1
Rise of Applied AI
Manish Singhal, Partner, pi Ventures
2
$75 bn market
globally. Current
solutions are
expensive, unreliable
for Indian conditions.
Not much data is
digital either
cellphone camera
attached to
microscopes,
images are captured
and sent to cloud
By
leveraging deep
learning on the
images, faster and
cheaper (5x) and more
accurate diagnostics
can be made at
scale
Founders come
from data science lab
of Amex, having built
enterprise scale
solutions earlier on
deep learning
Applying Deep Learning to Diagnostics
3
India is at a Great Inflexion Point
More bank
accounts opened in
India last year than the
total number of bank
accounts are in US
More than 1 bn
citizens came onto
the digital grid through
universal ID project in
last 5 years
In just last 12
months, more than
100mn new mobile
wallets were created
from Zero base.
4
India is becoming a Mobile Nation
By 2020, avg age
in India is going to
be 29, tech savy and
early adopter. Mobile
data will cross 1
Exabyte by 2019
435mn
Smartphones by
2019, will disrupt both
B2C and B2B
customer workflows
$500bn
discretionary
spending signalling
large market. India
would be 3rd largest
economy by 2030.
Built
proprietary deep
learning platform
and latency
optimisations schemes,
beats google for
accuracy for Indic
languages
5
Voice Interface is
a big opportunity for
mobile and IoT as
Indic languages will be
the 2nd language by
2050 after
Chinese
Ex.
Microsoft (Bing
Research), Ph. D.
Signal Processing with 7
patents in signal
processing
(Qualcomm) &
Samsung
Best speech
solution for Hindi
and even English in
Indian accent with >
90% accuracy, highly
scalable API and
SDK.
Voice is the most Natural Interface
Very simple
saving instrument
like Fixed Deposit and
saving’s account, are
used by most of Indians.
Only 9% invest in
Mutual funds
6
Working Class
millennials in India
(15-20mn) have close to
$100bn in saving
potential. Overall
potential of $1.1 tn
Founders are ex-
Flipkart with deep
experience in mobile,
technology and domain
Mining Personal Data For Right Savings Instruments
AI
Maturity
Level 2
Leveraging
Mobile to mine small
data (context of spend)
and using machine
learning to suggest right
saving instruments
to grow money
7
Extreme
Personalisation
Predictive
Business
AI will enable new experiences
Big Data
Small Data
Dark Data
8
India could see rapid Adoption of AI
Retail Fin-tech
Cyber
security
Healthcare
Logistics
Leading AI practitioners
(Microsoft, Google, Amazon) have
done a good job in training good
talent at lower cost points
Indian businesses operate on
lower cost structures, making
AI impact more meaningful for
them, helping in faster adoption
Large adoption of mobile
workflows, create more data,
and fewer regulations, allowing
startups to exploit data growth
Data
Adoption
Talent
Confidential: Please do not share without explicit permission9
Core AI Building
Blocks
Heavy R&D Spend to solve
core problems, ex. NLP,
Image recognition,
Deep Learning,
Speech recognition,
Emotions
Rise of Applied AI
Startups that leverage
core AI frameworks to
create business value
New Category
Leaders
Mature Applied AI,
with new leaders and
consolidation by
incumbents/laggards
*R&D by large Companies pi Ventures
Business Value
1990 2016 2020
We are here
Inflection
Point
*Source : Bootstrap Labs
Now is the Time to Invest in Applied AI
Enterprise
Value
10
In 1600’s India’s share of global GDP was 25%
Thank You!
Manish Singhal
manish@piventures.in
@manish_saarthiwww.piventures.in

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Artificial Intelligence - Trends & Advancements

  • 1. 1 Rise of Applied AI Manish Singhal, Partner, pi Ventures
  • 2. 2 $75 bn market globally. Current solutions are expensive, unreliable for Indian conditions. Not much data is digital either cellphone camera attached to microscopes, images are captured and sent to cloud By leveraging deep learning on the images, faster and cheaper (5x) and more accurate diagnostics can be made at scale Founders come from data science lab of Amex, having built enterprise scale solutions earlier on deep learning Applying Deep Learning to Diagnostics
  • 3. 3 India is at a Great Inflexion Point More bank accounts opened in India last year than the total number of bank accounts are in US More than 1 bn citizens came onto the digital grid through universal ID project in last 5 years In just last 12 months, more than 100mn new mobile wallets were created from Zero base.
  • 4. 4 India is becoming a Mobile Nation By 2020, avg age in India is going to be 29, tech savy and early adopter. Mobile data will cross 1 Exabyte by 2019 435mn Smartphones by 2019, will disrupt both B2C and B2B customer workflows $500bn discretionary spending signalling large market. India would be 3rd largest economy by 2030.
  • 5. Built proprietary deep learning platform and latency optimisations schemes, beats google for accuracy for Indic languages 5 Voice Interface is a big opportunity for mobile and IoT as Indic languages will be the 2nd language by 2050 after Chinese Ex. Microsoft (Bing Research), Ph. D. Signal Processing with 7 patents in signal processing (Qualcomm) & Samsung Best speech solution for Hindi and even English in Indian accent with > 90% accuracy, highly scalable API and SDK. Voice is the most Natural Interface
  • 6. Very simple saving instrument like Fixed Deposit and saving’s account, are used by most of Indians. Only 9% invest in Mutual funds 6 Working Class millennials in India (15-20mn) have close to $100bn in saving potential. Overall potential of $1.1 tn Founders are ex- Flipkart with deep experience in mobile, technology and domain Mining Personal Data For Right Savings Instruments AI Maturity Level 2 Leveraging Mobile to mine small data (context of spend) and using machine learning to suggest right saving instruments to grow money
  • 7. 7 Extreme Personalisation Predictive Business AI will enable new experiences Big Data Small Data Dark Data
  • 8. 8 India could see rapid Adoption of AI Retail Fin-tech Cyber security Healthcare Logistics Leading AI practitioners (Microsoft, Google, Amazon) have done a good job in training good talent at lower cost points Indian businesses operate on lower cost structures, making AI impact more meaningful for them, helping in faster adoption Large adoption of mobile workflows, create more data, and fewer regulations, allowing startups to exploit data growth Data Adoption Talent
  • 9. Confidential: Please do not share without explicit permission9 Core AI Building Blocks Heavy R&D Spend to solve core problems, ex. NLP, Image recognition, Deep Learning, Speech recognition, Emotions Rise of Applied AI Startups that leverage core AI frameworks to create business value New Category Leaders Mature Applied AI, with new leaders and consolidation by incumbents/laggards *R&D by large Companies pi Ventures Business Value 1990 2016 2020 We are here Inflection Point *Source : Bootstrap Labs Now is the Time to Invest in Applied AI Enterprise Value
  • 10. 10 In 1600’s India’s share of global GDP was 25%