This ppt will help viewers to learn about cognitive computing, its hardware and software technologies.

1. COGNITIVE COMPUTING
Submitted to :
Ms. Prachi Gupta
Ms.Neha Gupta
Submitted By :
Anmol Nijhawan
Section B
1308210017

2. Content
• What do we mean by term Cognitive?
• What is cognitive Computing?
• Brain inspired architecture
• Cognitive Computing is combination of principles of Neuroscience
,Nanotechnology, and Supercomputing
• Neuroscience
• Nanotechnology
• Super Computing
• Event driven non von Neumann architecture
• Cognitive Computing Power Efficient architecture
• Technologies integrated in cognitive computing
• IBMWatson

3. What do we mean by term Cognitive?
The Cognitive is the mental action to
learning and acquiring through
thought, experience, and the senses .

4. What Is Cognitive Computing?
• Cognitive computing involves the systems that can
analyse , memorise ,processing to mimic the way the
human brain works.
• The basic idea behind this type of computing is that to
develop the computer systems (include hardware and
software) who interacts with human like humans.
• These computer can recognize ,understand ,analyze
and take out the best possible result as or near about
the human brain.

5. Brain Inspired Architecture
• Cognitive computing is the synthesis of
software and silicon inspired by brain.
• The Cognitive computing chip, designed
to emulate the neurons and synapses
(connections) in the human brain.
• Brain-inspired architecture consists of a
network of 4096 neurosynaptic cores
include neurons and synapse.
• Individual cores can fail and yet, like the
brain, the architecture can still function.

6. Cognitive Computing is combination of principles
of Neuroscience ,Nanotechnology,
and Supercomputing

7. Neuroscience
•Neuroscience deals with the study mind , study of the
neural systems.
•The architecture of the cognitive computing devices is
same as a architecture of brain.
•The devices based on this architecture consist of the
electronic neurons and synapse and are called
Neurosynaptic chips.
•There inner network is like brain network.

8. Mammalian brain architecture
Scientists are installing processors and network between the
processors as like this brain network to achieve
the human brain capabilities.

9. Nanotechnology
• As we know nanotechnology is science in
which material size of 10 to the power -9
meter.
• We need to embed large number of
processors and synapse to build the
system like the human brain
• So to embed the large number of
processor over the chips is done with the
help of the nanotechnology.
• Built on 45 nanometer silicon/metal oxide
semiconductor platform, chips have 5.4
billion transistors 256 million synapse.
Cognitive chips made by IBM
Called as IBM's
"Neurosynaptic" using
nanotechnology

10. Super Computing
• Cognitive Computing develops the brain like computers and as
our brain have high performance capacity .
• So to achieve such high performance supercomputing
algorithm and hardware needs in cognitive computing.
• As same as supercomputers we calculate the performance of
the cognitive computing devices FLOPS(Floating point
operations per seconds).
In this way Neuroscience , Nanotechnology and Supercomputing
collectively form a cognitive computing.

11. Event Driven nonVon Neumann Architecture
• Cognitive Computing machine operate -without a clock-
in an event-driven fashion.
• This new neurosynaptic chip is event-driven and operates
only when it needs to, resulting in a cooler operating
environment and lower energy use.
• NonVon Neumann architecture is that it embed the
memory with processing unit which is different

12. The chip is especially designed for low power consumption,
which can clearly be seen in this thermal image that shows
the cool cognitive chip is in blue color and heat up traditional
chip in red.

13. Cognitive computing brings
Power Efficient architecture
• This new architecture represents a critical shift away
form today's traditional von Neumann computers, to
extremely power-efficient architecture.
• It integrates memory with processors, and it is
fundamentally massively parallel and distributed as
well as event-driven, so it begins to rival the brain's
function, power and space.“
• Goal is to build a chip system with 10 billion neurons
and 100 trillion synapses that consumes just one
kilowatt-hour of electricity .

14. Technologies integrated in Cognitive computing
to mimic capabilities of Human brain?
•ParallelComputing
•Data Mining
•Machine Learning
•Natural Language Processing

15. Parallel Computing
• Human brain do not works in the sequential format i.e. it doesn't
performs the thing one by one but it do all the things in parallely.
• So using parallel computing we allow the cognitive machines
adapts the parallel architecture and parallel algorithms.
• To cognitive computing chips have 256 million neurons, an array of
256 by 256 (or a total of 65536) synapses(connection in brain).
• With this cognitive computing chips have gained the capability to
work like the human brains.

16. Data Mining in Cognitive Computing
• Cognitive Computing provides the data analytic capabilities.
• We are generating 2.5 quintillion bytes of data every day.
• Today we have very large amount of data which is in terabytes,
petabyte and in future we will have it in zeta or yottabyte which
is noisy and unstructured data.
• So to get the best possible results or knowledge, data mining is
introduced in cognitive computing .

17. Machine Learning
• Machine learning is a subfield of computer science that evolved from
the study of pattern recognition and computational learning
theory in artificial intelligence.
• Cognitive systems with this learn with experience , its input and
output data.
• It is the field of study that gives computers the ability to learn without
being explicitly programmed.

18. Natural Language Processing
• Processing of the human generated language by computer.
• Natural language processing (NLP) is a field of computer
science, artificial intelligence, and computational linguistics concerned
with the interactions between computers and human (natural)
languages.
• These cognitive system take the input in the human understandable
language process it with NLP algorithms and give the results in human
understandable language.
• To get data from the internet which have large amount of data in
natural language cognitive chips use NLP .

19. IBM Watson
• IBMWatson is cognitive computing machine
made by the IBM.
• It is a question answer based machine.
• Uses natural language processing to
understand grammar and context.
• Evaluates all possible meanings and
determines what is being asked.
• And than answer based on supporting
evidence and quality of information found.

21. Conclusion
• Cognitive Computing is very important for the future with the lots of data.
• Each and every professional on this planet will become master of his field
with the cognitive assistant.
• Helps to make a correct decision by parse lots of data.
• These type of machines give data smartly in less time.
• Provides enterprise intelligent systems.
• Helps to build a smarter planet.

22. Bibliography
• http://www.research.ibm.com/cognitive-computing/#fbid=zid-
3nqoVLV
• http://www.research.ibm.com/cognitive-
computing/brainpower/#different_from_a_standard_chip_noscript
• http://www.ibm.com/smarterplanet/us/en/ibmwatson/
• http://venturebeat.com/2011/08/17/ibm-cognitive-computing-chips/
• https://en.wikipedia.org/wiki/Machine_learning
• http://www.popsci.com/technology/article/2011-08/first-generation-
cognitive-chips-based-brain-architecture-will-revolutionize-
computing-ibm-says

23. Thank You