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Lecture notes and practical notes - Artifical Intelligence (SET09122) Artificial Intelligence: A Modern Approach, Global Edition, ISBN: 9781292401133R484,54
Artificial Intelligence Full Course
24 September 2020 10:04
1. History of AI
a. Greek Mythology - Talos
i. Giant animated warrior programmed to guard the island of Crete
b. 1950 - Alan Turing
i. Published a paper of machines that can think
ii. Thinking is difficult for a machine
iii. Turing test -
c. 1951 - Game AI
i. Chess program and checkers program
d. 1956 - The birth of AI
i. Coined by John McCarthy
e. 1959 - First AI laboratory
i. MIT lab
f. 1960 - First Robot was introduced
g. 1961 - First Chatbot - Eliza
h. 1997 - IBM Deep Blue - beats world champion at chess
i. 2005 - DARPA Grand Challenge
j. 2011 - IBM Watson
2. Demand for AI
a.
3. What is Artificial Intelligence?
a.
b.
artificial intelligence Page 1
,intro
14 September 2020 15:06
Read - chapter 1 and 2
Week 6 assessment from Ben and submit 10
What language can we use? - Whatever language feels fine for us
1. What is Artificial Intelligence?
a. Thinking Humanly
b. Thinking Rationally
c. Acting Humanly
d. Acting Rationally
2. Contribution to AI
a. Philosophy
i. Can formal rules be used to draw valid conclusions (Aristotle)?
ii. How does the mind Arise from the physical brain (free will), dualism,?
1) Two things - mind brain (dualism)
2) Materialism - one thing
iii. Where does knowledge come from (empiricism, logical positivism)?
1) Measure from our sense
2) Only knowledge you can have are the things you can prove through logic
iv. How does knowledge lead to action (or does the need for action lead to thought)?
b. Mathematics
i. Formal rules
ii. Valid Conclusions
iii. Look logically and compute them
iv. Bayers' Theorem ??
c. Economics
d. Neuroscience
i. How the brain works
e. Psychology
f. Computer engineering - important
i. Intelligence and artefact
g. Control Theory and Cyvernetics
artificial intelligence Page 2
, Important
03 October 2020 23:03
• Artificial Intelligence
• Machine Learning - the ability for an algorithm to learn from prior data in order to produce a
behavior. It is teaching machines to make decisions in situations they have never seen.
• Deep Learning - branch of machine learnning where artificial neural networks - algorithms
inspired by the way neurons work in the brain - find patterns in raw data by combining
multiple layers of artificial naurons.
• Natural Language Processing - must communicate with humans as well as humans
communicate with each other.
• Context Awareness - like a human assistant, an AI assistant can only be as smart as the
information - the context - you give it access to.
• Machine Learning: It’s the science of getting computers to act by feeding them data
so that they can learn a few tricks on their own, without being explicitly programmed
to do so.
• Neural Networks: They are a set of algorithms and techniques, modeled in
accordance with the human brain. Neural Networks are designed to solve complex
and advanced machine learning problems.
• Robotics: Robotics is a subset of AI, which includes different branches and
application of robots. These Robots are artificial agents acting in a real-world
environment. An AI Robot works by manipulating the objects in it’s surrounding, by
perceiving, moving and taking relevant actions.
• Expert Systems: An expert system is a computer system that mimics the decision-
making ability of a human. It is a computer program that uses artificial intelligence
(AI) technologies to simulate the judgment and behavior of a human or an
organization that has expert knowledge and experience in a particular field.
• Fuzzy Logic Systems: Fuzzy logic is an approach to computing based on “degrees
of truth” rather than the usual “true or false” (1 or 0) boolean logic on which the
modern computer is based. Fuzzy logic Systems can take imprecise, distorted, noisy
input information.
• Natural Language Processing: Natural Language Processing (NLP) refers to the
Artificial Intelligence method that analyses natural human language to derive useful
insights in order to solve problems.
• Expert Systems:
artificial intelligence Page 3
, In artificial intelligence, an expert system is a computer system that emulates the
decision-making ability of a human expert. It is a computer program that uses
artificial intelligence (AI) technologies to simulate the judgment and behavior of a
human or an organization that has expert knowledge and experience in a particular
field.
From <https://www.edureka.co/blog/artificial-intelligence-tutorial/>
• Fuzzy Logic Systems:
Fuzzy logic is an approach to computing based on “degrees of truth” rather than the
usual “true or false” (1 or 0) Boolean logic on which the modern computer is based.
Fuzzy logic Systems can take imprecise, distorted, noisy input information.
Fuzzy logic is a solution to complex problems in all fields of life, including medicine,
as it resembles human reasoning and decision making.
From <https://www.edureka.co/blog/artificial-intelligence-tutorial/>
• Natural Language Processing (NLP) refers to the Artificial Intelligence method of
communicating with intelligent systems using a natural language.
By utilizing NLP and its components, one can organize the massive chunks of text
data, perform numerous automated tasks and solve a wide range of problems such
as – Machine translation, Named Entity Recognition, Sentiment Analysis, Speech
Recognition, and Topic Segmentation etc.
From <https://www.edureka.co/blog/artificial-intelligence-tutorial/>
• Neural Networks:
Neural Networks are a class of models within the general machine learning literature.
Neural networks are a specific set of algorithms that have revolutionized machine
learning and Artificial Intelligence.
From <https://www.edureka.co/blog/artificial-intelligence-tutorial/>
artificial intelligence Page 4
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