Emerging Technology Chapter 3 Artificial Intelligence

Chapter Three
Artificial Intelligence

Intelligence (AI) ?
 In 1956, the term artificial intelligence was defined by John McCarthy. He defined
AI as: ‘The science and engineering of making intelligent machines.’
 The development of computer systems that are capable of performing tasks that
require human intelligence, such as decision making, object detection, solving
complex problems, and so on.
Source: Internet

 From The term Artificial Intelligence
• 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.
• It has the ability to acquire, understand and apply knowledge, or the ability to exercise
thought and reason or the ability of problem solving, learn and recognize, understand and
perceive,
What is Artificial Intelligence (AI)?
A man made thinking power.

Intelligenge?
● Intelligence is composed of:
 Reasoning
 Learning
 Problem Solving
 Perception
 Linguistic Intelligence

AI and Machine Learning (ML)
 Machine learning, an advanced form of AI
where the machine can learn as it goes
rather than having every action
programmed by humans.
 Neural networks are biologically inspired
networks that extract features from the
data in a hierarchical fashion. The field of
neural networks with several hidden layers
is called deep learning.

Some known examples of AI
Autonomous vehicles
playing games
search engines
medical diagnosis

AI System
 is the system that is intelligent.
 It composed from two things:
1. Agent Is anything that can perceive its environment through sensors and acts upon
that environment through effectors. E.g. Robot, Human
2. Environment the environment where the agent can perceive and act up on it.

AI Intelligence
Need for Artificial Intelligence:
 To create expert systems(the capability to learn, demonstrate, explain
and advice its users)
 Helping machines find solutions to complex problems
.

Goals of Artificial Intelligence
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

AI AND ITS DISCIPLINES
AI
Sociology
Computer
Science Psychology
Neuron
System Philosophy
Biology Mathematics

Advantage and Disadvantage of AI
 High Accuracy with fewer errors
 High-Speed (fast decision making)
 High reliability
 Useful for risky areas (such as defusing
bomb, exploring ocean floor)
 Digital Assistant
 Useful as a public utility (self driving cars)
● High Cost
● Can't think out of the box
● No feelings and emotions
● Increase dependence on machines
● No Creativity
● Unemployment
Advantage Disadvantage

13
● Do you think AI is new technology?
● It is much older than you would imagine.
History of AI

IBM Deep Blue
First computer to
beat world chess
champion
Evolution of
Artificial
Neuron
1950
1966 1990 2011
1956 1980 2011
1943 1972 1997 2015
2002
1976
Turing
Machine
Birth of AI
Dartmouth
Conference
First Chabot:
Elisa
First intelligent
robot Wabot-1
AI in home
Roomba
First AI Winner
Expert System
Second AI
winner
IBM Watson
Win quiz show
Google Now
Amazon Echo
HISTORYOFAI

15
 A. Maturation of Artificial Intelligence (1943-1952)
 The year 1943:
 The first work which is now recognized as AI
 done by Warren McCulloch and Walter.
 They proposed a model of artificial neurons.
 The year 1949:
 modifying the connection strength between neurons.
 Donald Hebb
 His rule is now called Hebbian learning.
 The year 1950:
 The Alan Turing who was an English mathematician and pioneered Machine learning in 1950.
 "Computing Machinery and Intelligence" in which he proposed a test.
 The test can check the machine's ability to exhibit intelligent behavior equivalent to human
intelligence, called a Turing test.
 B. The birth of Artificial Intelligence (1952-1956)
 The year 1955:
 "first artificial intelligence program" Which was named "Logic Theorist".
 This program had proved 38 of 52 Mathematics theorems,
 The year 1956:
 The word "Artificial Intelligence" first adopted by American Computer scientist John
McCarthy
 At that time high-level computer languages such as FORTRAN, LISP, or COBOL were

16
 The year 1966:
 developing algorithms that can solve mathematical problems.
 created the first chatbot in 1966, which was named as ELIZA.
 The year 1972:
 The first intelligent humanoid robot was built in Japan which was named WABOT-
1.
 D. The first AI winter (1974-1980)
 The duration between the years 1974 to 1980 was the first AI winter duration.
 During AI winters, an interest in publicity on artificial intelligence was decreased.
 E. A boom of AI (1980-1987)
 The year 1980:
 "Expert System". Expert systems were programmed that emulate the decision-making
ability of a human expert.
 In the Year 1980, the first national conference of the American Association of Artificial Intelligence
was held at Stanford University.
 F. The second AI winter (1987-1993)
 The duration between the years 1987 to 1993 was the second AI Winter duration..

17
 G. The emergence of intelligent agents (1993-2011)
 The year 1997: IBM Deep Blue beats world chess champion,.
 The year 2002: for the first time, AI entered the home in the form of Roomba, a vacuum cleaner.
 The year 2006: AI came into the Business world until the year 2006. Companies like Facebook,
Twitter, and Netflix also started using AI.
H. Deep learning, big data and artificial general intelligence (2011-present)
 The year 2011: In the year 2011,
 Develop the machine that solve complex questions as well as riddles.
 proved that it could understand natural language and can solve tricky questions
quickly.
 The year 2012:
 Google has launched an Android app feature "Google now", which was able to provide
information to the user as a prediction.

TYPES OF
● ,M
Weak General
Strong
Reactive
Machine
Limited
Memory
Theory of
Mind
Self
Awareness
BASED ON
CAPABILITIES BASED ON
FUNCTIONALITY
AI

Types of AI Based on Capabilities:
1. Weak AI - The most common and currently available AI (e.g. Siri, IBM Watson)
 cannot perform beyond its field or limitations, as it is only trained for one specific task.
 Narrow AI can fail in unpredictable ways if it goes beyond its limits
2. General AI - Could perform any intellectual task with efficiency like a human.
● such a system that could be smarter and think like a human on its own.
● As systems with general AI are still under research, and it will take lots of effort and time to develop such systems.
3. Super AI – These machines could surpass human intelligence (hypothetical)
 can perform any task better than a human with cognitive properties.
 the ability to think, to reason solve the puzzle, make judgments, plan, learn, and communicate on its own.

Types of AI Based on Functionality:
1. Reactive Machines - focus on current scenarios and react on it (e.g. Google AlphaGo, IBM
deep blue), do not store memories or past experiences for future actions
2. Limited Memory - can store past experiences or some data for a short period of time(e.g.
self driving cars).
3. Theory of Mind - Should understand human emotions, beliefs, and be able to interact social
like humans. (Still not developed, researchers are working on it)
4. Self-Awareness - Have their own consciousness, the future of AI (Hypothetical)

 Intelligence or cognitive process of human is composed of three main stages:
1.Observe and input the information or data in the brain.
2.Interpret and evaluate the input that is received from the surrounding environment.
3.Make decisions as a reaction towards what you received as input and interpreted and
evaluated.
AI researchers are simulating the same stages.
How Human think?

Mapping human thinking to artificial intelligence
components
 Acquire information from their surrounding - sensing layer
 Reasoning and thinking about the gathered input – Processing
 Taking action or making decisions – Solve problems, Respond
to user

Influencers of artificial intelligence
 Big data: Structured data versus unstructured data
 Advancements in computer processing speed and new chip
architectures
 Cloud computing: Delivery of on-demand AI services (AWS,
IBM Cloud etc.) though internet
 The emergence of data science: extract knowledge or
insights from data.
 Big Data
 Advancement of
processing speed
 Cloud computing
 Data science
INFLUENCERS

Applications of AI
 Agriculture (crop monitoring, Detecting diseases)
 Healthcare (Smart watches, diagnosing systems)
 Education (Teaching assistant, Virtual reality)
 Finance and Economics (chatbot, Prediction,
 Gaming (Strategic games, PES)
 Data security (AI2 Platform, AEG bot)
 Communication (Twitter, Facebook, Telegram)
 Transport (Suggesting the hotels, best routes)
 Automotive Industry (Self driving cars,
TeslaBot)
 Robotics (Sophia, Erica)
 Entertainment (Virtual Reality, Augmented
Reality, Netflix

25
● Platforms are some sort of hardware architecture or software framework.
● Provide users a tool kit to build intelligent applications.
● The most common AI platforms are:
 IBM Cloud, Microsoft AZURE ML, Google Cloud Prediction API etc.
AI tools and platforms

Emerging Technology Chapter 3 Artificial Intelligence

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