The document provides an overview of machine learning and artificial intelligence. It defines machine learning as a technique used to develop artificial intelligence by having computer programs learn from examples without being explicitly programmed. The key elements of machine learning/AI are data, algorithms, and computations. Machine learning is used across many industries and in products/services like healthcare applications that can detect diseases from medical images. Machine learning tools are being democratized through APIs to expand their use. AI will be applied to more areas as machines learn and adapt based on data.

1. Understanding Intelligence:
Machine Learning & Artificial
Intelligence

2. Machine learning is
a core, transformative
way by which we’re
rethinking how we’re
doing everything.
– Sundar Pichai
“
”

3. AI and Machine Learning
A.I. is the science of
making things smart
Machine learning
is a technique used
to develop A.I.

4. A branch of artificial intelligence
A way to solve problems without
explicitly codifying the solution
A way to build systems that
improve themselves over time
Machine learning is...

5. A different way of doing things
Write a computer program
to learn from examples
try to classify some emails;
change self to reduce errors;
repeat;
Write a computer program
with explicit rules to follow
if email contains “You won a Cruise”
then mark is-spam;
if email contains …
if email contains …

6. Machine learning is
learning from examples and
experience

7. data algorithmscomputations
Key Elements of ML/AI

8. Deep Neural Networks Step 1: training

9. Deep Neural Networks Step 2: testing

11. ML in Products

12. Healthy Diseased
Hemorrhages
Proliferative DRSevere DRModerate DRMild DRNo DR
54321

13. INDIA
Shortage of 127,000 eye doctors
45% of patients suffer vision loss before diagnosis

14. 0.95
Algorithm
0.91Ophthalmologist
(median)
F-score
The study by Gulshan and colleagues truly
represents the brave new world in medicine.
– Dr. Andrew Beam, Dr. Isaac Kohane
Harvard Medical School
“
”
[...] It actually lives up to the hype.
– Dr. Luke Oakden-Rayner
University of Adelaide
“
”
JAMA | Original Investigation | INNOVATIONS IN HEALTHCARE DELIVERY
Development and Validation of a Deep Learning
Algorithm for Detection of Diabetic Retinopathy in
Retinal Fundus Photographs
The Journal of the
American Medical Association
n=9,963 images
AUC 99.1% [98.8, 99.3
Sensitivity,%
1- Specificity, %
100
80
60
40
20
0
0 20 40 60 80 100

15. ML for everyone

16. TensorFlow
released in Nov. 2015
#1 Repository
for machine learning
on GitHub
Sharing ML tools with people around the world

17. APIsAI

18. Cloud
Vision API
Cloud
Translate API
Cloud
Natural Language API
Cloud
Speech API
Democratization of AI -- How?
Partner’s AI
Capability
Corporate Secret
AI Capability

19. Myriads of
Applications
will go from
Transact
To
Adapt
Democratization of AI will happen through APIs
Partner’s AI
Capability
Cloud
Vision API
Cloud
Translate API
Cloud
Natural Language API
Cloud
Speech API
Corporate Secret
AI Capability

20. Use of AI
In reality, every application
will become a learning application

21. Manufacturing
● Predictive maintenance
● Condition monitoring
● Warranty reserve estimation
● Demand forecasting
● Process optimisation
Travel & hospitality
● Aircraft scheduling Dynamic pricing
● Consumer interaction analysis
● Customer complaint resolution
● Traffic patterns
● Congestion management
● Recommendation engines
Retail
● Predictive inventory planning
● Recommendation engines
● Upsell & cross-channel marketing
● Market segmentation & targeting
● ROI & lifetime value modelling
Financial services
● Risk analytics
● Customer segmentation
● Cross-selling and upselling
● Marketing campaign management
● Creditworthiness evaluation
● Trading desk bid management
Health & life sciences
● Real-time alerts and diagnosis
● Disease identification
● Patient triage optimisation
● Proactive health management
● Healthcare provider sentiment analysis
Energy & utilities
● Power usage analytics
● Seismic data processing
● Carbon emissions & trading
● Customer-specific pricing
● Smart grid management
● Energy demand and supply
optimisation
Wherever there are large data sets and
complex problems

22. BI + Reporting Machine Learning + AI
Machine Learning and AI thrive on predictive and prescriptive analytics
Low HighSophistication
Descriptive -> Predictive Analytics & Diagnostic ->
Prescriptive Analytics with the help of ML/AI
Descriptive
Analytics
Diagnostic
Analytics
Predictive
Analytics
Prescriptive
Analytics

23. AI for Good
● Establish best practices
● Advance public
understanding
● Open discussion of AI and
its influences on people
and society
http://www.partnershiponai.or
g/ est. September 2016

24. “AI is turning science fiction into non-fiction,
but some of its most meaningful applications
haven’t been imagined yet.”

25. Thank you