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DeepLearning:SmarterArtificialIntelligence
March24,2016
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“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
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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
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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
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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
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