the spring of ai : leveraging collective disruptor insights
TRANSCRIPT
The AI spring
- LeveragingCollectiveDisruptorInsights
1
Introduction of Turing test
Convergence of innovations has moved AI forward in the last few years
1950
Computational Power
Data Platforms
Better Algorithms
First AI programto play Tic Tac Toe
1960
RDBMS
LOGIC THEOREMS-Single layer learning, Perceptron, Adaline
IBM Deep blue defeats Gary Kasparov
1997
OLAP
NEURAL NETWORKS- Multilayer Back propagation
512Core GPU
2880Core GPU
12000Core GPU
Cost of Computing
$200Per million transistors
$50Per million transistors
$0.05Per million transistors
2011 2015
Watson became Jeopardy Champion
BIGDATA PLATFORMS-HDFS
DEEP LEARNING -Convoluted Neural Network
2
DeepMind’s self-taught AI can beat human players at 29 of 49 Atari games
And is disrupting all industry verticals
1- Analysed basis data maturity, software penetration, regulatory restrictions across the value chain representing disruption potential over next 5 years2 – Analysed basis current investments ( talent + acquisition) for all players
BFSI
Healthcare
Pote
ntia
l to
Dis
rupt
ion
1
AI Maturity 2
Retail
Predictive diabetes management solution
AI based Robo advisory service.
Enterprise Software
Semicon
Consumer Electronics Microsoft cloud platform Azure, has NLP capabilities
Nvidia’s Machine Learning Enabled Hardware - 12x faster.
Recommends what styles to wear based on current customer photographs
Driven 130 million miles using the autopilot feature since
2014.Auto
Aerospace
Consumer Software
95% of Facebook’s $17B revenue was generated through ML enabled Advertising.
3Source: GEIP
Telecom
Artificial neural network to adjust helicopter rotors faster and more accurately
Amazon Echo-equipped with the NLP platform Alexa.
Healthcare
Infrastructure
Tech Mafias are building an AI-first future
Automotive Consumer
AI Talent Acquisition Patents 30K $10 B 300+
Wearables for Health monitoring
Project Titan
Siri controlled home kit
AppleSmartwatch
iPhone iOS 10 image recognition
Spotlight for images & text Siri
AIPlatforms
Kinect
SwiftKey
Cortana for Healthcare
Microsoft –Volvo Self driving
Cortana
Microsoft Graph –Sales lead scoring
Hololens
Azure MLDSSTNE
Oculus
Facial recognition
Facebook M
Facebook Deeptext
FAIRWit.ai
Alexa
Recommender systems
AWS MLCNTK
4Source:GEIP
Allo
Google Home
Verily –algorithms for Diagnosis
Deepmind for Healthcare
Google X nanoparticle
research
Google X –Self Driving
Android Wear Smartwatch
AI Robot-GoogleX
Google Prediction API
Google Now
Tensorflow
Project Jacquard
Deepmind Google for Work
5
Sensing the opportunity, VCs have increased their investment in AI start-ups
Quarterly funding trend (2013-16 YTD)
Q1, 2012
Q1, 2013
Q1, 2014
Q1, 2015
Q1, 2016
$94$137
$253
$121
$302
$552
$926 $901
$602
$1,049Raises $100M for Deep learning based ultrasound
Google acquires Deepmind for$500M
Raises $65M for ML based threat detection
Q1, 2011
Focussing on reverse engineering the neocortex raised series A
AI based unicorns have emerged since July, 20165
Billion Dollar Valuation Line
Zoox
Valuation - $1.85 BnHealthcare
Valuation - $1.55 BnAutomotive
Valuation - $1.5 BnEnterprise
Valuation - $1 BnConsumer
Valuation - $1 BnHealthcare
Valu
atio
n
Age of Start-up
Zymergen
Healthcare
Infrastructure
AI start-ups are ambitious and trying to disrupt various industry verticals
Automotive Consumer
AI Talent Funding Patents 45K $15 B 200+
iCarbonX
ZooxApi.ai
Lumiata
ButterflyZymergen
Drive.ai
Affectiva
H20.ai
Attivio
AI Platforms
Imagen Technologies
Nutonomy
Diffbot
Sentient.ai
x.ai
Vicarious Systems TrifactaAyasdi
6Source: GEIP
MobilEye
ZenDriveAnki Jibo
Magisto
Ugobe Mioji
Luka
Gluru
EmotechSherpa
SentenAI
SigOpt
$ 721 Mn in investments
$ 1217 Mn in investments
$ 365 Mn in investments
$ 1032 Mn in investments
$ 996 Mn in investments
7
Traditional methods of analysing individual competitors doesn’t work in analysing start-ups
Porter’s Five Forces Model SWOT Analysis7S Framework
8
SWARM DISRUPTIONFRAMEWORK
Leveraging fresh lenses to understand the collective impact of disruptive start-ups in highly
dynamic segments like artificial intelligence to track developments in key business dimensions
Zinnov’s Swarm Disruption Model provides an holistic approach to gain insights from start-ups
9
Uses data from Zinnov’s proprietary database on start-ups
10
Sample lenses used to gain insights on the AI Swarm disruptions
Value Chain Disaggregation
Understand collaboration points with AI start-ups across the industry value chain
Deadpool Intensity
Analyse constraints for AI start-ups to scale and gain perspective into market conditions
Absorption Pulse
Examine the focus areas and drivers for M&A & investment strategies of incumbents
Use Case Adoption
Patterns on the top use cases adopted by highly scalable general purpose AI platforms
Global Ecosystem Maturity
Congregation of AI start-ups in enabling ecosystems across the world
Skillset Transformation
Adapt to the changing human capital needs to drive an AI-first business strategy
Value Chain Disaggregation
11
Start-ups are leveraging deep learning techniques to build solutions for autonomous cars and infotainment systems
ADAS Driver Safety Autonomous cars
Image Processing
Connected Car/ Infotainment
Machine Learning
NLP
Computer Vision
DeepLeaning
$24M
$10M
$80M
$18M
$337M
Tota
l Fun
ding
of V
alue
Cha
in S
egm
ent
VALUE CHAIN SEGMENT
AI T
ECH
NO
LOG
Y
Key Trends in Auto Start-up LandscapeImpact Assessment of AI start-ups in the automotive value chain
HighLowAI Tech Adoption
Tier 1 players on acquisition
spree
Interest from Non Automotive
Companies
OEMs creating innovation labs
in Bay Area
Emergence of New Tier 1
players
12
AI start-ups are leveraged across the retail value chainby large retail enterprises
Security& Surveillance
Supply Chain Management
In-Store Analytics
Customer Engagement
Multi-Channel Marketing
Subscription Model
Licensing Model
One Time Payment
Affiliate Fees
$24M
$ 90M
$ 159M
$ 100M $105M
Tota
l Fun
ding
of V
alue
Cha
in S
egm
ent
Acquired predictive Intelligence Platform to reduce fraud and improve customer targeting
Customer Engagement
Supply Chain Management
Acquired Machine learning platform that solves out-of-stock and overstocking problems
Top retailers are partnering with AI start-ups to bolster their value chain
Impact Assessment of AI start-ups in the retail value chain
Lowe’s set up an innovation lab in Bangalore for AR/VR tools on demand manufacturing and robotics
Value Chain Disaggregation
BU
SIN
ESS
MO
DEL
S
VALUE CHAIN SEGMENT
HighLowAI Tech Adoption
13
AI platform companies are prioritizing use cases in Finance, Marketing and Healthcare
Total Funding
Patents
Vicarious Systems DataRobot
$135.8 Mn $97.9M $75.6 Mn $67M $57.4 Mn
8 16 9 - 3
Total Funding
Patents
$48M $37.4 Mn $34.2 M $30.6 Mn $30M
4 29 42 - 2
Sentiment Analysis
Personal-ization
Customer Engagement
Digital Marketing
Marketing
Fraud Detection
Insurance claims
Algorithmic Trading
Risk Modelling
Finance
Patient Monitoring
Drug Delivery
Population Health
Precision Medicine
Clinical Variance
Healthcare
Use Case Adoption
14
US is the dominant innovation hotbed for AI start-ups led by the Bay Area Ecosystem
2322Start-ups
$14.74Billion
Global AI start-up distribution
86Canada
Netherlands25
26Australia
Brazil
18
France
43
25 Singapore
Hong Kong12
Total FundingNo. of Start-ups
Global AI start-up distribution
$11.5 B
$0.6B
$0.03 B$0.5 B
$0.6 B
$0.1 B $0.1 B
$0.1 B
APPLICATIONS-FINTECH, HEALTHCARE
APPLICATIONS –HRTECH, HEALTHCAREAPPLICATIONS – AUTO, FINTECH, RETAIL
PLATFORMS- DEEPLEARNING, VISION
ENABLERS –BIGDATA PLATFORMS
Vision based advanced assistance system
AI based consumer robotics start-up
Massively scaled deep learning
ML based threat detection
ML based recruitment solution
ML for retail
ML for personalised healthcare
NLP API
Data cataloguing and cleaning
PLATFORMS- DEEPLEARNING, NLP
GlobalEcosystemMaturity
$0.1B
6deals
15
Corporate acquisitions and investment strategies indicate the direction the industry is focussed on
BuildNewProducts
BolsterTechnologyStack
23deals
$625MGoogle
Deepmind
EnterNewMarkets
10deals
Notdisclosed
Amazon
Snaptell
Wit.aiNot
Disclosed
AcquihireTalent
6deals
Intel
IndisysNot
Disclosed
TechnologyandmarketexpansionareprimarydriversforM&A
Amazon Apple Facebook MicrosoftGoogle
AcquisitionYear
Acqu
ireeMaturity
DotComEra SmartphoneEra CognitiveEra
2004 2010 2016
1
2
3
4
5BulkoftheacquisitionsbyMicrosoft and
Google toboosttheirSearchTech.
MS andApple beginworkonGestureControl
devices.TheTechMafiainvestingheavily
inAIenablementplatformsGoogle beginworkonMaps
NLP VisionML NLP Vision ML NLP Vision Robotics
IndicatesAverage
Salesforce Intel Oracle IBM GE
AbsorptionPulse
16
LegendApplication CompaniesPlatform CompaniesInfrastructure Companies
Consumer Enterprise IndustryML NLP Vision
Data Platform Hardware
Age of Start-up0 2 4 6 8 10 12
Deadpool
Scal
e (B
ased
on
Inve
stm
ents
, Hea
dcou
nt G
row
th a
nd C
usto
mer
Tra
ctio
n)
Major factors that have prevented AI start-ups from crossing the value chasm
Regulatory Restrictions
Business Model
Product Market Fit
Regulatory restriction and lack of product/market fit dominates the reason for start-up failures
Series A
Seed. $3.1M
Series C
Comma.ai
*700 Start-ups plotted
Deadpool Intensity
17
AI start-up engineering footprint distantly different fromincumbent competitors
R&D
IT
Sales & BD
Product Management
Others
29.7% 33%
21.5% 7%
30% 38%
5.8% 4%
13% 17%
HC 10+ yrs exp
Hardware
Software
Architect
Analytics
UI/UX
24%
23%
5%
6%
14%
73%
50%
92%
55%
52%
HC 10+ yrs exp
12%
18%
4%
12%
10%
80%
30%
90%
36%
40%
ML/NLP
Release
QA
11%
8%
11%
42%
27%
73%
43%
-
2%
26%
-
-
Engineering Talent Hired From
Skillset Transformation
18
Swarm Disruption Model will allow enterprise leadership teams to answer several strategic questions
CTO HR
Product Manager
Strategy and M&A
“
“
What are the emerging technology paradigms that disruptors are leveraging to get ahead ?
What is the nature of talent I need to recruit to make my business AI – ready ?
“
“
What are the top locations where my organization can hire new age skills ?
“
“
How mature are start-ups operating in aligned areas and what synergies can they bring ?
Should I invest, acquire or partner with emerging disruptors in my space ?
“
“
What value adding features can be incorporated into my products to enhance customer satisfaction ?
What new business models are gaining traction in my industry ?
19
20
Agenda
APPENDIX
21
Lenses(1/2)Dimension Lens Description
ValueChain ValueChainDisaggregation
IndustriesandOrgfunctionssuchasHR/LegaletcbrokendownintosegmentsofthevaluechainandmappedagainstpotentialforimpactbyAItechnologiesandstart-ups
ValueChain ValueChainAggregation Examinesintegrationofdifferentsegmentsofthevaluechaintoincreasevalue.Forexamplecustomeranalyticsresultinginpredictivesupplychainmanagement
ValueChain ProfitConcentration
Technology TechnologyMaturity Maturityoftechnologyplatformsintheindustryintermsofadoptionandintegrability
Technology Autonomy&Manageability
Capabilityoftechnologytomanageendtoendoperationsandthedegreeofsupport/overheadrequiredtodeliveragoodcustomerexperience
Technology ThirdPartyTools/Infra TheavailabilityofthirdpartytoolsandinfrastructuresuchasAPIs,SDKs,Serversetctoacceleratedevelopmentofnewsolutions
Technology ExtensionPropensity Theabilityofthetechnologytoscaleandaddressawiderangeofusecases
Market UseCaseAdoption PatternsonthetopusecasesadoptedbyhighlyscalablegeneralpurposeAIplatforms
Market MarqueeCustomerTraction
Areaswherestart-upshavebeenabletoon-boardFortune500customersandlargeaccounts
Market DeadpoolIntensity Examinesthestart-upsthathavefailedinindustrysegmentsandthemajorreasonsforfailure
Market NonConsumptionIndex Examinesmarketsegmentsthathavewitnessedvolumesofnewentrantsbutlimitedtraction
22
Lenses(2/2)
Dimension Lens Description
ConsumptionPattern BusinessModeltrends Examinesthenatureofbusinessmodelsacrossindustrysegmentsandidentifiesproliferationofnovelbusinessmodels
ConsumptionPattern NextGenerationInterfaces
Studiesthepreferenceofcustomerstointeractwithtechnology(Voice,Mobile,Webetc)
Consumptionpattern CustomerEngagementParadigm
Initiativestakenbydisruptorstoenhancecustomerengagementonlineandoffline
ConsumptionPattern CustomerExperienceEvolution
Examineshowcustomerexperienceisevolvingacrossindustriesandtheroleplatedbydisruptors
Ecosystem GlobalEcosystemMaturity
UnderstandlocationswithhighproportionoftalentpoolinbuildingAIhorizontalplatformswithacalloutforskillpoolsofMachineLearning,NLP,ComputerVision,BigDataAnalytics
Ecosystem AbsorptionPulse ExaminethefocusareasandkeydriversforM&Aandinvestmentstrategiesofprominentincumbents
Ecosystem Collaborationintensity Identifythepropensityofswarmstocollaboratewithincumbents,universitiesanddevelopercommunitiesacrosssegments
Ecosystem SkillsetTransformation Howengineeringorganizationsareevolvingtobemoreleanandagileinthenewenvironment