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GOALS OF ARTIFICIAL
INTELLIGENCE
Deduction, reasoning, problem solving
THE BRANCHES OF AI
Logical AI
Knowledge representation
Search
Planning
Pattern Recognition
Learning
Natural
language
(communication)
Motion and manipulation
processing
Representation
Inference
Perception
Long-term
goals:
General
intelligence,Socialintelligence,Creativity
TOOLS OF ARTIFICIAL
INTELLIGENCE
Probabilistic methods for uncertain
reasoning
Classifiers and statistical learning methods
Neural networks
Control theory
Languages
Common sense knowledge and
reasoning
Learning from experience
Planning
Epistemology
Ontology
Heuristics
Logic
Search and optimization
Genetic Programming
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What is Artificial Intelligence?
Artificial
Intelligence
is
the
intelligence exhibited by machines or
software. It is also an academic field of
study. Major AI researchers and textbooks
define the field as "the study and design of
intelligent agents", where an intelligent
agent is a system that perceives its
environment and takes actions that
maximize its chances of success.John
McCarthy, who coined the term in 1955,
defines it as "the science and engineering of
making intelligent machines". AI research
is highly technical and specialised, and is
deeply divided into subfields that often fail
to communicate with each other. Some of
the division is due to social and cultural
factors: subfields have grown up around
particular institutions and the work of
individual researchers.
AI research is also divided by several
technical issues. Some subfields focus on
the solution of specific problems. Others
focus on one of several possible approaches
or on the use of a particular tool or towards
the
accomplishment
of
particular
applications. The field was founded on the
claim that a central property of humans,
intelligence—the sapience of Homo
sapiens—"can be so precisely described that
a machine can be made to simulate it." This
raises philosophical issues about the nature
of the mind and the ethics of creating
artificial beings endowed with human-like
intelligence, issues which have been
addressed by myth, fiction and philosophy
since antiquity.
Artificial intelligence has been
the subject of tremendous optimism
but has also suffered stunning
setbacks. Today it has become an
essential part of the technology
industry, providing the heavy lifting
for many of the most challenging
problems in computer science.
Approaches of AI
Historically there were two main
approaches to AI: ?
 classical approach (designing the AI),
based on symbolic reasoning - a
mathematical approach in which
ideas and concepts are represented by
symbols such as words, phrases or
sentences, which are then processed
according to the rules of logic.
 a connectionist approach (letting AI
develop), based on artificial neural
networks, which imitate the way
neurons work, and genetic algorithms,
which imitate inheritance and fitness
to evolve better solutions to a
problem with every generation.
Symbolic reasoning have been successfully
used in expert systems and other fields.
Neural nets are used in many areas, from
computer games to DNA sequencing. But
both approaches have severe limitations. A
human brain is neither a large inference
system, nor a huge homogenous neural net,
but rather a collection of specialised
modules. The best way to mimic the way
humans think appears to be specifically
programming a computer to perform
individual functions (speech recognition,
reconstruction of 3D environments, many
domain-specific functions) and then
combining them together.
Additional approaches:



genetics, evolution
Bayesian probabilyinferencing
combinations - ie: "evolved
(genetic) neural networks that
influence probability distributions
of formal expert systems"
Themes of AI
The main advances over the past
sixty years have been advances in search
algorithms, machine learning algorithms,
and integrating statistical analysis into
understanding the world at large.
However most of the breakthroughs in AI
aren’t noticeable to most people. Rather
than talking machines used to pilot space
ships to Jupiter, AI is used in more subtle
ways such as examining purchase histories
and
influence
marketing
decisions[Shaw01].
What most people think of as ‘true
AI’ hasn’t experienced rapid progress over
the decades. A common theme in the field
has been to overestimate the difficulty of
foundational problems. Significant AI
breakthroughs have been promised ‘in 10
years’ for the past 60 years. In addition,
there is a tendency to redefine what
‘intelligent’ means after machines have
mastered an area or problem. This
so-called ‘AI Effect’ contributed to the
3
downfall of US- based AI research in the
80s.
In the field of AI expectations seem
to always outpace the reality. After decades
of research, no computer has come close to
passing the Turing Test (a model for
measuring ‘intelligence’); Expert Systems
have grown but have not become as
common as human experts; and while
we’ve built software that can beat humans
at some games, open ended games are still
far from the mastery of computers. Is
the problem simply that we haven’t
focused enough resources on basic research,
as is seen in the AI winter section, or is the
complexity of AI one that we haven’t yet
come to grasp yet? (And instead, like in the
case of computer Chess, we focus on much
more specialized problems rather than
understanding
the
notion
of
‘understanding’ in a problem domain.)
This paper will go into some of these
themes to provide a better understanding
for the field of AI and how it has
developed over the years. In looking at
some of the key areas of AI work and the
forces that drove them, perhaps we can
better understand future developments in
the field.
What are the Applications of
Artificial Intelligence?
have been adopted by mainstream
computer science and are no longer
considered a part of AI
Finance
Banks use artificial intelligence
systems to organize operations, invest in
stocks, and manage properties.
Hospitals and medicine
Artificial intelligence has been used in a
wide range of fields including medical
diagnosis, stock trading, robot control, law,
remote sensing, scientific discovery and
toys. However, many AI applications are
not perceived as AI: "A lot of cutting edge
AI has filtered into general applications,
often without being called AI because once
something becomes useful enough and
common enough it's not labeled AI
anymore," Nick Bostrom reports.[1] "Many
thousands of AI applications are deeply
embedded in the infrastructure of every
industry."[2] In the late 90s and early 21st
century, AI technology became widely used
as elements of larger systems,[2][3] but the
field is rarelycredited for these successes.
Computer science
AI researchers have created many tools
to solve the most difficult problems in
computer science. Many of their inventions
A medical clinic
can use artificial
intelligence
systems to organize
bed
schedules,
make a staff rotation, and provide medical
information and other important tasks.
Heavy industry
Robots have become common in many
industries. They are often given jobs that
are considered dangerous to humans.
Robots have proven effective in jobs that
are very repetitive which may lead to
mistakes or accidents due to a lapse in
concentration and other jobs which
humans may find degrading.
Online and telephone customer
service
Artificial intelligence is implemented in
automated online assistants that can be
seen as avatars on web pages.It can avail
for enterprises to reduce their operation and
training cost. A major underlying
technology to such systems is natural
language processing.
Transportation
Fuzzy
logic
controllers have been
developed
for
automatic gearboxes
in automobiles (the
2006 Audi TT, VW
Touregand VW Caravell feature the DSP
transmission which utilizes Fuzzy Logic, a
number of Škoda variants (ŠkodaFabia)
also currently include a Fuzzy Logic based
controller).
Telecommunications
Many telecommunications companies
make use of heuristic search in the
management of their workforces, for
example BT Group has deployed heuristic
search[9] in a scheduling application that
provides the work schedules of 20,000
engineers.
Toys and games
The 1990s saw some of the first
attempts to mass-produce domestically
aimed types of basic Artificial Intelligence
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for education, or leisure. This prospered
greatly with the Digital Revolution, and
helped introduce people, especially children,
to a life of dealing with various types of
Artificial Intelligence, specifically in the
form of Tamagotchis and Giga Pets, iPod
Touch, the Internet (example: basic search
engine interfaces are one simple form), and
the first widely released robot, Furby.
Music
The evolution of
music has always
been affected by
technology. With AI,
scientists are trying to
make the computer
emulate the activities
of the skillful musician. Composition,
performance,
music
theory,
sound
processing are some of the major areas on
which research in Music and Artificial
Intelligence are focusing.
Aviation
The Air Operations Division (AOD) uses AI
for the rule based expert systems. The AOD
has use for artificial intelligence for
surrogate operators for combat and
training simulators, mission management
aids, support systems for tactical decision
making, and post processing of the
simulator data into symbolic summaries.
10 Ways Artificial Intelligence
Will Affect Our Lives
By Bambi Turner
Since the start of the 21st century, there's
no question that mankind has made
tremendous strides into the field of robotics.
While modern robots can now replicate the
movements and actions of humans, the
next challenge lies in teaching robots to
think for themselves and react to changing
conditions. The field of artificial
intelligence promises to give machines the
ability to think analytically, using
concepts and advances in computer science,
robotics and mathematics.
While scientists have yet to realize the full
potential of artificial intelligence, this
technology will likely have far-reaching
effects on human life in the years to come.
Read on to learn about some of the
surprising ways in which artificial
intelligence impacts your life today, and
see how it could change things in the
future.
1.
Taming the Weather
Meteorologists analyze large volumes of
data in order to predict the weather, and
even the most experienced weatherman
isn't always accurate. Soon, scientists may
be able to predict the weather better by
using artificial intelligence software, which
can sift through complex data and spot
patterns missed by the human eye. When
this software sees a big storm coming, it
will automatically issue alerts to warn
residents and the media, and this may help
save lives.
2.
Tackling Dangerous (or Boring)
Tasks
If you have a robotic vacuum cleaner in
your home, you're already taking
advantage of artificial intelligence to tackle
one of life's more tedious tasks. These
devices not only clean your floor according
to schedule, but are also able to maneuver
around obstacles like stairs, furniture and
even the cat. Facilities with large turf
areas, like golf courses, rely on similar
technology to mow their lawns without the
need for human intervention. The same
technology may soon allow robots to
perform boring or repetitive tasks along an
assembly line, or even sort trash and
recycling at waste processing centers.
3.
Saving the Planet
With artificial intelligence, scientists may
soon be able to use robots or other devices
to clean up the environment and reduce
the effects of air and water pollution.
Advanced software programs will allow
these machines to distinguish between
biological
organisms
and
potential
pollutants like oil or hazardous waste. Tiny
microbes will consume waste products and
leave good biological matter intact,
minimizing damage to the ecosystem.
4.
Driverless Transport
Imagine cars that warn you of potential
obstacles to help you avoid accidents, or
even allow you to sit back and take in the
sites as they drive themselves. Artificial
intelligence may soon make all this possible,
using cameras, sensors and special software
built into the vehicle. Manufacturers
already rely on this technology to make
backing up and parking safer, while both
the Toyota Prius and certain Lexus models
can self-park at the touch of a button
5.
Pushing the
Exploration
Limits
of
Space
In the near future, advances in artificial
intelligence will allow scientists to travel
well beyond the limits of 20th-century
space travel and explore more of the
universe beyond our solar system. Today,
NASA relies on unmanned shuttles to
explore distant galaxies that would take
years for humans to reach. Driverless land
rovers also allow researchers to explore and
photograph Mars and other planets, where
inhospitable conditions make human
5
exploration impossible. These smart
vehicles sense obstacles, like craters, and
find safe paths of travel around them
before returning to the shuttle [source:
NASA Jet Propulsion Laboratory].
6.
calls and other communications. These
programs can sift through large volumes of
data quickly and are even capable of
distinguishing between casual conversation
and potential threats [source: U.S.
Department of Homeland Security].
Protect Your Finances
8.
As of 2010, roughly half of world stock
trades
are
driven
by
artificial
intelligence-based
software.
These
programs rely on algorithms to spot
patterns in the market and predict price
changes based on these patterns [source:
Association for the Advancement of
Artificial Intelligence]. Some can even buy
or sell shares based on these predictions,
while others issue an alert to human
brokers and advise them of the changes to
come. This technology results in better
performance and improved returns for
investors.
While the world may not be ready for
flying cars, families may soon enjoy the
perks of robotic servants to handle
housekeeping tasks. These intelligent
robots will not only clean your living room
and do the dishes, but may also tackle jobs
like assembling furniture or caring for kids
and pets. Through the use of artificial
intelligence software, these machines will
be able to recognize and sort objects, and
even learn to minimize future mistakes as
they work [source: Chang].
9.
7.
A Little Help Please
Space-Age Medicine
Staying Safe
Artificial intelligence technology will soon
help keep your family safe by protecting it
from international threats as well as home
burglaries. The U.S. Department of
Homeland Security relies on virtual smart
agents to supplement its human workforce,
or to replace an agent when he or she is
unavailable. The agency also incorporates
artificial intelligence software into its
monitoring systems, which scan phone
While robotic servants and driverless cars
offer a certain wow factor, artificial
intelligence in medicine is already helping
doctors detect diseases and save lives.
Cedars-Sinai Medical Center relies on
special software to examine the heart and
stop heart attacks before they occur
[source: Cedars-Sinai Medical Center].
Artificial muscles feature smart technology
that allows them to function more like real
muscles, and the latest intelligent devices
can distinguish between life-saving
medications and fake or tainted pills.
10. The Robot-Human Species
Transhumanism
represents
the
ultimate application
of
artificial
intelligence
to
human life.
Proponents
of
transhumanism
believe that artificial
intelligence
can
improve the overall
human experience by expanding the limits
of the mind and body. As humans
incorporate more and more technology into
their everyday lives, transhumanism offers
the opportunity to eliminate disabilities,
slow aging and even stop death.
Some picture transhumanism resulting in
cyborgs, while others picture an entirely
new species that people have yet to
imagine: a being that's developed beyond
the current human state to enjoy a higher
level of reasoning, culture and physical
capabilities. While members of the World
Transhumanist Association celebrate the
coming of this new creation, others call it
the most dangerous threat to humanity.
With significant ethical implications,
particularly those related to cloning and
eugenics, transhumanism must be pursued
with extreme care to let mankind maintain
its sense of humanity [source: World
Transhumanist Association].
Softbank unveils 'human-like'
robot Pepper
Japanese firm Softbank has unveiled
a robot called Pepper, which it says can
read human emotions.It uses an "emotional
engine" and a cloud-based artificial
intelligence system that allows it to analyze
gestures, expressions and voice tones.The
firm said people could communicate with it
"just like they would with friends and
family" and it could perform various
tasks.It will go on sale to the public next
year for 198,000 yen ($1,930; £1,150).
"People describe others as being robots
because they have no emotions, no heart,"
Masayoshi Son, chief executive of
Softbank, said at a press conference.
"For the first time in human history,
we're
giving
a
robot
a
heart,
emotions."Softbank said it planned to
subsequently station Pepper at more of its
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stores nationwide.
A prototype version of the robot will serve
customers in Softbank's mobile phone
stores Analysts said that development of
household robots was likely to pick up,
especially in countries like Japan that have
an ageing population."Even if one can
pre-programme such robots to carry out
specific tasks based on certain commands
or gestures, it could go long way in helping
improve elderly care," said RhenuBhuller,
senior vice president healthcare at
consulting firm Frost & Sullivan.
"And with the technology improving fast you could see big improvements in
managing labour requirement in the the
sector."
Softbank developed Pepper in collaboration
with French company Aldebaran Robotics,
in which it took a majority stake in
2012.Bruno Maisonnier, founder and chief
executive of Aldebaran said: "The
emotional robot will create a new
dimension in our lives and new ways of
interacting with technology."
"It's just the beginning, but already a
promising reality."
Creepy or cool? Japan's robots
more human-like than ever
Originally published: June 24, 2014 9:49 AM
Updated: June 24, 2014 10:31 AM
ByTHE ASSOCIATED PRESS
History of AI applied to Chess
Chess has long been considered a game of
intellect, and many pioneers of computing
felt that a chess-playing machine would be
the hallmark of true artificial intelligence.
While the Turing Test is a grand challenge
to ascertain machine intelligence, chess too
is a good pursuit, one which fortunately
has been ‘solved’ by AI researchers;
producing programs which can rival if not
best the world’s best chess players.
However, even the best game- playing
machines still do not understand concepts
of the game and merely rely on brute force
approaches to play.
Origins of computer-Chess
TOKYO - The new robot guides at a Tokyo
museum look so eerily human and speak so
smoothly they almost outdo people —
almost.
Japanese robotics expert Hiroshi Ishiguro,
an Osaka University professor, says they
will be useful for research on how people
interact with robots and on what
differentiates the person from the machine.
"Making androids is about exploring what
it means to be human," he told reporters
Tuesday, "examining the question of what
is emotion, what is awareness, what is
thinking."
Chess and intelligence have always been
linked; the ability to play chess was even
used as a valid question to ask during a
Turning Test in Turing’s original paper.
Many people envisioned machines one day
being capable of playing Chess, but it was
Claude Shannon who first wrote a paper
about developing a chess playing program
Shannon’s paper described two approaches
to computer chess: Type-A programs,
which would use pure brute force,
examining thousands of moves and using a
min-max search algorithm. Or, Type-B,
programs which would use specialized
heuristics and ‘strategic’ AI, examining
only a few, key candidate moves.
Initially Type-B (strategic) programs were
favored over Type-A (brute force) because
during the 50s and 60s computers were so
limited. However, in 1973 the developers of
the ‘Chess’ series of programs (which won
the ACM computer chess championship
1970-72) switched their program over to
Type-A The new program, dubbed ‘Chess
4.0’ went on to win a number of future
ACM computer chess titles. *WikiChess+.
This change was an unfortunate blow to
those hoping of finding a better
understanding of the game of chess
through the development of Type-B
programs. There were several important
factors in moving away from the arguably
more intelligent design of a Type-B
program to a dumber Type-A. The first
was simplicity. The speed of a machine has
a direct correlation to a Type-A program’s
skill, so with the trend being machines
getting faster every year it is easier to write
a strong Type-A program and ‘improve’ a
program by giving it more power through
parallelization or specialized hardware.
Whereas a Type-B program would need
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