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EQUITYPERSPECTIVES DeepLearning:SmarterArtificialIntelligence March24,2016 568Views “Deeplearning,”amajorbreakthroughinthefieldofartificialintelligence (A.I.),isonthevergeofdrivingaccelerateddemandforsuchapplications. ByEricGhernati Inaslow-growthenvironment,f ollowingconsensusestimatesmightseemlikeasaf ewaytogo,but itisnotnecessarilythebestwaytoaddalpha.1Sometimesthebestreturnscomef rombuying stocksoutsidethelimitationsof consensus,whichexplainswhyLordAbbettanalystsareregularly encouragedtosharetheir“variantperceptions”oncompanieswithprospectsthatmaybe underappreciatedbythemarket. Take,f orexample,theprevailingnotionthatdeeplearning,af undamentallynewsof twaremodel, wherebillionsof sof tware“neurons”andtrillionsof connectionsaretrained,inparallel,willcausea moderatechangeinchipdemand.Onthecontrary,Ibelievetheindustryisonthecuspof much strongerdemandf ordeep-learningapplicationsbasedongraphics-processingunits. Deeplearning,thef astestgrowingpartof machinelearning,2 isusedtohelpsolvemanybig-data problems,suchascomputervision.Practicalexamplesincludevehicle,pedestrian,andlandmark identif icationf ordriverassistance(includingpredictionsof wheretraf f icjamsmightoccur);image recognition;speechrecognitionandtranslation;naturallanguageprocessing,andlif esciences. (SeeChart1.) Thevanguardof deep-learningprojectsinvolvesthetrainingof deepneuralnetworks,an advancedbranchof artif icialintelligencethatsimulatesthewaythebrainworks.Onecompanyis usingrobotstotraindeepneuralnetworkstoprogramitsrobotstograsprandomobjectsby basicallyimprovingarobot'shand-to-eyecoordination.Lookingf artherahead,somescientists envisiondeepneuralnetworkswithpersonalsensorsthatcouldidentif yorpredictmedical problems. Chart1.DeepLearningIsaMajorBreakthroughinArtificialIntelligence Usesmachinestoprovidesmarteranswersandpredictchancesoffutureevents,needs 1 Source:LordAbbett. CurrentDeep-LearningApplications Therangeof deep-learningapplicationshasalreadyreachedimpressiveproportions,including: DigitalassistantslikeApple’sSIRIandOKGoogle Imageandf acialrecognition(socialmedia,enhancedadvertisement,onlineretailshopping, hospitality,onlinemediarecommendations,security,etc.) Advancedsaf etycarf eatures Lif escience(genomics,drugdiscovery,earlydetection,andpreventionof diseases) Financialservices(algorithmictrading,customerservice,wealthmanagement,creditanalysis) Cyber-security(preventionagainstadvancedmaliciousthreats) Insurance(underwriting,claimsprocess,f rauddetection) Butthenextstageof deeplearning—callitdeeplearning2.0—hasthepotentialtotakedisruptive innovationtoanotherlevel.Googlesearchresponsestousers’queriesshouldgetmuchsmarter, withnarrowerandmorerelevantresults,reducingthemassiveamountof timesusersspendgoing overallthequeries’results.Likewise,theintegrationof deeplearningwithconsumerappslike GoogleMaps,Gmail,Calendar,location-basedservices,photosandYouTubevideosholds signif icantpromise,bothtoconsumersintermsof speedieraccesstomorerelevantinf o(including imagesandvideos)andtoadvertisers,intermsof acquiringamoretargetedaudiencef ortheir products. Deeplearning’snextbigmarketoutsideof consumer/socialmedialikelywillbeintransportation. Dronesarenothingmorethananiterationof deeplearning2.0.asdronesseesignif icant 2 enhancementinimagerecognitionandpathplanning.Likewiseinautos,deeplearning2.0 applicationscanbeseenininitialiterationsof driverlesscarsalreadyontheroad.Thenextwave of driverlesscarsshouldcometomarketoverthenextonetothreeyears.Anddependingon supportf romvariousregulatorybodies,adoptionof machinelearning,advancedsof tware,andin activesaf etyandinf otainmentintheautosectoralsoshouldhappenataf asterclip. Retailapplicationsarealsoexpectedareexpectedtof acilitatesmarterandmoreaccurate decisionmaking;answerquestionsquickly,accurately,andatscale;providemoreintelligence (relationships)betweenlargesetsof data(images,videos,texts,voice)thancurrentlyallowed; andperceiveandunderstandtheworldsimilarlyashumansf romrawdatainputs.Wehaveseen alreadythisinthef ormof recommendationsf rommajoronlineretailers(basedonconsumerbuying history).Thenextwaveshouldhelpcustomersinstantaneouslyrecognize,locate,andpurchase anymerchandisetheyviewastheybrowseimagesontheinternet. DeepLearning2.0inRobotics Theroboticsrevolutionisstartingtoheatup.Thebigquestionnowishowsignif icantof amegatrendroboticswillbecome.Af terall,whereveryoucomparethehighercostsof ahumanbeingto amachine,andtakeintoconsiderationthef asterpayback(intermsof returnoninvestedcapital) of substitutingamachinef orahuman,itbecomesano-brainerf oralotof sectorstoautomateon thislevel. Deeplearningpromisestomakeroboticsmoreintelligentandubiquitous,includingtheintroduction of personalrobotandlargedeploymentof commercialdrones. AccordingtotheBostonConsultingGroup(BCG),by2025,theshareof tasksperf ormedby robotswillrisef romaglobalaverageof around10%toabout25%acrossallmanuf acturing industries.Asaresultof widerroboticsadoption,manuf acturingproductivity,accordingtoBCG, hasthepotentialtorisebyupto30%,andaveragemanuf acturinglaborcostscoulddrop,f or example,by33%inSouthKoreaand18–25%inChina,Germany,theUnitedStates,andJapan. HowDeepLearningTiestoOurInvestmentThesis Whileconsumerandenterpriseinnovationisslowing,A.I.innovationisonabreakneckpace.As oneprominenttechnologyexecutiveputitinatarecentpresentation:“ThisA.I.technologyishow [variouscompanies]respondtoyourspokenword,translatespeechortexttoanotherlanguage, recognizeandautomaticallytagimages,andrecommendnewsf eeds,entertainment,andproducts thataretailoredtowhateachof uslikesandcaresabout.Startupsandestablishedcompaniesare nowracingtouseA.I.tocreatenewproductsandservices,orimprovetheiroperations.” Winnersinthisarenawillhavetoadaptquicklytothisnextwaveof innovation,lesttheybe disruptedbymoreagileplayers.Af terall,deep-learningtechnologyisopen-sourcedandcloudbased.Combiningthosef actorswithf astmobilebandwidth,consumer-drivenservices,andthe necessarycomputingpowerhasthepotentialtoreachmorethanthreebillionglobal,connected consumersinstantly,creating,inmyview,avirtuouscirclearoundinnovation. Theinvestmentramif icationsf orInternetcompaniescouldbehuge.Foronething,globaladoption of deep-learningtechnologieshasthepotentialtoacceleratetheprof itpoolof existinginnovators. Italsohasthepotentialtoshif tlargeprof itsawayf romestablishedplayersandtowardnew players,particularlywhenitcomestosmartphonesandservicesandthecarindustry. Forthesemiconductorindustry,programmablehigh-perf ormancechipsarethekeyenablersto deeplearning,especiallysinceitisverylikelytobedeployedenmasse,eitherwithinmobile devicesthemselvesascomputingpowerandpowerconsumptiongettothepointof supportingalldaydeeplearning,orinthecloudwhereintelligencecanbeprocessedinsupportof mobile devices.Themostinnovativeprovidersof high-perf ormancecomputing,networkingandmemory shouldbenef itf romthistrend. Inthemeantime,sof twarecompanieswillneedtoembeddeeplearningorbringtomarketnew 3 applicationsthatleveragedeeplearning.Hardwarecompanies,ontheotherhand,mayneedmore timetomoveupthedeep-learningcurve.Inf act,onlyonecompanysof arhasplacedabigbeton thesuccessof cognitivecomputing. Thebottomline:Technologyischangingf asterthanever,andcompaniesthatembracethe disruptivepotentialof deeplearninghavethepotentialtotransf ormthemarketplaceandgrow f asterthantheircompetition. EricGhernatiisaTechnologyResearchAnalystatLordAbbett. 1Alphaisthedif f erencebetweenaf und'sexpectedreturnsbasedonitsbetaanditsactualreturns.Someinvestors interpretthatasthevaluethataportf oliomanageradds,aboveandbeyondarelevantindex'srisk/rewardprof ile. 2Machinelearningisabranchof computersciencethatevolvedf romthestudyof patternrecognitionand computationallearningtheoryinartif icialintelligence.ArthurSamuel,ascientistperhapsbestknownf orcomputer checkers,def inedmachinelearningin1959asa"f ieldof studythatgivescomputerstheabilitytolearnwithoutbeing explicitlyprogrammed." Theinf ormationprovidedhereisf orgeneralinf ormationalpurposesonlyandshouldnotbeconsideredan individualizedrecommendationorpersonalizedinvestmentadvice. Investinginvolvesrisk,includingpossiblelossof principal. Forecastsandprojectionsarebasedoncurrentmarketconditionsandaresubjecttochangewithoutnotice. Projectionsshouldnotbeconsideredaguarantee. Theopinionsintheprecedingcommentaryareasofthedateofpublicationandsubjecttochangebasedonsubsequent developmentsandmaynotreflecttheviewsofthefirmasawhole.Thismaterialisnotintendedtobelegalortaxadviceand isnottoberelieduponasaforecast,orresearchorinvestmentadviceregardingaparticularinvestmentorthemarketsin general,norisitintendedtopredictordepictperformanceofanyinvestment.Investorsshouldnotassumethatinvestments inthesecuritiesand/orsectorsdescribedwereorwillbeprofitable.ThisdocumentispreparedbasedoninformationLord Abbettdeemsreliable;however,LordAbbettdoesnotwarranttheaccuracyorcompletenessoftheinformation.Investors shouldconsultwithafinancialadvisorpriortomakinganinvestmentdecision. Investorsshouldcarefullyconsidertheinvestmentobjectives,risks,chargesandexpensesof theLordAbbettFunds.Thisandotherimportantinformationiscontainedinthefund's summaryprospectusand/orprospectus.Toobtainaprospectusorsummaryprospectusonany LordAbbettmutualfund,youcanclickhereorcontactyourinvestmentprofessionalorLord AbbettDistributorLLCat888-522-2388.Readtheprospectuscarefullybeforeyouinvestor sendmoney. NotFDIC-Insured.Maylosevalue.Notguaranteedbyanybank.Copyright©2017Lord,Abbett& Co.LLC.Allrightsreserved.LordAbbettmutualfundsaredistributedbyLordAbbett DistributorLLC.ForU.S.residentsonly. 4