This document discusses cognitive computing and artificial intelligence. It defines cognitive computing as systems that learn from experience and instructions to mimic human cognition by synthesizing information, finding patterns rather than exact answers, and interacting naturally with humans. Specific examples discussed are IBM's Watson, which uses natural language processing and machine learning to answer questions and make complex decisions from vast amounts of data. The document also discusses concerns about the future risks of artificial intelligence, such as superintelligent systems that humans may not be able to control and could ultimately replace humans.

1. COGNITIVE COMPUTING
And the Future of Artificial Intelligence

2. COGNITIVE COMPUTING
• Mimicking functioning of Human Brain and handling Human kind of
problems.
• Synthesis of not just information sources but also of influences, contexts, and
insights.
• Answer that is “best” rather than “right”.
• Finding patterns to form the answer rather than looking for the answer itself.
• Learns by experience and instructions given.
• Redefines the relationship between the people and their increasingly
pervasive digital environment.

3. • Cognitive computing systems learn and interact naturally with people to
extend what either humans or machine could do on their own. They help
human experts make better decisions by penetrating the complexity of Big
Data.
• It will forever change the way people interact with computing systems to
help people extend their expertise across any domain of knowledge and
make complex decisions involving extraordinary volumes of fast moving Big
Data.
• Cognitive systems can quickly identify new patterns and insights. Over time,
they will simulate even more closely how the brain actually works.

4. • It is a category of technologies that
uses natural language
processing and machine learning to
enable people and machines to
interact more naturally to extend and
magnify human expertise and
cognition.
• Cognitive Systems must be:
• Adaptive
• Interactive
• Iterative and Stateful
• Contextual

6. COGNITIVE ENVIRONMENT
• A cognitive environment is an infrastructure inhabited by the society of cogs
and the devices that let them behave as one shared integrated resource,
enabling “human-computer collaboration at the speed of thought.”

7. • Watson is an artificially intelligent
computer system capable of
answering questions posed in
natural language, developed in
IBM's DeepQA project.
• Cognitive-based systems, such
as IBM Watson, are able to build
knowledge and learn, understand
natural language, and reason and
interact more naturally with
human beings than traditional
systems.
IBM WATSON

8. • Watson is build to mirror the same learning process that we have – through
the power of cognition.
• What drives this process is a common cognitive framework that humans use
to inform their decisions: Observe, Interpret, Evaluate and Decide.
• Unlike other computing systems, Watson takes in data from all sorts of
sources. Watson is not bound by volume or memory.
• Watson is discovering and offering answers and patterns we hadn’t known
existed, faster than any person or group of people ever could.

9. • Watson uses this same cognitive framework to achieve mastery over a given
subject and develop expertise.
• More than 100 different techniques are used to analyze natural language,
identify sources, find and generate hypotheses, find and score evidence,
and merge and rank hypotheses.
• Watson's main innovation was not in the creation of a new algorithm for its
operations but rather its ability to quickly execute hundreds of proven
language analysis algorithms simultaneously to find the correct answer.

11. ARTIFICIAL INTELLIGENCE
• The central goals AI research include
reasoning, knowledge, planning,
learning, natural language
processing (communication), perce
ption and the ability to move and
manipulate objects.
• As a minimum, an AI system must be
able to reproduce aspects of human
intelligence.
• This raises the issue of how ethically
the machine should behave towards
both humans and other AI agents.

12. FUTURE OF ARTIFICIAL INTELLIGENCE
• Humans should not assume machines or robots would treat us favorably,
because there is no prior reason to believe that they would be sympathetic
to our system of morality.
• Hyper-intelligent software may not necessarily decide to support the
continued existence of mankind, and would be extremely difficult to stop.
• Physicist Stephen Hawking, Microsoft founder Bill Gates and SpaceX founder
Elon Musk have expressed concerns about the possibility that AI could
evolve to the point that humans could not control it, with Hawking theorizing
that this could "spell the end of the human race".

13. • Specialized AI applications,
robotics and other forms of
automation will ultimately result in
significant unemployment as
machines begin to match and
exceed the capability of workers to
perform most routine and repetitive
jobs.
• A super intelligence, hyper
intelligence, or superhuman
intelligence is a hypothetical agent
that would possess intelligence far
surpassing that of the brightest and
most gifted human mind.

14. • If research into Strong AI produced sufficiently intelligent software, it might
be able to reprogram and improve itself. The improved software would be
even better at improving itself, leading to recursive self-improvement.
• The new intelligence could thus increase exponentially and dramatically
surpass humans. This will give birth to Technological Singularity.
• Technological Singularity will be the beginning of the end of mankind.