Artificial intelligence basic presentation

knowledge vs intelligence vs wisdom?
ಜ್ಞಾನ vs ಬುದ್ಧಿವಂತಿಕೆ vs ವಿವೇಕ

W h a t d o w e l e a r n f r o m p a s t ?

All answer resides
in our Past Glory

Source- https://www.snopes.com/fact-check/a-spanish-mystery/

First Computers
The first substantial computer was the giant ENIAC
machine by John W. Mauchly and J. Presper Eckert at the
University of Pennsylvania. ENIAC (Electrical Numerical
Integrator and Calculator) used a word of 10 decimal digits
instead of binary ones like previous automated
calculators/computers.

Artificial Intelligence
(AI)
M3

Contents 9 Hours
1. Concept of AI
2. Meaning of AI
3. History of AI
4. Levels of AI
5. Types of AI
6. Applications of AI in Agriculture, Health, Business
(Emerging market), Education,
7. AI tools and platforms (eg: scratch/object tracking).

Concept of AI, Artificial
Intelligence
is composed
of 2 words
Artificial
and
Intelligence

Artificial defines "man-made," and
intelligence defines "thinking power", or
“the ability to learn and solve problems”
hence Artificial Intelligence
means "a man-made thinking power."
1956,The phrase artificial intelligence is coined at the "Dartmouth
Summer Research Project on Artificial Intelligence." Led by John
McCarthy, the conference, which defined the scope and goals of
AI, is widely considered to be the birth of artificial intelligence as
we know it today.

Meaning
So, We can define Artificial
Intelligence (AI) as the branch of
computer science by which we can
create intelligent machines which can
behave like a human, think like
humans, and able to make decisions.

ನಮಗೆ AI ಏಕೆ ಬೇಕಪ್ಪ?
Artificial intelligence is drastically important to our
future because AI forms the very foundation of
computer learning.
Through AI, computers have the ability to harness
massive amounts of data and use their learned
intelligence to make optimal decisions and discoveries
in fractions of the time that it would take humans.
AI , is becoming responsible for everything from
medical breakthroughs in cancer research to cutting-
edge climate change research.

• To create expert systems that exhibit intelligent
behavior with the capability to learn,
demonstrate, explain and advice its users.
• Helping machines find solutions to complex
problems like humans do and applying them as
algorithms in a computer-friendly manner.
Need

G o a l s o f A I
1. Replicate human intelligence
2. Solve Knowledge-intensive tasks
3. An intelligent connection of perception and action
4. Building a machine which can perform tasks that requires human
intelligence such as:
✓ Proving a theorem
✓ Playing chess
✓ Plan some surgical operation
✓ Driving a car in traffic
5. Creating some system which can exhibit intelligent behavior, learn
new things by itself, demonstrate, explain, and can advise to its user.

12 jobs that robots will replace in the future

1. Customer service executives
2. Bookkeeping and data entry
3. Receptionists
4. Proofreading
5. Manufacturing and pharmaceutical work
6. Retail services
7. Courier services
8. Doctors
9. Soldiers
10. Taxi and bus drivers
11. Market research analysts
12. Security guards
Source- https://www.saviom.com/blog/12-jobs-that-robots-ai-will-
replace-in-the-future-and-12-that-wont/

12 jobs that AI can’t replace
1. Human resource managers
2. Writers
3. Lawyers
4. Chief executives
5. Scientists
6. Clergyman
7. Psychiatrists
8. Event planners
9. Graphic designers
10. Public relations managers
11. Software developers
12. Project managers
• Source- https://www.saviom.com/blog/12-jobs-that-robots-ai-will-replace-in-the-future-and-12-that-wont/

ನೀವು ಹಾಗೆ ಯೋಚಿಸುತ್ತೀರಾ?

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Stage 1- Rule Bases System
Stage 2- Context-awareness and Retention
Stage 3- Domain-specific aptitude
Stage 4- Reasoning systems Stage

• Stage 1- Rule Bases System
• In this stage, AI surrounds us in everything from Robot
Process Automation used in business to autopilots used
in aircraft.
• Stage 2- Context-awareness and Retention
• The machines based on algorithms are trained on the best
human knowledge and experience with knowledge based
on specific domains. The existing knowledge base can be
updated once new queries and solutions arise. The most
common application to be Robo-advisors or chatbots
which can be used in a forward customer inquiry that can
help human in everything.

Stage 3- Domain-specific aptitude
In this stage, the advanced systems can develop mastery in
particular domains. Due to the capability to store and
process a wide volume of information to make decisions the
capabilities of these machines can be more than humans.
• Cancer diagnosis is one of the applications and
• Google Deepmind's system that defeated 18 times world go
champion Lee Sadol proved the domain-specific expertise.
Stage 4- Reasoning systems
This machine algorithm has a concept of intellect, intentions,
knowledge, and their own logic. They have the capacity to
reason, interact and, deal with other machines and humans
too. Such algorithms will be in the commercial arena in some
years.

• Stage 5- Artificial General Intelligence
• This is the main objective of many scientists working in the field of AI- to
develop a machine with intelligence like humans. They are not in application
to date but not many years left to discover this avenue. This is the stage
represented in many sci-fiction movies that machines are leading
humans in intelligence.
• Stage 6- Artificial Super Intelligence(ASI)
• This stage is one notch of the Artificial General Intelligence, the algorithms
will be capable of defeating smartest of the humans in all the domains. This
stage can be the real solution to the problems that are still complex for the
human mind like poverty, hunger, and climate change. This will be the
stage where machines made by humans will outsmart humans too.
• Stage 7- Singularity and excellency
• The development path led by ASI will lead us to the point in time where the
capabilities of humans will see the tremendous extension. With the help
of this ASI, technology humans would be able to connect the minds
of each other and be like the human internet.

Alan Turing
AI is not a new concept, the origin of AI trace back to almost a century
ago in the time of the 2nd
World War when Alan Turing, came up with
an idea of machines able to think. Alan Turing was one of the first
scientists to work in the field of Artificial Intelligence and smart
algorithms.

Watson and the Jeopardy! Challenge

• Artificial intelligence or AI simulates human intellect to machines. AI-enabled machines are
capable of performing specific tasks better than humans and mimic human actions. There
are four types of AI:
1. Reactive machines: This is the most superficial level of AI. Reactive machines can do basic
operations. They cannot form memories or use past experiences to make decisions.
IBM’s Deep Blue is the perfect example of this type of machine. This AI beat international
grandmaster Garry Kasparov in 1997.
2. Limited memory: This AI type can store existing data and create better output by using
the data. For example, Tesla’s self-driving cars observe the speed of vehicles and direction
and act accordingly.
3. Theory of mind: Theory of mind can connect with human thoughts and interpret them
better. The AI can understand people and have thoughts and emotions of its own. These
AI machines are still hypothetical, but researchers are making many efforts to develop
such AI machines.
4. Self-aware AI: This type of AI is a thing of the future. A self-aware AI will have an
independent intelligence, and it will make its own decisions. These machines will be
smarter than the human mind.

• Narrow AI is a type of AI which is able to perform a
dedicated task with intelligence. The most common and
currently available AI is Narrow AI in the world of Artificial
Intelligence
• General AI is a type of intelligence that could perform any
intellectual task with efficiency like a human
• Super AI is a level of Intelligence of Systems at which
machines could surpass human intelligence, and can
perform any task better than a human with cognitive
properties. This refers to aspects like general wisdom,
problem solving and creativity. It is an outcome of general
AI.

HISTORY OF ARTIFICIAL INTELLIGENCE

Sage Valmiki
writes the
thoughts of
Brahma when he
saw Kumbhakarna
:

Artificial Intelligence in Ramayana

ML
Machine Learning is a subset of
Artificial Intelligence that uses
statistical learning algorithms to build
systems that have the ability to
automatically learn and
improve from experiences without
being explicitly programmed.

Deep learning takes artificial intelligence a step further, by mimicking how the human brain
works through the use of artificial neural networks. In an artificial neural network, each neuron
is charged with providing a binary (yes/no) response to basic questions about a piece of data. By
layering thousands (or millions) of these artificial neural networks, a Deep Learning machine is
able to generate reliable outputs (recommendations or interactions) without changing the
underlying coding.

Facts aren’t Artificial
• We know that technology is evolving day by day and AI is
reaching new heights. Even the research is growing
constantly and continues to grow. In the last five years,
AI research has grown by 12.9% annually worldwide,
hence it can be seen that the rate at which AI is growing
is truly commendable.
• It is predicted that in the coming 4-5 years, China will
become the biggest global source of Artificial Intelligence
and will take over the United States. The not so shocking
thing is that Europe will be on the number one spot.

Applications of AI in Agriculture, Health,
Business (Emerging market), Education,

Top 10 Agritech Startups Empowering Indian
Farmers

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Artificial intelligence basic presentation

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