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Emerging technology for, Summaries of Computer Communication Systems

Haramaya UniversityComputer Communication Systems
Prof. Ibsa Dukena

Haramaya University for ethiopia

Typology: Summaries

2025/2026

Uploaded on 06/22/2026

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CHAPTER THREE
Artificial Intelligence
1
Andualem T.
8/8/2021 Fundamental of Information System
Contents
How humans think
Types of AI
Levels of AI
History of AI
Artificial Intelligence
2
Application of AI
8/8/2021 Fundamental of Information System
Artificial Intelligence (AI)
•Artificial Intelligence is composed of two words Artificial and
Intelligence.
•Artificial defines "man-made," and intelligence defines "thinking power",
or “the ability to learn and solve problems”
•Artificial Intelligence means "a man-made thinking power."
•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.
•Intelligence is the ability to acquire and apply knowledge.
3
8/8/2021 Fundamental of Information System
Artificial Intelligence (AI)
•Knowledge is the information acquired through experience.
•Experience is the knowledge gained through exposure (training).
•Therefore, artificial intelligence as the “copy of something natural (i.e.,
human beings) „WHO‟ is capable of acquiring and applying the
information it has gained through exposure.”
•Artificial Intelligence exists when a machine can have human-based
skills such as learning, reasoning, and solving problems.
•In Artificial Intelligence you do not need to preprogram a machine to
do some work, despite that you can create a machine with programmed
algorithms which can work with own intelligence.
4
8/8/2021 Fundamental of Information System
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CHAPTER THREE

Artificial Intelligence

1

Andualem T.

Contents

How humans think

Types of AI

Levels of AI

History of AI

Artificial Intelligence

2

Application of AI

Artificial Intelligence (AI)

  • Artificial Intelligence is composed of two words Artificial and Intelligence.
  • Artificial defines "man-made," and intelligence defines "thinking power", or “the ability to learn and solve problems”
  • Artificial Intelligence means "a man-made thinking power."
  • 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.
  • Intelligence is the ability to acquire and apply knowledge.

8/8/2021 Fundamental of Information System 3

Artificial Intelligence (AI)

  • Knowledge is the information acquired through experience.
  • Experience is the knowledge gained through exposure (training).
  • Therefore, artificial intelligence as the “copy of something natural (i.e., human beings) „WHO‟ is capable of acquiring and applying the information it has gained through exposure.”
  • Artificial Intelligence exists when a machine can have human-based skills such as learning, reasoning, and solving problems.
  • In Artificial Intelligence you do not need to preprogram a machine to do some work, despite that you can create a machine with programmed algorithms which can work with own intelligence.

8/8/2021 Fundamental of Information System 4

Artificial Intelligence (AI)

  • Intelligence is composed of:
    • Reasoning
    • Learning
    • Problem Solving
    • Perception and
    • Linguistic Intelligence
  • Artificial Intelligence system is composed of
    • Agent and
    • Environment.

Artificial Intelligence (AI)

  • Artificial Intelligence system is composed of Agent and its Environment. - An agent (e.g., human or robot) is anything that can perceive its environment through sensors and acts upon that environment through effectors. - Intelligent agents must be able to set goals and achieve them. - Machine perception is the ability to use input from sensors (such as cameras, microphones, sensors, etc.) to deduce aspects of the world. e.g., Computer Vision.

Artificial Intelligence (AI)

  • High-profile Examples of AI include
    • Autonomous vehicles (such as drones and self-driving cars)
    • Medical diagnosis
    • Creating art (such as poetry)
    • Proving mathematical theorems
    • Playing games (such as Chess or Go)
    • Search engines (such as Google search)
    • Online assistants (such as Siri)
    • Image recognition in photographs
    • Spam filtering
    • Prediction of judicial decisions and
    • Online advertisements

8/8/2021 Fundamental of Information System 7

Artificial Intelligence (AI)

  • AI deals with the area of developing computing systems that are capable of performing tasks that humans are very good at. - Example: recognizing objects, recognizing and making sense of speech, and decision making in a constrained environment.
  • Machine Learning is an advanced form of AI where the machine can learn as it goes rather than having every action programmed by humans.
  • Machine learning, a fundamental concept of AI research since the field‟s inception, is the study of computer algorithms that improve automatically through experience.

8/8/2021 Fundamental of Information System 8

Advantages of Artificial Intelligence

  • High Accuracy with fewer errors: AI machines or systems are prone to fewer errors and high accuracy as it takes decisions as per pre-experience or information.
  • High-Speed: AI systems can be of very high-speed and fast-decision making, because of that AI systems can beat a chess champion in the Chess game.
  • High reliability: AI machines are highly reliable and can perform the same action multiple times with high accuracy.
  • Useful for risky areas: AI machines can be helpful in situations such as defusing a bomb, exploring the ocean floor, where to employ a human can be risky.
  • Digital Assistant: AI can be very useful to provide digital assistant to users such as AI technology is currently used by various E-commerce websites to show the products as per customer requirements.
  • Useful as a public utility: AI can be very useful for public utilities such as a self driving car which can make our journey safer and hassle-free, facial recognition for security purposes, Natural language processing (for search engines, for spelling checker, for assistant like Siri, for translation like google translate ), etc.

Disadvantages of Artificial Intelligence

  • High Cost: The hardware and software requirement of AI is very costly as it requires lots of maintenance to meet current world requirements.
  • Can't think out of the box: Even we are making smarter machines with AI, but still they cannot work out of the box, as the robot will only do that work for which they are trained, or programmed.
  • No feelings and emotions: AI machines can be an outstanding performer, but still it does not have the feeling so it cannot make any kind of emotional attachment with humans, and may sometime be harmful for users if the proper care is not taken.
  • Increase dependence on machines: With the increment of technology, people are getting more dependent on devices and hence they are losing their mental capabilities.
  • No Original Creativity: As humans are so creative and can imagine some new ideas but still AI machines cannot beat this power of human intelligence and cannot be creative and imaginative.

History of AI [Reading Assignment]

8/8/2021 Fundamental of Information System 15

History of AI A. Maturation of Artificial Intelligence (1943-1952)

  • The year 1943: The first work which is now recognized as AI was done by Warren McCulloch and Walter pits in 1943. They proposed a model of artificial neurons.
  • The year 1949: Donald Hebb demonstrated an updating rule for modifying the connection strength between neurons. His rule is now called Hebbian learning.
  • The year 1950: The Alan Turing who was an English mathematician and pioneered Machine learning in 1950. - Alan Turing publishes " 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.

8/8/2021 Fundamental of Information System 16

History of AI

B. The birth of Artificial Intelligence (1952-1956)

  • The year 1955: An Allen Newell and Herbert A. Simon created the "first artificial intelligence program" Which was named "Logic Theorist". This program had proved 38 of 52 Mathematics theorems, and find new and more elegant proofs for some theorems.
  • The year 1956: The word "Artificial Intelligence" first adopted by American Computer scientist John McCarthy at the Dartmouth Conference. For the first time, AI coined as an academic field. At that time high-level computer languages such as FORTRAN, LISP, or COBOL were invented. And the enthusiasm for AI was very high at that time.

History of AI

C. The golden years-Early enthusiasm (1956-1974)
  • The year 1966: The researchers emphasized developing algorithms that can solve mathematical problems. Joseph Weizenbaum 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. AI winter refers to the time period where computer scientists dealt with a severe shortage of funding from the government for AI researches.
  • During AI winters, an interest in publicity on artificial intelligence was decreased.

History of AI

E. A boom of AI (1980-1987)

  • The year 1980: After AI winter duration, AI came back with "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.
  • Again, Investors and government stopped in funding for AI research due to high cost but not efficient results. The expert system such as XCON was very cost-effective.

8/8/2021 Fundamental of Information System 19

History of AI

G. The emergence of intelligent agents (1993-2011)
  • The year 1997: In the year 1997, IBM Deep Blue beats
world chess champion, Gary Kasparov, and became the
first computer to beat a 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.

8/8/2021 Fundamental of Information System 20

Levels of AI

  • Stage 5 – Self Aware Systems / Artificial General Intelligence (AGI)
    • These systems have human-like intelligence
    • AGI is the intelligence of a machine that has the capacity to understand or learn any intellectual task that a human being can.
  • Stage 6 – Artificial Superintelligence (ASI)
    • AI algorithms can outsmart even the most intelligent humans in every domain.
    • Logically it is difficult for humans to articulate what the capabilities might be, yet we would hope examples would include solving problems we have failed to so far, such as world hunger and dangerous environmental change.
    • A few experts who claim it can be realized by 2029.
    • Fiction has tackled this idea for a long time, for example in the film Ex Machina or Terminator.

Levels of AI

  • Stage 7 – Singularity and Transcendence
    • This leads to a massive expansion in human capability.
    • Human augmentation could connect our brains to each other and to a future successor of the current internet, creating a “hive mind” that shares ideas, solves problems collectively, and even gives others access to our dreams as observers or participants.
    • Pushing this idea further, we might go beyond the limits of the human body and connect to other forms of intelligence on the planet – animals, plants, weather systems, and the natural environment.
    • (^) Some proponents of singularity such as Ray Kurzweil, Google‟s Director of Engineering, suggest we could see it happen by 2045 as a result of exponential rates of progress across a range of science and technology disciplines.
    • The other side of the fence argues that singularity is impossible and human consciousness could never be digitized

Levels of AI

8/8/2021 Fundamental of Information System 27

Types of AI

  • Artificial Intelligence can be divided into various types, these are
    • Based on Capabilities and
    • Based on Functionality

8/8/2021 Fundamental of Information System 28

Based on Capabilities

1. Weak AI or Narrow AI: - Is a type of AI which is able to perform a dedicated task with intelligence. - cannot perform beyond its field or limitations, as it is only trained for one specific task. - Also called as Weak AI. - Is the most common and currently available AI in the world - Can fail in unpredictable ways if it goes beyond its limits. - E.g. Apple Siri , IBM's Watson supercomputer ,Google translate, playing chess, purchasing suggestions on e-commerce sites, self-driving cars, speech recognition, and image recognition.

Based on Capabilities

2. General AI - Is a type of intelligence that could perform any intellectual task with efficiency like a human. - The idea behind the general AI to make such a system that could be smarter and think like a human on its own. - Currently, there is no such system exists which could come under general AI and can perform any task as perfect as a human. - As systems with general AI are still under research, and it will take lots of effort and time to develop such systems.

Based on Capabilities

3. 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.
  • Some key characteristics of strong AI include capability include the ability to think, to reason solve the puzzle, make judgments, plan, learn, and communicate on its own.
  • Super AI is still a hypothetical concept of Artificial Intelligence.
  • The development of such systems in real is still a world-changing task.

8/8/2021 Fundamental of Information System 31

Based on Functionality

1. Reactive Machines:

  • The most basic types of Artificial Intelligence
  • Do not store memories or past experiences for future actions
  • Only focus on current scenarios and react on it as per possible best action.
  • Eg. IBM's Deep Blue system and Google's AlphaGo

8/8/2021 Fundamental of Information System 32

Influencers of Artificial Intelligence

  • Influencers of AI includes:
    • Big data: Structured data versus unstructured data
    • Advancements in computer processing speed and New chip architectures
    • Cloud computing and Application Program Interfaces
      • Cloud computing is a general term that describes the delivery of on-demand services, usually through the internet, on a pay-per-use basis.
    • The emergence of data science
      • The goal of data science is to extract knowledge or insights from data in various forms, either structured or unstructured, which is like data mining.

Applications of Artificial Intelligence

  • AI in agriculture
    • Very helpful for farmers
    • As agriculture robotics, solid and crop monitoring
  • AI in Healthcare
    • to make a better and faster diagnosis than humans.
  • AI in education
    • as a teaching assistant
    • Eg: chatbot
  • AI in Finance and E-commerce
  • AI in Gaming : eg chess
    • AI in Social Media
      • To organize and manage massiveamounts of data
    • AI in Data Security
      • used to make your data moresafe and secure.
    • AI in Travel &Transport
      • Use chatbots which can make human-like interaction withcustomers
    • AI in Robotics
    • AI in Entertainment
    • AI in the Automotive Industry

AI Tools and Platforms

  • AI has developed a large number of tools to solve the most difficult problems in computer science, like: - Search and optimization - Logic - Probabilistic methods for uncertain reasoning - Classifiers and statistical learning methods - Neural networks - Control theory - Languages
  • Most common artificial intelligence platforms include Microsoft AZURE Machine Learning, Google Cloud Prediction API, IBM Watson, TensorFlow, Infosys Nia, Wipro HOLMES, API.AI, Premonition, Rainbird, Ayasdi, MindMeld, and Meya.

8/8/2021 Fundamental of Information System 39

Sample AI Application

  • Commuting
    • Googles AI-powered predictions
    • Ridesharing Apps like Uber
  • E-mail
    • Spam filters
    • Smart e-mail categorization
  • AI in education
    • As a teaching assistant
    • Eg: chatbot
  • Social Networking
    • Facebook
    • Instagram
      • Online Shopping
        • Search (Amazon)
        • recommendations for products
      • Mobile Use
        • Voice-to-text
        • Smart personal Assistants (Siri)

8/8/2021 Fundamental of Information System 40

END OF CHAPTER THREE

Next: Chapter Four: IoT

8/8/2021 Fundamental of Information System 41