introduction to deep learning andneural networks...a neuron is illustrated below. figure 3....
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1
AUGUST30,2016
DEBORAHWEINSWIG,MANAGINGDIRECTOR,FUNGGLOBALRETAIL&TECHNOLOGYDEBORAHWEINSWIG@FUNG1937.COMUS:917.655.6790HK:852.6119.1779CN:86.186.1420.3016Copyright©2016TheFungGroup.Allrightsreserved.
1) Deep learning and neural networks are techniquesused in computer science to analyze data. They areespeciallyusefulinpatternandimagerecognition.
2) Neuralnetworksusesoftwaretomimicthefunctionofthemanyneuronsinthehumanbrain.Thesefunctionscanbe tunedovertime;thismeansman-madeneuralnetworkscanlearn.
3) 3Deep learning refers to the use ofmultiple layers ofneuralnetworks.
4) Consumersbenefit from these technologieseverydaywhen they read curated news headlines, researchrentingaroomonlineorconversewithachatbot.
5) Although the emerging artificial intelligence (AI)marketisestimatedatjust$400millionthisyear,itcanpotentially enhance adjacent markets such asmedicine, consumer electronics, robotics, and mostimportantly,autonomouscars.
6) Many global industrial and technology companies arepursuingautonomouscars.
7) Venture capitalists and technology companies areaggressivelyinvestinginandacquiringAIstartups.
Introduction to Deep Learning
and Neural Networks
D E B O R A H W EI N S W I G M a n a g i n g D i r e c t o r ,
F u n g G l o b a l R e t a i l & T e c h n o l o g y d e b o r a h w e i n s w i g @ f u n g 1 9 3 7 . c o m
U S : 6 4 6 . 8 3 9 . 7 0 1 7 H K : 8 5 2 . 6 1 1 9 . 1 7 7 9
C H N : 8 6 . 1 8 6 . 1 4 2 0 . 3 0 1 6
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AUGUST30,2016
DEBORAHWEINSWIG,MANAGINGDIRECTOR,FUNGGLOBALRETAIL&TECHNOLOGYDEBORAHWEINSWIG@FUNG1937.COMUS:917.655.6790HK:852.6119.1779CN:86.186.1420.3016Copyright©2016TheFungGroup.Allrightsreserved.
EXECUTIVESUMMARY
AIispresentlycausingagreatdealofexcitementintechnologyandfinancialcircles.DecadesofresearchintoAIandneuralnetworkshavefinallycreatedbreakthroughsthatcanbeusedinsystemsthatcananalyzedataandmakepredictions.ThesebreakthroughshaveresultedinstunningamountsbeingpaidtoacquireAIcompaniesandinvest instartups.Atthesametime,theexcitement over AI has created buzzwords such as “deep learning” and“neuralnetworks,”buttheyarereallyjustwaystoanalyzeandidentifydatawithintherealmofcomputerscience.
Todevelop these approaches, scientists andprogrammers have turned tothemysterioushumanbrainandthetrillionneuronsinsideitthattransmitand process information, as the model for analyzing data. They havedevelopednetworksof cells thatmimic the functionofneurons.Althoughthis approach has gained and lost favor over time among computerscientists it is currently considered the best approach to accurately andproductively identify patterns. Patterns are extremely important in AI;images of handwritten objects or obstacles in the path of a movingautonomousvehiclearepatternsthatneedtobeidentifiedandhandled.
Source:Shutterstock
AlthoughtheAI industry isestimatedatamere$400million in itscurrentinfant state, the market could encompass tens of billions of dollars asadjacentindustriessuchasautonomouscars,robots,military,medicineandconsumer electronics embrace the technology. As mentioned above,technologythatcanidentifyobstaclesintheroadisextremelyimportanttofirms who offer and guarantee a safe ride in an autonomous vehicle.Industrial and technology companies around the globe are aggressivelypursuingthispotentially importantandhugemarket.TherecentadvancesinAIcombinedwith thepotentially largemarkets thatcouldbeenhancedby the technology,are the likely reason for theavalanche in fundingofAIstartupsandthebiddingwarsthathaveoccurredtoacquirethem.
The good news for us humans is neural nets and deep learning have thepotential to improve our lives.We already use them every daywhenwe
AlthoughtheAIindustryisestimatedatamere$400millioninitscurrentinfantstate,themarketcouldencompasstensofbillionsofdollarsasadjacentindustriessuchasautonomouscars,robots,military,medicineandconsumerelectronicsembracethetechnology.
Thehumanbrainiscomprisedof1quadrillionneuronsthatcommunicatewitheachother.
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AUGUST30,2016
DEBORAHWEINSWIG,MANAGINGDIRECTOR,FUNGGLOBALRETAIL&TECHNOLOGYDEBORAHWEINSWIG@FUNG1937.COMUS:917.655.6790HK:852.6119.1779CN:86.186.1420.3016Copyright©2016TheFungGroup.Allrightsreserved.
read a BuzzFeed article or look up a room on Airbnb. These twotechnologies are purelymethods for analyzing data anddonot appear tolead to computers that become autonomous and self-aware, the stuff ofmanyfrighteningscience-fictionstories.
INTRODUCTION
Neural nets are tools that can be createdwith electronics or software toemulate some of the function of a neuron, which comprise the humanbrain.
Thehumanbrain is comprisedof1quadrillionneurons that communicatewith each other. As in the human brain, many artificial neurons can becombined in a network to communicate with each other. Deep learningreferstotheuseofmultiplelayersofneuralnetworksinordertoincreaseaccuracyandproductivity.
Source:Shutterstock
Specifically,neuralnetsaregoodatidentifyingpatterns—inimages,speech,data, or even stock prices. The neurons contain programmable elementsthatareusedtoevaluatetheir inputs,andsincetheparameterscontainedwithin these neurons can be changed or tuned to make the patternidentificationmoreaccurate,thenetwork“learns”toidentifythoseimages.
One application of neural nets is handwriting recognition. In this case, aneural net is fed a sequence of handwritten digits, and the weights aretuneduntil thenetworkcanrecognizethedigitswithacceptableaccuracy.The Mixed National Institute of Standards and Technology (MNIST)establishedadatabaseof60,000 trainingdigitsand10,000 testing imagesfortuningandtestinghandwritingrecognitionsystems.SomeoftheMNISTdigitsareincludedinthefigurebelow.
Deeplearningreferstotheuseofmultiplelayersofneuralnetworksinordertoincreaseaccuracyandproductivity.
Theparameterscontainedwithintheseneuronscanbechangedortunedtomakethepatternidentificationmoreaccurate,thenetwork“learns”toidentifythoseimages.
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AUGUST30,2016
DEBORAHWEINSWIG,MANAGINGDIRECTOR,FUNGGLOBALRETAIL&TECHNOLOGYDEBORAHWEINSWIG@FUNG1937.COMUS:917.655.6790HK:852.6119.1779CN:86.186.1420.3016Copyright©2016TheFungGroup.Allrightsreserved.
Figure1.MNISTTesting/TrainingDigits
Source:neuralnetworksanddeeplearning.com
Neural nets date back to the 1940s, when neurophysiologist WarrenMcCulloch and mathematician Walter Pitts published a paper thatdescribedhowelectricalcircuitscouldbeusedtocreateaneuralnetwork.In the 1960s, the interest of computer scientists turned to vonNeumannarchitectures that are basedon a CPU, logic andmemory, and interest inneural nets waned. However, in the 1980s, some groundbreakingdevelopments in neural nets reinvigorated interest, which continuesthrough the present day. Many researchers consider deep learning “themostaccurateandproductivetechniqueinAIresearchtoday,”accordingtoCBInsights.
Therearedeeplearningandmachinelearninginproductsandservicesweconsumeanduseeveryday,including:
• ProductrecommendationsfromAmazon
• HeadlinesfromBuzzFeed
• PricesontheAirbnbwebsite
• Facebook’sMassistant
Google has integrated a deep-learning machine with its Street Viewplatform to enable the identification of nearly every location, and thecompanyisalsousingitsownDeepMindAItechnologytoreducetheenergyusedtocoolitsdatacenterby40%.
AIANDNEURALNETWORKS
AI refers to thebranchof computer science thatuses computers toapplyhumanintelligencetosolveproblems.WithinAI,machinelearningreferstothetechniquesusedtoperformcognitivefunctions.Deeplearningreferstotheuseofmultiple layersofneuralnetworks.The relationshipamong thethreeisshownintheVenndiagrambelow.
Figure2.HierarchyandInteractionofAIApproaches
Source:CBInsights
Neuralnetsdatebacktothe1940s,whenneurophysiologistWarrenMcCullochandmathematicianWalterPittspublishedapaperthatdescribedhowelectricalcircuitscouldbeusedtocreateaneuralnetwork.
AIreferstothebranchofcomputersciencethatusescomputerstoapplyhumanintelligencetosolveproblems.WithinAI,machinelearningreferstothetechniquesusedtoperformcognitivefunctions.Deeplearningreferstotheuseofmultiplelayersofneuralnetworks.
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AUGUST30,2016
DEBORAHWEINSWIG,MANAGINGDIRECTOR,FUNGGLOBALRETAIL&TECHNOLOGYDEBORAHWEINSWIG@FUNG1937.COMUS:917.655.6790HK:852.6119.1779CN:86.186.1420.3016Copyright©2016TheFungGroup.Allrightsreserved.
Deeplearningisjustonewaytocreatemachinelearning.Othersinclude:
• AssociationRule
• Bayesian
• Clustering
• DecisionTrees
• DimensionalityReduction
• Ensemble
• Instance-based
• Others
• Regression
• Regularization
NEURALNETWORKS
Thehumanbrain iscomposedofabout100billionbraincells,orneurons,andeachneuroncanconnectto10,000otherneurons.Thus,ahumanbraincancontain1quadrillion,i.e.,1,000trillion,synapticconnections.Aneuronisillustratedbelow.
Figure3.IllustrationofaNeuron
Source:appsychology.com
Anartificialneuron,orperceptron,worksmuchthesamewayasahumanneuron,withinputsandoutputs,anditsfunctionaldiagramappearssimilartoaneuron.Severalinputsconnecttoaneuron,whichcanbeimplementedinelectronicsorinsoftware.Theelectronicdeviceorsoftwarecontainsanalgorithmthatusesamathematicalfunctiontocreatearesult,whichissenttotheoutput.
The figurebelow illustrates anartificial neuron inwhich theoutput is thesumofeachoftheinputs,multipliedbyaweightingfactorviatheobjectivefunction.Theresultisconsideredaoneorzero,dependingonwhethertheoutput exceeds a certain threshold value.Neurons can also use nonlinearandmorecomplexmathematicalfunctions.
Thehumanbrainiscomposedofabout100billionbraincells,orneurons,andeachneuroncanconnectto10,000otherneurons.Thus,ahumanbraincancontain1quadrillion,i.e.,1,000trillion,synapticconnections.
Anartificialneuron,orperceptron,worksmuchthesamewayasahumanneuron,withinputsandoutputs.
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AUGUST30,2016
DEBORAHWEINSWIG,MANAGINGDIRECTOR,FUNGGLOBALRETAIL&TECHNOLOGYDEBORAHWEINSWIG@FUNG1937.COMUS:917.655.6790HK:852.6119.1779CN:86.186.1420.3016Copyright©2016TheFungGroup.Allrightsreserved.
Figure4.DiagramofanArtificialNeuron
Source:Infinitemusings.com/FungGlobalRetail&Technology
DEEP-LEARNINGNEURALNETWORKS
Deeplearningisnotamachine-learningapproachinitself,butratherreferstotheuseofmultiplelayersofprocessing.Deepneuralnetworkshavetwoormorehiddenlayers,asdepictedinthefigurebelow.
Figure5.DeepNeuralNetwork
Source:neuralnetworksanddeeplearning.com
APPLICATIONS
Applicationsforneuralnetsanddeeplearningcenteronimagerecognitionand processing, however the networks can be applied to any data orinformationthatcontainspatterns.Examplesinclude:
• Computervision
• Datamining
• Imageprocessing/compression
• Natural-languageprocessing
• Character/patternrecognition
Inputs
Output
Weights
ObjectiveFunction
Deeplearningisnotamachine-learningapproachinitself,butratherreferstotheuseofmultiplelayersofprocessing.Deepneuralnetworkshavetwoormorehiddenlayers.
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AUGUST30,2016
DEBORAHWEINSWIG,MANAGINGDIRECTOR,FUNGGLOBALRETAIL&TECHNOLOGYDEBORAHWEINSWIG@FUNG1937.COMUS:917.655.6790HK:852.6119.1779CN:86.186.1420.3016Copyright©2016TheFungGroup.Allrightsreserved.
• Robotics
• Stock-marketprediction
Other applications continue to be discovered, such as in medicine,identifyingodors,securityandlawenforcementandloanqualification.
Image processing and identification is a very hot topic these days, sincemany companies in the industrial, automotive and technology sectors areracing to develop autonomous vehicles, i.e., self-driving cars, that canidentifyandavoidtypicalandunforeseenobstaclesontheroad.
APPLICATIONINAUTONOMOUSVEHICLES/SELF-DRIVINGCARS
Self-driving cars need advanced image-processing and identificationplatforms inorder tonavigatearoundandavoidobjectsand impedimentsontheroad.
InadditiontotheworkofTeslaandmajorautomobilemanufacturers,manyglobal industrial, technology and software companies are pursuing thedevelopmentofself-drivingcarsandresearchingdeeplearning.
• TherearenumerousreportsthatdetailApple’sresearchandeffortstodevelopanautonomousvehicle.
• Google is developing autonomous vehicles and is documenting on itsblogthetestsitisrunningnearitsSiliconValleyheadquarters.
• Chip companies such as NVIDIA and Qualcomm are developingmachine-visionchipsforuseinautonomousvehicles.
Chinesetechnologygiantsarealsoaggressivelypursuingtheintroductionofself-drivingcars:
• OnlinemarketplaceAlibabalaunchedaventurewithChinesecarmakerSAIC todevelop Internet-enabledcars.Managementcommented theycanquicklydevelopself-drivingcarsfromtheplatform.
• ChinesewebportalBaiduhastestedaself-drivingcarontheroadsofBeijing.
Self-drivingcarsneedadvancedimage-processingandidentificationplatformsinordertonavigatearoundandavoidobjectsandimpedimentsontheroad.
Chinesetechnologygiantsarealsoaggressivelypursuingtheintroductionofself-drivingcars.
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AUGUST30,2016
DEBORAHWEINSWIG,MANAGINGDIRECTOR,FUNGGLOBALRETAIL&TECHNOLOGYDEBORAHWEINSWIG@FUNG1937.COMUS:917.655.6790HK:852.6119.1779CN:86.186.1420.3016Copyright©2016TheFungGroup.Allrightsreserved.
• TencentannouncedapartnershipwithTaiwan’sFoxconnandaChineseluxuryautodealertoexploreopportunitiesindevelopingsmartelectricvehicles.
• CarmakerChongqingChanganAutomobile Co. launchedaself-drivingcar that uses cameras and radar. The vehicle completed a 1,200-miletripinApril2016.
MARKETS
AlthoughthemarketforAIisestimatedtobefairlysmallthisyear,just$400million,marketresearchersexpectrevenuestogrowatahealthy50%+rate,andsurpass$10billionin2024,asillustratedinthegraphbelow.
Figure6.AIRevenue(USDMil.)
Source:Tractica
Intheabovegraph,weseetheAsia-PacificregionisforecasttopassNorthAmericainmarketsizein2019.
There are several adjacent markets that can benefit from AI, includingrobotics, autonomous cars, unmanned aerial vehicles and healthcare, asdepictedinthefigurebelow.
Figure7.SelectedRelatedAIMarketsin2020(USDBil.)
Source:BostonConsultingGroup/Companyreports/euRobotics/Frost&Sullivan/IHSAutomotive/InternationalFederationofRobotics/JapanRobotAssociation/MinistryofEconomy,TradeandIndustry/TealGroup/FungGlobalRetail&Technology
$0
$5,000
$10,000
$15,000
15 16E 17E 18E 19E 20E 21E 22E 23E 24E
NorthAmerica WesternEurope EasternEurope Asia-PacificLannAmerica MiddleEast Africa
CAGR2016–24E=50.9%
$16.4
$8.0 $7.5$4.8
$0.0
$5.0
$10.0
$15.0
$20.0
Roboncs AutonomousCars(2025E)
UnmannedAerialVehicles
Healthcare
AlthoughthemarketforAIisestimatedtobefairlysmallthisyear,just$400million,marketresearchersexpectrevenuestogrowatahealthy50%+rate,andsurpass$10billionin2024.
ThereareseveraladjacentmarketsthatcanbenefitfromAI,includingrobotics,autonomouscars,unmannedaerialvehiclesandhealthcare.
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AUGUST30,2016
DEBORAHWEINSWIG,MANAGINGDIRECTOR,FUNGGLOBALRETAIL&TECHNOLOGYDEBORAHWEINSWIG@FUNG1937.COMUS:917.655.6790HK:852.6119.1779CN:86.186.1420.3016Copyright©2016TheFungGroup.Allrightsreserved.
STARTUPS,ACQUISITIONSANDVENTURE-CAPITALFUNDING
Startups
Thepotentialandpowerofdeeplearninghascreatedseveralstartupsthatdevelop applications. During the past five years, large technologycompanies have aggressively acquired them. At the same time, venture-capitalfinancinghasfloodedintotheindustryatarapidrate.
Severalinnovativeprivatecompaniesareoutlinedinthetablebelow.
Figure8.SelectedPrivateMachine-LearningCompanies(USDMil.)
Company Description Location TotalFunding
Sentient UsesadvancedAItechnologytosolvecomplexbusinessproblems
SanFrancisco,CA
$136
Ayasdi Machineintelligenceplatformthathelpsorganizationsbenefitfrombigdata
MenloPark,CA
$106
DigitalReasoning CognitiveComputingforenterprises Franklin,TN $74
Vicarious Avisualperceptionsystemthatinterpretsphotographsandvideos
SanFrancisco,CA
$72
DataRobot Machinelearningplatformforbuildingaccuratepredictivemodels
Boston,MA $57
Source:CBInsights/Companies
Acquisitions
There has been an explosion in the acquisition of machine-learning anddeep-learningcompaniesbylargecompanies,totaling31acquisitionssince2011, according to CB Insights. The table below lists selected acquisitionsfromthatlist.
Figure9.RecentMachineLearningAcquisitions
Company Business Acquirer Date
Turi MachinelearningandAI Apple Aug.2016
MagicPony Machinelearningandvisualprocessingtechnology
Twitter Jun.2016
Itseez Computervisionandpatternrecognition
Intel May2016
Emotient Emotion-detectiontechnology Apple Jan.2016
VocalIQ Speech-processingforimprovedhuman-machineinteraction
Apple Oct.2015
Saffron Cognitivecomputingplatform Intel Oct.2015
Thepotentialandpowerofdeeplearninghascreatedseveralstartupsthatdevelopapplications.Duringthepastfiveyears,largetechnologycompanieshaveaggressivelyacquiredthem.Atthesametime,venture-capitalfinancinghasfloodedintotheindustryatarapidrate.
Therehasbeenanexplosionintheacquisitionofmachine-learninganddeep-learningcompaniesbylargecompanies,totaling31acquisitionssince2011.
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AUGUST30,2016
DEBORAHWEINSWIG,MANAGINGDIRECTOR,FUNGGLOBALRETAIL&TECHNOLOGYDEBORAHWEINSWIG@FUNG1937.COMUS:917.655.6790HK:852.6119.1779CN:86.186.1420.3016Copyright©2016TheFungGroup.Allrightsreserved.
Company Business Acquirer Date
Whetlab Technologytomakemachinelearningbetterandfaster
Twitter Jun.2015
Madbits Deeplearning-basedvisualintelligenceplatformtoidentifyimagecontent
Twitter Jul.2014
DeepMind Self-learningalgorithms Google Jan.2014
Indisys Natural-languageprocessing Intel Sep.2013
DNNResearch Deeplearningandneuralnetworksforimagesearch
Google Mar.2013
IQEngines Image-recognitionsoftware Yahoo Aug.2013
LookFlow APIforimagerecognitionandcategorization
Yahoo Oct.2013
SkyPhrase Natural-languageprocessingtechnology
Yahoo Dec.2013
DarkBlueLabs Deeplearning-basedtechnologyforunderstandingnaturallanguage
Google Oct.2014
VisionFactory Objectandtext-recognitionusingdeeplearning
Google Oct.2014
Source:CBInsights/Companies
Venture-CapitalFunding
Venture-capital fundingofAI nearlydoubled in2013andnearly tripled in2014, according to CB Insights. The amount of funds raised and dealscompletedincreasedfurtherin2015,asdepictedinthefigurebelow.
Figure10.GlobalAIVCFinancing(USDMil.)
Source:CBInsights
$282 $415$757
$2,177 $2,388
67
131
196
307
397
0
50
100
150
200
250
300
350
400
450
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
2011 2012 2013 2014 2015
Num
berofDealsDisclosedInvestmen
t
DisclosedInvestment NumberofDeals
Venture-capitalfundingofAInearlydoubledin2013andnearlytripledin2014,accordingtoCBInsights.Theamountoffundsraisedanddealscompletedincreasedfurtherin2015
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AUGUST30,2016
DEBORAHWEINSWIG,MANAGINGDIRECTOR,FUNGGLOBALRETAIL&TECHNOLOGYDEBORAHWEINSWIG@FUNG1937.COMUS:917.655.6790HK:852.6119.1779CN:86.186.1420.3016Copyright©2016TheFungGroup.Allrightsreserved.
CONCLUSION
Although deep learning and neural networks are technology buzzwordstoday, they comprise real products and services we use on a daily basis.Deep learning and neural networks use software to mimic how neuronsfunction in the human brain. They are particularly good at patternrecognitionandimageprocessingbecausetheylearnwhentheirfunctionismodified. These technologies will likely enable many global markets,particularlyautonomouscars.Manyglobalindustrialandtechnologygiantsareaggressively researchingAI,and thiscoincideswithan investmentandacquisitionboominAIstartups.
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AUGUST30,2016
DEBORAHWEINSWIG,MANAGINGDIRECTOR,FUNGGLOBALRETAIL&TECHNOLOGYDEBORAHWEINSWIG@FUNG1937.COMUS:917.655.6790HK:852.6119.1779CN:86.186.1420.3016Copyright©2016TheFungGroup.Allrightsreserved.
DeborahWeinswig,CPAManagingDirectorFungGlobalRetail&TechnologyNewYork:917.655.6790HongKong:852.6119.1779China:86.186.1420.3016deborahweinswig@fung1937.comJohnHarmon,CFASeniorAnalyst
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