwall.AclassicalAIrackneeds

20,000wattsforpatternrecognition.Whencooling

infrastructurecan’tdissipatetheheatorpowerbudgetscollapse,youswitchtoneuromorphiccomputingforenergy-efficientedgeAI.

Third,thedensitywall.Siliconstoragehitsquantumtunnellinglimitsaroundoneterabytepercubicinch.DNAstores215petabytespergram.Whenthedatacentrerealestateforarchivalstorageexceedsthecostofawet-labinterface,weswitchtobiocomputing.

Finally,thelatencywall.Whenthespeedoflight

becomesthebottleneck,suchashigh-frequencytradingorsensor-levelprocessing,weswitchtophotonic

computingattheedge.

Classicalcomputingisexpectedtostilldominatebyvolumeandeconomicfootprintin2045.

Quantumandbiocomputing

breakthroughsarereal,buttheyarenarrowbreakthroughs,notgeneral-purposeones.

Evenoptimisticroadmapspositionthemas

co-processorsaccessedthroughclassical

orchestrationlayers,notstandalone

replacements.Soin2045,thedatacentreis

stillclassicalatitscore,justwithfarmore

specialisedcomputeislandsembeddedwithinit.

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DataCentreFutures:DataandCompute

Driversofchange

Driver1

Computeshiftsoutward,creatinga‘ladder-shaped’datacentrenetwork

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Modelsshiftfrom‘talking’to‘doing’,requiring‘alwayson’inference.

Thestrategicfocus

shiftstotheportfolio,

527.5

AIismovingfromgeneratingcontentto

notasinglesite.

isreinforcedby

Theshifttowardsdecentralisation

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takingactions,shiftingcomputedemand.LargeLanguageModels(LLMs)aregivingwaytoLargeActionModels(LAMs)thatobserve,decide,andexecutecontinuously,integratedintodailylife,frompersonal

distributedusageofthemodels,whichuseslocalcompute,whiletrainingstillreliesonlarge,

Spaceasanexperimentalinfrastructuretier

devicesandhomestoworkplacesandenterprisesystems.

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Datavolumeinzettabyte

Atthefarendoftheladder,spaceisemergingasanexperimentalinfrastructuretierfornewcomputearchitecture.Orbitaldatacentresarenotnear-termsubstituteforterrestrialcapacitybutcouldoffertheadvantageofabundantsolarenergy,water-freeheatrejection,andzerolanduse,thoughhighlaunchcosts2andregulatoryuncertaintyremainsignificantchallenges.

Atthesametime,datafromsensors,

wearables,IoTdevices,autonomoussystems,andindustrialequipmentistransformingthevolume,speed,andimmediacyofinformationflows.Thisdrivesdemandforalways-on

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centralisedclusters.

inference,lowlatencyandtighterlinksbetweenAIandoperationalsystems.

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Technologiesfromradarunderpinningthis

Becausedecisionsincreasinglyneedto

driver:Self-learningsystems,bio-integrated

happeninrealtime,computeismovingclosertowherepeopleandmachinesact,atthe

sensors,quantumsensors,distributedAI,livingwearables,wearableecosystems,wearableAI,edgeAI,edgecomputing,5G,6G,7G,space

Enterprisesadoptingedgecomputingaren’treplacingcentralisedinfrastructure;they’recreating‘ladder-shaped’networksthatlinklocaledgenodesforreal-timetasks,regionalhubsforaggregation,andcoresitesfor

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edge’,ratherthanonlyindistanthyperscalers.Trainingstilldependsonlarge,centralised

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baseddatacentres,largeactionmodels.

clusters,butinferenceisbecomingmoredistributed.

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heavyworkloadsliketrainingandlarge-scalestorage.Thiscreatesamoreresilientsystem,withcriticalactionshappenclosetowherethey’reneeded,whileheavyliftingstays

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efficientatscale.

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Volumeofdataorinformationcreated,captured,copied,andconsumedworldwidefrom2010to2029

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DataCentreFutures:DataandCompute

Driversofchange

Driver2

Storageshiftsfromone-size-fits-alltooptimisedtires

Thinkofitasorganisingyouritemsinyour

Fromone-size-fits-allstoragetotiered,security-drivenarchitectures

homeintothreeplaces:whatyouuseevery

daystayswithinarm’sreach,thingsyoumightneedthismonthgoinacloset,andthingsyoualmostnevertouchgointheattic.Datacentresaredoingthesamewithdata,splittingitinto‘hot’datathatmustberetrievedinstantly,

Emergingarchivalmediareshapestorageeconomics

Withdatagenerationacceleratingfaster

Atthesametime,storagearchitectureis

thanstoragesupply,3theindustryispushingbeyondsilicon-basedstorage4towardnext-

becomingmoretieredandpurpose-built.

Ratherthanrelyingononesystemforalldata,organisationsareseparatingfastworkingsets,durablemid-termretention,anddeeparchivallayers,eachmatchedtodifferentmediaandretrievalpatterns.

generationarchivaltechnologiessuchasglassandDNA-basedstorage.Thesemediacouldchangestorageeconomicsbyincreasing

‘warm’datathatshouldbereliablebutnot

ultra-fast,and‘cold’archivesthatarecheapertostorebutslowertoaccess,usingdifferent

density,reducingrefreshrequirementsand

loweringcoolingdemand.DNA,forexample,couldtheoreticallyholdupto1.8exabytes

storagetechnologiesforeachsothewhole

systembecomesfasterandcheaper.Inpracticalterms,amulti-mediastoragestackcancut

Thispointstoafutureinwhichstorageis

pergram5,greatlyreducingthefootprintofarchivalstorage.

costandenergyforcolddatawhileimprovingrecoverabilitywhenitmattersmost.

ButthesetechnologiesarenotyetreadyforbroaddeploymentDNAstorageremains

optimisedthrough

Securitypressureswillreinforcethisshift,as

deliberateuseof

costlyduetosynthesisandsequencingexpenses,6andmajoruncertaintiespersistaroundhowbiologicalstoragecanbe

ransomwareincreasinglytargetsbackupsystemsfirst,drivingdemandforimmutablestorageandisolatedrecoveryenvironmentswithstronger

multiplemediatypes,eachtailoredtoits

integratedseamlesslyintoexistingdigitalsystemsandcomplianceframeworks.

physicalseparation.

operationalpurpose.

Technologiesfromradarunderpinningthis

driver:DNAbasedstorage,glass-basedstorage,ultra-denseSSDs,solidstatestorage.

WarmData

Reliable,cost-optimisedretention

ColdArchives

Immutable,isolated,storage

HotData

Highperformance,frequentaccess

DataCentreFutures:DataandCompute

Driversofchange

Driver3

Securityandsovereigntydrivedesignandinvestmentdecisions

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Asdatacentresareincreasinglytreated

Datasovereigntyandcross-borderlegalexposureshapewheredata,backups,andkeyscanreside.

ascriticalnationalinfrastructure,high

Encryption,PQC,keymanagement

Securitylayer

Fibreroutes,corridors,exchangepoints

Connectivitylayer

Datacentres,land,energy

Physicallayer

GDPR,sovereignty,nationalAIstrategies

Policylayer

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securityrequirementsarebeingembeddedingovernmentAIstrategies,raisingtheimportanceofearlylocationand

Securityis

designdecisions.

increasinglyjudgedbyrecoverability,

Quantum-safesecuritymakesconnectivityafacilityandcorridorissue

containmentand

Quantumcomputingaddsafurtherpressure.Encryptionthatprotectsdataintransittodaycouldbecomevulnerablewithinadecade.

sensitivedatacontrol,shapingdatacentrelocation,replication,andconnectivity.

Creatingacurrent“harvestnow,decrypt

later”risk.Governmentsandstandardsbodiesareacceleratingtheshifttopost-quantum

cryptographyforthisreason.

Thismakessecureconnectivityacorefacilityissue.Siteswithdiverseroutesandstrong

Datasovereignty,rulesthatrequiredatato

carrierecosystemsgainvalue,whilefacilitiesneeddedicatedtokeymanagementzones,

stayinaspecificlocationorbecontrolled

Technologiesfromradarunderpinningthisdriver:Quantumcomputing,

Quantumcommunication,hybrid

classical-quantum,braincomputerinterface,spacebaseddatacentres,5G,6G,7G.

underitslaws,isnowapracticalconstraint,prioritisedby88%ofITdecision-makers

strongertrafficseparation,andlayoutsthatsupportcryptoagility8.Securityisbecomingamoreengineeredandauditabledesign

(Lenovo)7.RegulationssuchastheEU’s

GDPRandsector-specificrulesrestrictcross-borderaccess,retention,andliability,pushingorganisationstolocalisedata,whileaddingcomplexitytostoragestrategies.

requirement,movingfrompolicyintenttophysical,testabledesignchoices.

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Driversofchange

Driver4

Facilitiesandsitesshiftfromhomogenoustospecialised

Untilrecently,mostworkloadsimprovedbyscalingsimilarhardware.Nowworkloadsarediverging.AItrainingandinference,

simulationorstreaminganalyticsand

methodsthatanalysedatawhilelimitingexposureofsensitiveinformationoftenrequiredifferentchipstoachievethebestperformanceandenergyefficiency.910

Asthelimitsofconventionalsiliconbecomemorevisible,newhardwareapproachesarematuringinparallel:photonicprocessors

.

optimisedforcommunication-heavytasks,neuromorphicchipsdesignedforlow-powerinference,hybridclassical-quantumsystemsforcomplexoptimisation,andemerging

biocomputingmodelsexploringradicallydifferentphysicalbehaviours.Thisis

Specialisationisalsoreshapingfacility

Technologiesfromradarunderpinningthisdriver:Neuromorphiccomputing,stochasticcomputing,organoid

intelligence,biocomputing,photoniccomputing,quantumcomputing,AIcomputing,largelanguagemodels,largeactionmodels,personallargeactionmodels,symbolicreasoningintegration.

geography.Advancedcomputetypesare

concentratinginto‘capabilityhubs’wheretherightecosystem,supplychains,andexpertiseexisttodeploythemreliably.l6

pushingdatacentresawayfromserverhallsintodifferentiatedenvironmentslldesignedtosupportradicallydifferentrequirementsforpower,cooling,vibration,and

environmentalstability12.Aphotonicclustermayneedprecisetemperaturestability.

Ifwegetthisright,heterogeneitybecomesa

strength:facilitiesthatcanhostnewworkloadsfaster,withbetterperformanceperunitofpowerandspace.

Liquid-cooledGPUrackscanexceed100kWperrackl3,whilequantumrequire

extremethermalcontrol.

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DataCentreFutures:DataandCompute

Externalexpertpiece

Fromalways-ontocontext-aware:rethinkingdigitalinfrastructurefordataecologies

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MarinaOtero

Architect,researcher,andadvocatefornewmodelsofdatastorageHarvardGSD’s2022WheelwrightPrizeforresearchintothefutureofdatastorage

Thereisasignificantshiftinhowmajorbigtechcompaniesand

corporationsareoperating.Astechnologyevolvesrapidlyandthe

lifespanofcomponentslikesemiconductorsandserversgrowsshorter,manycompaniesarebecominglessinterestedinbuildingfixeddata

centres.Instead,theyarefavouringmoreflexibleconfigurations–

poweredwarehousesorpowershells–thatallowhardwaretobeplaced,replaced,orrelocateddependingonchangingconditionssuchasenergyavailability,taxincentives,orcommunityresponses.Extremeexamplesincludebuildingcomponentsonwheelsthatcanbetreatedastemporaryequipmentandbypassregulation.

Thiscouldcreateahighlyfluidlandscapeinwhichterritoriesbecometemporaryhostsfordigital

capacity,oftenwithoutlong-termcommitments.

Whendemandshiftsorprioritieschange,facilitiesriskbeingleft

under-usedorunsuitableforfutureneeds.Andastheseinfrastructures

reshapepowergrids,watersystems,andsurroundingenvironments,oncethemachinesmoveon,theycouldleavebehindindebtedterritoriesthatwereorganisedaroundafuturethatneverarrived.

Rethinkingthe‘always-on’infrastructure,for‘ecologiesofdata’

Thisevolutionraisesamoreprofoundquestionaboutthelogicgoverningdigitalinfrastructure.Datacentreshavelongbeenbuiltonthepremiseofconstantdemand:

24/7operation,continuouslowlatency,andimmediatedataaccessibility.

However,ourcitiesdonotfunctionuninterruptedlyat

maximumcapacity;theirrhythmsfluctuatethroughoutthedayandnight.Onlyalimitedrangeofdigital

activitiesgenuinelyalwaysrequiresimmediateresponse,suchasmedicaldevicesoraviationcontrolsystems.

Treatingeveryworkloadasifitbelongedtothiscategoryleadstoover-provisioned,energy-intensivefacilitiesthatimposeunnecessaryenvironmentalburdens.Whatifwechallengedthisapproachandscrutinisedthelocalimpactofdatacentres?

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Idefineasdistinct‘ecologies’—hot,warm,cold,open,private,

ephemeral,oreternal.Thinkoftheseecologiesastypologiesreflectingthenatureofthedata.Eachecologyimpliesdifferentmodesofstorageandsecuritylevels,oftenmoreappropriatethancurrentpractices.Coldorlong-termdata,forexample,doesnotrequiretheimmediacyofaTier4facility(averyhighresilience,highavailabilitydatacentrestandard)andcanbehousedinsimplerenvironmentsoptimise