artificial intelligence

1. ARTIFICIAL INTELLIGENCE (A.I.)
Narendra Kumar
Institute of Pharmacy, Pt. Ravishankar Shukla
University, Raipur

2. CONTENTS
• INTRODUCTION
• HISTORY
• CURRENT STATUS
• GOALS
• APPLICATIONS
• ADVANTAGES
• DISADVANTAGES
• FUTURE SCOPE
• CONCLUSION

4. ARTIFICIAL INTELLIGENCE
ARTIFICIAL
INTELLIGENCE
Intelligence: “The capacity to learn and solve problems”
Artificial Intelligence: Artificial intelligence (AI) is the
simulation of human intelligence by machines.
• The ability to solve problems
• The ability to act rationally
• The ability to act like humans

5. • The artificial intelligence term was used in the year 1956, and the
concept was used from the year 1950, under the topics of problem
solving and symbolic methods.
• Artificial Intelligence is the branch of engineering & computer
science which deals with making of intelligent machines or systems
that can function intelligently and independently, especially intelligent
computer programs.
• Artificial Intelligence is the ability of a computer or a robotic
computer enabled system to process the given information and
produce outcomes in a manner similar to the attention process of
humans in learning, decision making, reasoning, self-correction and
solving problems. Artificial intelligence is becomes an essential part of
the technology industry. Research associated with artificial
intelligence is highly technical and specialized.

6. Year Milestone
1943 Neurons can do logical operations like “and”, “or” or “not”, when they
are connected as a network. This process was proved by Walter Pitts and
Warren McCulloch.
1951 First neuronal network, which solved a problem from the real world i.e.
SNARC (Stochastic Neural Analog, Reinforcement Computer) was by
Marvin Minsky.
1956 At Dartmouth college conference the term “Artificial Intelligence” was
coined.
1958 Perceptrons (neuronal networks that transmit information in one
direction) was created by the Frank Rosenblatt which is the origin for
todays AI progress.
1969 Minsky supported the symbolic representation of problems in his book -
“Perceptrons”.
Mile stones in the artificial intelligence process

7. Year Milestone
1974 -
1980
During this period, interest on AI was dropped, which is called as
“First AI Winter”.
1986 Back propagation algorithm design was developed by Georey Hinton
which is widely using in deep learning nowadays.
1987 -
1993
This phase is called as “AI winter”
1997 This year IBM Deep blue defeated the Garry Kasparov (Russian
grandmaster).
2013 Google used the British technology to perform efficient research on
photos.
2016 Google DeepMind, software AlphaGo defeated the Go Champion Lee
Sedol.
2016 Humanoid robot developed by Hong Kong based company Hanson
Robotics Sophia was activated on February 14, 2016

8. A.I. TIMELINE

9. EARLY HISTORY
OF A.I.
1950 : “CAN MACHINES
THINK??????”
1956 : THE TERM
“ARTIFICIALINTELLIGENCE”
WAS FIRST INTRODUCED.

10. • Analyse Satellite
Images to identify
which areas have the
highest poverty level
• Gate allocationfor
plane while landing
• Tickt price
determination
• Companies are
creating robots to
teach subjects
A.I. FOR GOOD AVIATION EDUCATION

11. • Solving a variety of
problems of patients,
hospitals & healthcare
industry overall.
• Using Avatars in place of
patients.
• Robots have become
very common in many
industries
• Can do repetitive
laborious tasks
• Algorithmic Trading
• Market analysis &
data mining
• Personal Finance
• Portfolio management
HEALTH CARE HEAVY INDUSTRY FINANCE

12. • To develop algorithms that human use.
• Algorithms can require enormous
computational resources and problem
goes beyond a certain size
• Knowledge Representation :
To build machine with the capability
of making working assumption and
common sense.

13. • Planning :
 In classical planning problems, the agent can
assume that it is the only system acting on the
world
 Multi-agent planning uses the cooperation and
competition of many agents to achieve the
given goal.
• Learning :
 Machine learning is the fundamental concept
of AI search.
 Unsupervised learning is the ability to find
patterns in s stream of input
 Supervised learning includes both
classification and numerical regression

14. To understand what artificial intelligence is, we need to know
how it works and what are the Subfields and components that make
machines work intelligently.
Speech Recognition
Humans can speak and listen to communicate through language; this is
the field of speech recognition. Since speech recognition is statistically
based, hence it’s called statistical learning.
Natural Language Processing
Humans can write and read the text in a language; this is the field of
NLP or natural language processing.
Working, Subfields and Components

15. Machine Vision
Humans can see with their eyes and process what they see; this is the
field of computer vision. Computer vision falls under the symbolic
way for computers to process information.
Moreover, they can recognize the surroundings around them
through their eyes which create images of that world. This field of
image processing which even though is not directly related to AI is
required for computer vision.
Robotics
Humans can understand their environment and move around
fluidly; this is the field of robotics.
Pattern Recognition
Humans can see patterns such as grouping of like objects; this is the
field of pattern recognition. Machines are even better at pattern
recognition because they can use more data and dimensions of data,
this is the field of machine learning.

16. Types of artificial intelligence:-
Artificial Intelligence is a wide-ranging concept and can be classified
into a number of ways. Based upon their caliber:-
1. Weak intelligence or Artificial narrow intelligence (ANI): This
system is designed and trained to perform a narrow task, such as facial
recognition, driving a car, playing chess, traffic signaling.
E.g.: Apple SIRI virtual personal assistance, tagging in social media.
2. Artificial General Intelligence (AGI) or Strong AI : It is also
called as Human Level AI. It has the ability to simplify human
intellectual abilities. Due to this, when it exposed to an unfamiliar task,
it has the ability to find the solution. AGI can perform all the things as
humans.
3. Artificial Super intelligence (ASI): It is a brain power, which is
more active than smart humans drawing, mathematics, space, etc; in
each and every field from science to art. It ranges from the computer
just little than the human to trillion times smarter than humans.

17. AI Representation

18. APPROACHES OF A.I.

20. Drug discovery process
Health support and medication assistance
Attainment of in person and online consultation
Helping in repetitive jobs
Maintaining of medical records
Accuracy of medicine
Diagnostic and imaging sector
Competition & prizes
Automotive
Finance &Economics
Video games
Applications of Artificial Intelligence:

21. Health care application Representative company
AI Technology platform Key benefits
Analytics 4 life is pioneering digital
health using AI to develop a completely
new form of medical imaging. With an
initial focus on coronary artery disease
(CAD). It is a novel radiation free and
exercise free cardiac imaging
technology.
Physicians can noninvasively assess
the presence of significant CAD in a
single office visit without radiation,
exercise or pharmacological stressors
using physiologic signals naturally
emitted by the body.
By using this platform to cardiac phase
space tomography analysis (cPSTA) data
and paired coronary angiography results
it developed its initial product focused
on CAD.
Delivers an improved diagnostic solution
previously available only through
invasive, expensive tests providing
immediate and measurable benefits to
patients, payers and providers.
Intelligent diagnostics

22. Health care application Representative company
AI Technology platform Key benefits
It offers a machine intelligence software
platform, Topological data analysis
(TDA), that enables organizations to
analyze and build predictive models
using big data or highly dimensional data
sets.
It allow healthcare providers and
pharmaceutical companies to
automatically stratify complex data
and uncover relationships to optimize
patent care paths., procedures and
protocols for personalized medicine
leading to faster and more effective
outcomes.
The TDA platform draws on a range of
machine learning statistical and genomic
algorithms to combine and synthesize
them in accordance with the data.
Patient and provider data base

23. Health care application Representative company
AI Technology platform Key benefits
It uses it's advanced proprietary AI that
can be applied to manage publicly and
privately available noisy data.
Helps uncover valuable biology not
easily translated by the traditional
approaches enabling faster lead design
and candidate identification while
reducing development costs and
attrition rates.
It developed a technology that can
model most important absorption,
distribution, metabolism and excretion
properties in the drug development
process
Drug discovery process with
advanced analytics

24. Health care application Representative company
AI Technology platform Key benefits
It developed robotic assisted surgical
products with a platform that includes
advanced imaging, robotics, big data
management and machine learning to
provide advanced surgical tools and
capabilities to surgeons.
Expected to be only 20% the size of
and considerably less expensive than
current systems, while improving quality
of precision and patient outcomes
significantly.
Focus on improving and standardizing
the outcomes in challenging procedures
such as thoracic lobectomy, gastrectomy
and low anterior resection.
Medical devices and robotics

25. Health care application Representative company
AI Technology platform Key benefits
It uses AI to contextualize data
regarding a patient’s health status and
self management behavior to provide
early detection of potentially harmful
health events.
Significantly impacts health care
quality and cost by improving self-
management and enabling proactive
interventions.
At the core of Ibis platform lies Scio, an
AI brain which allows complex health
management via a continuous five-step
AI process including observation,
learning, discovering, anticipating and
prompting
With this system, upto 80% comply
with their care plan versus a control
50% norm.
Significantly reduces acute care
utilization.
Home health using A. I.

26. Artificial intelligence : healthcare diagnostic and scope

27. Error Reduction - Artificial Intelligence helps human beings to reduce the error
and increases the chance of reaching accuracy with more precision.
Daily Application - Artificial Intelligence is useful for the daily application
purpose. Everyone widely uses the GPS system, which is helpful in long Drives.
Digital Assistants - Artificial Intelligence systems ‘avatar’ which are models of
digital assistants are used by advanced organizations to reduce the need for human
resources. The avatars are free of emotional thinking, so they think logically and
take right decisions. Human emotions are generally associated with moods that
disturb the judgments and affect the human efficiency.
Repetitive Jobs & multi - tasking - Humans can do only one task at a time.
Machines can perform multi-tasking and can think faster than human beings.
Machines can perform dangerous tasks and their parameters can be adjusted i.e.
speed and time.
No Breaks - Humans can work 8 hours per day with 2 or 3 breaks. Unlike human
beings machines do not require frequent breaks and refreshment.

28. Medical Applications - Nowadays, the physicians are assessing the patients and
analyzing the health risks with the help of Artificial Intelligence. Artificial
Intelligence program is educating the physicians about various medicines and
their side effects. Training surgeons are gaining knowledge with the help of
simulators of artificial surgery. They are trained with the help of artificial surgery
simulators viz., brain simulation, heart simulation, GIT simulation etc.
No risk of harm - when human beings are working at the fire stations, if some
mishap happens, it causes harm to the personnel. While in the case of machines,
they don’t feel and have emotions. Also, If machines are broken, it is possible to
mantle the parts.
Act as aids - Machines which have AI technology can be used to serve children
with disability or the elders on a 24/7 basis. They act as a source for teaching and
learning. They are also useful in security alerting in fires, robbery in banks and in
difficult climatic conditions.
Limitless functions - Machines do not have any boundaries; they do everything
better than humans. They are emotionless, more efficient, more accurate and
provide more free time to us.

29.  High cost
 Decrease in demand for human labour
 AI may be programmed to do somethingdevastating
 Machine Ethics
 Thestorage and access are not
as effective as human brains
 No improvement with
experience
Disadvantages of A.I.

31.  Improved speech, voice, image, video
recognition will change the way devices.
 Personal assistants will become more
personal and context aware.
 More and more systems will run
autonomously to a point
 The positive impact AI research can
have on humanity, will start to be
across many walks of life - much of it
behind the scenes

32. CONCLUSION
 A.I. is a common topic in both Science Fiction & Projection.
 The future of Technology & society.
Rivals Human Intelligence.
Raises difficult Ethical Issues

33. A.I. Is like two edged sword, at one end they can solve
problems intelligently, at another end they pose a problem
themselves…. So we have to handle it properly.
I Am Good Or Bad ???
It’s Depends on who Created