This document discusses cognitive automation and artificial intelligence. It begins with definitions of cognition and automation. It then provides a brief history of automation and examples of current automation technologies. It discusses different types of artificial intelligence from narrow to general to super intelligence. It also discusses machine learning and deep learning approaches. The document outlines various applications of cognitive automation and artificial intelligence, as well as challenges. It emphasizes that cognitive automation will change but not eliminate jobs for humans. The presentation aims to inspire students to help build the future of cognitive automation and artificial intelligence.

1. Cognitive Automation
Build your Artificial Intelligence CoWorker
Tamilselvan Subramanian Program Lead AI @ Wipro
Samson Saju Lead AI Expert @ Wipro
Date : 15-Dec-2015
Venue : Christ University, Bangalore

2. Human development & Tools

3. What is Cognition ?
The mental action or process of acquiring knowledge
and understanding through
• thought
• experience
• senses
What is Automation ?
BMW Spartanburg robotic welding line
The use or introduction of automatic equipment
in a manufacturing or other process or facility.

4. History of Automation
In 1913, Ford Motor Company, which introduced electric motors to
the then-well-known technique of chain or sequential production
The first NC (Numerical Control) machines were built in the 1940s
and 1950s, based on existing tools that were modified with motors
that moved the controls to follow points fed into the system on
punched tape. These early servomechanisms were rapidly
augmented with analog and digital computers, creating the modern
CNC machine tools that have revolutionized the machining processes.
Amazon’s Kiva is a mobile material handling robot . The larger
model can carry pallets and loads as heavy as 1360 Kgs. The
mobile bots are battery-powered and need to be recharged
every hour for five minutes

5. Cognitive Automation
Automate the entire processes or
Workflows using sense and synthesize vast amounts
of information also learning and adapting as they go !
Artificial Narrow
Intelligence
Artificial General
Intelligence
Artificial Super
Intelligence
Cognition
Specializes in one narrow
task like coming up with
driving routes or playing
chess
At least as intellectually
capable as a human,
across the board
way smarter than any
human, across the
board

6. Bloom's Taxonomy
Cognition Map
What are the health benefits of eating apples?
Remember
Compare the health benefits of eating apples
vs. oranges
Understand
Would apples prevent scurvy, a disease caused
by a deficiency in vitamin C?
Apply
List four ways of serving foods made with apples and explain which
ones have the highest health benefits. Provide references to support
your statements
Analyze
Convert an "unhealthy"
recipe for apple pie to a
"healthy" recipe by replacing
your choice of ingredients.
Explain the health benefits
of using the ingredients
you chose vs. the original ones
Create
Which kinds of apples
are best for baking a
pie, and why?
Evaluate

7. Why Cognitive Computing Now?
Google Brain
Google Auto
HDFS / GFS
Infra Scalability
Curated Free Knowledge
Geff Hinton -
Deep Learning
GPU Computing
Neuromorphic
Engineering

8. Inspiration
FLY
THINK
Goal Technology
Cognitive Automation - Inspiration

9. Road to Human Brain by Computation Power
Source: Ray Kurzweil

10. Neuromorphic Chip -New Processor Design
Source: Ray Kurzweil
Microprocessors configured more
like brains than traditional chips
could soon make computers far
more astute about what’s going on
around them
It is a complement to the conventional Chip design not the replacement !
Intel Six Core i7 contains ~ 1.3 Billion Transistors ( 130 Crores)
IBM TrueNorth contains 5.4 Billion Transistors (540 Crores)

11. Levels of Cognitive Automation
the computer offers no assistance:
humans must take all decisions
and actions.
the computer offers a complete set
of decision/action alternatives
narrows the selection down to a few
suggests one alternative
executes that suggestion if the
human approves
allows the human a restricted time
to veto before automatic execution
executes automatically, then
necessarily informs the human informs the human only if asked
informs the human only if it, the
computer, decides
The computer decides everything,
acts autonomously, ignoring the
human
Parasuraman et al
Text Box Vs
Combo Box vs
Auto Suggestion
Pick from Cache

12. What are some of the problems to be solved ?
Natural Language
Processing
Automatic Speech
Recognition
Visual Recognition
Automatic summarization
Co-reference resolution
Sentiment analysis
Semantic Understanding
Named Entity Recognition
Natural Language Generation
Relationship Extraction
Part of Speech Tagging
Question answering
Optical character recognition
Image Tagging
Image Detection
Image Segmentation
Image Recognition

13. All the problems discussed requires Learning. A computer to should
able learn from data not by IF-ELSE code.
Machine Learning !

14. No Programming after the installation!
https://youtu.be/KpqaBKyZGeE

15. Machine Learning
Machine Learning boils down to learning a mapping from an input space to an output space in an
automated manner, using available data.

16. Machine Learning types
Supervised learning: The computer is presented with example inputs and their desired outputs,
given by a "teacher", and the goal is to learn a general rule that maps inputs to outputs.
Unsupervised learning: No labels are given to the learning algorithm, leaving it on its own to find
structure in its input. Unsupervised learning can be a goal in itself (discovering hidden patterns in
data) or a means towards an end.
Reinforcement learning: A computer program interacts with a dynamic environment in which it
must perform a certain goal (such as driving a vehicle), without a teacher explicitly telling it
whether it has come close to its goal. Another example is learning to play a game by playing against
an opponent.

17. Machine Learning Example
Spam filtering
Supervised Learning
* Handcrafted Feature Training
Customer Segmentation
Unsupervised Learning
* Feature Learning

18. Deep Learning
Deep Learning is about learning multiple levels of representation and abstraction that help to make
sense of data such as images, sound, and text.
One of the promises of deep learning is replacing handcrafted features with efficient algorithms
for unsupervised or semi-supervised feature learning and hierarchical feature extraction
Types of Architecture
Recurrent neural networks (Mostly used in language modeling )
Convolutional deep neural networks (Mostly used in Vision/ Speech recognition )

19. Thanks to Deep Learning Gurus..

20. Cognitive Automation - Types
Human
Automate
Everything
Automate
As much
as Possible
Automate
Boring and
dangerous
job
Automate
Human
cannot to
that job

21. Cognitive Automation in IT Companies.
• India to remain fastest growing IT market in 2016 and to reach 85.3$ Billion in 2019,
says Gartner.
• India has around 30 lakhs direct IT employees and 60 lakhs indirect employees today.
EmployeeOrganization
Job
+ Unique & No dull Job
- Job Threat for less skilled
+ Less Cost, High productivity
- Difficult to lock in multi vendor model,
Risk of too much Cruise Control
+ Quick resolution, Avoid repeating Mistakes
- Unintended consequences of Automation

22. What are we doing?
We are developing an Artificial Intelligent Platform, that is the feature of Wipro
and feature of any Organization who is looking to Automate the job.

24. Evolution of our AI Journey
Knowledge virtualization,
Machine Learning, Neural nets,
bots
Semantic, Ontology
Framework for understanding and
giving meaning to data.
Natural Language Processing
Text mining for topic modelling
intelligent clustering and
classification.
Data Science
Algorithm based
Predictive Analytics
Blended reality
Frameworks for experience designs in
immersive environments
Context and event based
architecturesSingle View of Customer
Failure Prediction and
Service optimization
Continuous
Integration
Conversational interface for
enterprise application
Cognitive Process
Automation
Futuristic Customer
Onboarding Experience
2010
2014
2012

25. Categories of AI Application
Data Science & Predictive Analytics
Extracting information from existing multi-structured data using
algorithms in order to discover patterns and predict future outcomes and
trends.
Intelligent Virtual Agents
Consumer oriented to improve usability and experience for performing
tasks on mobile devices , capabilities of speech recognition , NL
understanding
Robotic Process Automation
Robotic automation is driven by a set of instructions or logic describing
how to process work. These instructions may be user-defined, or
machine-learnt
Visual Computing & Human Computer Interface
Systems or applications that simplify HCI based on Sense & Response,
Multi-modal interactions and experience management
Knowledge Processing Systems
System with curated knowledge using artificial intelligence techniques
like Text processing, semantic and knowledge engineering techniques.
Autonomous Robots & Drones
Robotics includes electro mechanics , computer vision and cognitive
capabilities. Industrial robotics and service robotics are 2 broad spaces.
Low HighComplexity

26. In Media
PAC Group –
Wipro’s key offerings to solve these problems include:
 Hyper-automation – with its HOLMES platform Wipro indicates it aims to embed a
higher level of automation in traditional business processes – and especially within its
BPO transactions – where machine learning algorithms would be a key component of
the platform…” by Klaus Holzhauser
Everest Group –
“Outsourcing advisory firm Everest Group’s CEO Peter Bendor-Samuel believes the
effort made by Wipro through Holmes is a recognition of the profound changes
sweeping the IT services industry. They have recognised not only the customer
impact of implementing automation in their workflow, but also the impact on the
service provider, Samuel said in his blog Sherpas in Blue Shirts.”
TBRI
“While honing its integrated sales and delivery model, Wipro
continues to work toward building credibility as a higher-
value services provider, earning three expansive digital
transformation contracts in the United States and U.K. that
suggest favorable client reception toward Wipro’s portfolio
(including Holmes cognitive computing) and the company’s
ability to deliver on promises of measurable results” – Amy
McLaughlin
HfS research –
“Wipro’s new cognitive platform, built with open source tools, also has features of
New York-based IPsoft’s humanoid programme Amelia. All these platforms claim to
improve productivity by allowing IT vendors to deploy fewer engineers for repetitive
manual tasks.” – Tom Reuner
Gartner-
Wipro HOLMES was featured in the slides of
prominent Gartner Analyst Gilbert Van Der
Heiden
His key note session topic was – “The Journey to
Digital Door”
Initiated IDC Tech
Spot Light for
HOLMES
The Outsource Blog
Wipro Infosys turn to AI, design thinking in
subdued IT Market – Rahul Jain

27. Recursive Cortical Network (RCN)
Watch these space for more
Samsung, Wipro Follow Jeff Bezos in Funding AI Startup Vicarious
http://www.bloomberg.com/news/articles/2015-08-18/samsung-wipro-follow-jeff-bezos-in-funding-ai-startup-vicarious
Vicarious aims to replicate the human brain artificially

28. Demo

29. Challenges / Risk in Cognitive
Automation
• General Incremental Learning
• Automatic Goal Setting , braking into multiple Goals
• Semantic Understanding world Knowledge (Google word vector)
• Collaborative decision Making from Unexpected situation (Prof.Vijaykumar from Pittsburgh university)
• Absolutely fault tolerance.
• Retaining the Human skill for basic Operations
• Time to handoff to Human

30. Failed handoff – Automation Disaster??
…After talking to the Investigation team,
The MIT Professor Mindell said that the
crash illustrated a "failed handoff," with
insufficient warning, from the plane's
autopilot to the human pilots.
Air France Flight 447 (AF447/AFR447) was
a scheduled passenger flight from
Rio de Janeiro, Brazil to Paris, France,
which crashed on 1 June 2009. The Airbus A330,
operated by Air France, entered an aerodynamic
stall from which it did not recover and crashed
into the Atlantic Ocean at 02:14 UTC, killing all
228 passengers, aircrew and cabin crew aboard
the aircraft.
Wreckage from Atlantic Ocean

31. Knock.. Knock! Technological Singularity
The technological singularity is a hypothetical event related to the advent of genuine artificial
general intelligence. Such a computer, computer network, or robot would theoretically be
capable of recursive self-improvement (redesigning itself), or of designing and building
computers or robots better than itself on its own.
• A robot may not harm a human being, or, through
inaction, allow a human being to come to harm.
• A robot must obey the orders given to it by human
beings except where such orders would conflict
with the First Law.
• A robot must protect its own existence, as long as
such protection does not conflict with the First or
Second Laws.
Isaac Asimov’s Law of Robotics

32. Leaders view on AI
AI could spell the end of the human race
-Stephan Hawking,
I am in the camp that is concerned about
super intelligence -Bill Gates
.. our biggest existential threat is AI
- Elon Musk
artificial intelligence will doom mankind
- Clive Sinclair
All these Great visionaries are
not against AI, but they warn
we should cautious while
designing an AI system.
They are warning none other than you !
The Goal is Friendly AI !

33. So What Changed Two days ago?
.. our biggest existential threat is AI
- Elon Musk
Geoff Hinton
Research Director
OpenAI
Founded: December 11, 2015

34. What does Cognitive Automation mean to you?
As a Computer Science students..
• You will be mostly offered to solve the challenging problems, Not a repetitive boring job.
• You will be part of Training the Machines and validating results
• AI Machine will offer the collective results and ask you to take decision in the workflow.
• You will still be able to solve the simple problems in case of machine failure.
• You will be keep upgrading your skills that machine cannot do at the moment.
• Your role will be very critical than before.
• You will still be coding for a while to make a machine that writes a code for you 

35. Take Rest from 24/7 jobs !
Image Credit :www.frolicandwhimsy.com

36. Where would you begin?
Read Books / Blogs / Articles /
Talk to your Professor
Take a Courses on
AI / Machine learning /
Cognition Science /
Deep learning
Get your hand dirt with all modern
Machine / Deep learning libraries
Share the code with other Contributors
You trust.
Demonstrate to the world !
Work
Prepare
Inspire

37. This is the place to build your future !
Most innovative / Cognitive solutions that are helping the
human kind today are from the academic institutions like
yours !
Every tomorrow has two handles. We can take hold of it with the
handle of anxiety or the handle of confidence.
What are you holding it now ?
Think of a Project that will drive your /our Future. Bring it to us !

38. Every animal on earth is constrained by its energy budget; the
calories obtained from food will stretch only so far. And for
most human beings, most of the time, these calories are
burned not at the gym, but invisibly, in powering the heart, the
digestive system and especially the brain, in the silent work of
moving molecules around within and among its 100 billion
cells. A human body at rest devotes roughly one-fifth of its
energy to the brain, regardless of whether it is thinking
anything useful, or even thinking at all. Thus, the
unprecedented increase in brain size that hominids embarked
on around 1.8 million years ago had to be paid for with added
calories either taken in or diverted from some other function in
the body
Read more: http://www.smithsonianmag.com/science-nature/why-fire-makes-us-human-
72989884/#O6gkWrlVl2SISfkk.99
Give the gift of Smithsonian magazine for only $12! http://bit.ly/1cGUiGv
Follow us: @SmithsonianMag on Twitter
Fire for your thought !
Neuromorphic Computing – Analog Process
– Low power utilization

39. Questions ?
Feel free to get in touch
Cognitive Automation Discussion Group
https://www.linkedin.com/groups/8456078
Email : tamilselvan.subramanian@wi***.com
: tamilselvan@gmail.com
LinkedIn : https://in.linkedin.com/in/tsubraman
Tamilselvan Subramanian