Describe what is Artificial Intelligence. What are its goals and Approaches. Different Types of Artificial Intelligence Explain Machine learning and took one Algorithm "K-means Algorithm" and explained
Describe what is Artificial Intelligence. What are its goals and Approaches. Different Types of Artificial Intelligence Explain Machine learning and took one Algorithm "K-means Algorithm" and explained
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
2. Course Learning Outcomes
At the end of this course:
Knowledge and understanding
You should have a knowledge and understanding of the basic
concepts of Artificial Intelligence including Search, Game Playing,
KBS (including Uncertainty), Planning and Machine Learning.
Intellectual skills
You should be able to use this knowledge and understanding of
appropriate principles and guidelines to synthesise solutions to
tasks in AI and to critically evaluate alternatives.
Practical skills
You should be able to use a well known declarative language
(Prolog) and to construct simple AI systems.
Transferable Skills
You should be able to solve problems and evaluate outcomes and
alternatives
3. Attendance
You are expected to attend all the lectures. The lecture notes (see below)
cover all the topics in the course, but these notes are concise, and do
not contain much in the way of discussion, motivation or examples.
The lectures will consist of slides (Powerpoint ), spoken material, and
additional examples given on the blackboard. In order to understand the
subject and the reasons for studying the material, you will need to
attend the lectures and take notes to supplement lecture slides. This is
your responsibility. If there is anything you do not understand during the
lectures, then ask, either during or after the lecture. If the lectures are
covering the material too quickly, then say so. If there is anything you do
not understand in the slides, then ask.
In addition you are expected to supplement the lecture material by reading
around the subject; particularly the course text.
Must use text book and references.
4. Areas of AI and Some Dependencies
Search
Vision
Planning
Machine
Learning
Knowledge
Representation
Logic
Expert
Systems
Robotics
NLP
5. What is Artificial Intelligence ?
making computers that think?
the automation of activities we associate with human
thinking, like decision making, learning ... ?
the art of creating machines that perform functions that
require intelligence when performed by people ?
the study of mental faculties through the use of
computational models ?
6. What is Artificial Intelligence ?
the study of computations that make it possible to
perceive, reason and act ?
a field of study that seeks to explain and emulate
intelligent behaviour in terms of computational
processes ?
a branch of computer science that is concerned with
the automation of intelligent behaviour ?
anything in Computing Science that we don't yet know
how to do properly ? (!)
7. What is Artificial Intelligence ?
Systems that act
rationally
Systems that think
like humans
Systems that think
rationally
Systems that act
like humans
THOUGHT
BEHAVIOUR
HUMAN RATIONAL
8. Systems that act like humans:
Turing Test
“The art of creating machines that perform
functions that require intelligence when
performed by people.” (Kurzweil)
“The study of how to make computers do things
at which, at the moment, people are better.” (Rich
and Knight)
9. Systems that act like humans
You enter a room which has a computer
terminal. You have a fixed period of time to
type what you want into the terminal, and
study the replies. At the other end of the line
is either a human being or a computer
system.
If it is a computer system, and at the end of
the period you cannot reliably determine
whether it is a system or a human, then the
system is deemed to be intelligent.
?
10. Systems that act like humans
The Turing Test approach
a human questioner cannot tell if
there is a computer or a human answering his question, via
teletype (remote communication)
The computer must behave intelligently
Intelligent behavior
to achieve human-level performance in all cognitive
tasks
11. Systems that act like humans
These cognitive tasks include:
Natural language processing
for communication with human
Knowledge representation
to store information effectively & efficiently
Automated reasoning
to retrieve & answer questions using the stored information
Machine learning
to adapt to new circumstances
12. The total Turing Test
Includes two more issues:
Computer vision
to perceive objects (seeing)
Robotics
to move objects (acting)
13. What is Artificial Intelligence ?
Systems that act
rationally
Systems that think
like humans
Systems that think
rationally
Systems that act
like humans
THOUGHT
BEHAVIOUR
HUMAN RATIONAL
14. Systems that think like humans:
cognitive modeling
Humans as observed from ‘inside’
How do we know how humans think?
Introspection vs. psychological experiments
Cognitive Science
“The exciting new effort to make computers
think … machines with minds in the full and
literal sense” (Haugeland)
“[The automation of] activities that we
associate with human thinking, activities such
as decision-making, problem solving, learning
…” (Bellman)
15. What is Artificial Intelligence ?
Systems that act
rationally
Systems that think
like humans
Systems that think
rationally
Systems that act
like humans
THOUGHT
BEHAVIOUR
HUMAN RATIONAL
16. Systems that think ‘rationally’
"laws of thought"
Humans are not always ‘rational’
Rational - defined in terms of logic?
Logic can’t express everything (e.g.
uncertainty)
Logical approach is often not feasible in terms
of computation time (needs ‘guidance’)
“The study of mental facilities through the use
of computational models” (Charniak and
McDermott)
“The study of the computations that make it
possible to perceive, reason, and act”
(Winston)
17. What is Artificial Intelligence ?
Systems that act
rationally
Systems that think
like humans
Systems that think
rationally
Systems that act
like humans
THOUGHT
BEHAVIOUR
HUMAN RATIONAL
18. Systems that act rationally:
“Rational agent”
Rational behavior: doing the right thing
The right thing: that which is expected to
maximize goal achievement, given the available
information
Giving answers to questions is ‘acting’.
I don't care whether a system:
replicates human thought processes
makes the same decisions as humans
uses purely logical reasoning
19. Systems that act rationally
Logic only part of a rational agent, not all of
rationality
Sometimes logic cannot reason a correct
conclusion
At that time, some specific (in domain) human
knowledge or information is used
Thus, it covers more generally different
situations of problems
Compensate the incorrectly reasoned conclusion
20. Systems that act rationally
Study AI as rational agent –
2 advantages:
It is more general than using logic only
Because: LOGIC + Domain knowledge
It allows extension of the approach with more
scientific methodologies
21. Rational agents
An agent is an entity that perceives and acts
This course is about designing rational agents
Abstractly, an agent is a function from percept
histories to actions:
[f: P* A]
For any given class of environments and tasks, we
seek the agent (or class of agents) with the best
performance
Caveat: computational limitations make perfect
rationality unachievable
design best program for given machine resources
22. Artificial
Produced by human art or effort, rather than
originating naturally.
Intelligence
is the ability to acquire knowledge and use it"
[Pigford and Baur]
So AI was defined as:
AI is the study of ideas that enable computers to be
intelligent.
AI is the part of computer science concerned with
design of computer systems that exhibit human
intelligence(From the Concise Oxford Dictionary)
23. From the above two definitions, we can see that AI
has two major roles:
Study the intelligent part concerned with humans.
Represent those actions using computers.
24. Goals of AI
To make computers more useful by letting them
take over dangerous or tedious tasks from human
Understand principles of human intelligence
25. The Foundation of AI
Philosophy
At that time, the study of human intelligence began
with no formal expression
Initiate the idea of mind as a machine and its
internal operations
26. The Foundation of AI
Mathematics formalizes the three main area of AI:
computation, logic, and probability
Computation leads to analysis of the problems that
can be computed
complexity theory
Probability contributes the “degree of belief” to
handle uncertainty in AI
Decision theory combines probability theory and
utility theory (bias)
27. The Foundation of AI
Psychology
How do humans think and act?
The study of human reasoning and acting
Provides reasoning models for AI
Strengthen the ideas
humans and other animals can be considered as
information processing machines
28. The Foundation of AI
Computer Engineering
How to build an efficient computer?
Provides the artifact that makes AI application
possible
The power of computer makes computation of large
and difficult problems more easily
AI has also contributed its own work to computer
science, including: time-sharing, the linked list data
type, OOP, etc.
29. The Foundation of AI
Control theory and Cybernetics
How can artifacts operate under their own control?
The artifacts adjust their actions
To do better for the environment over time
Based on an objective function and feedback from the
environment
Not limited only to linear systems but also other
problems
as language, vision, and planning, etc.
30. The Foundation of AI
Linguistics
For understanding natural languages
different approaches has been adopted from the linguistic
work
Formal languages
Syntactic and semantic analysis
Knowledge representation
31. The main topics in AI
Artificial intelligence can be considered under a number
of headings:
Search (includes Game Playing).
Representing Knowledge and Reasoning with it.
Planning.
Learning.
Natural language processing.
Expert Systems.
Interacting with the Environment
(e.g. Vision, Speech recognition, Robotics)
We won’t have time in this course to consider all of these.
32. more powerful and more useful computers
new and improved interfaces
solving new problems
better handling of information
relieves information overload
conversion of information into knowledge
Some Advantages of Artificial
Intelligence
33. The Disadvantages
increased costs
difficulty with software development - slow and
expensive
few experienced programmers
few practical products have reached the market as
yet.
34. Search
Search is the fundamental technique of AI.
Possible answers, decisions or courses of action are structured
into an abstract space, which we then search.
Search is either "blind" or “uninformed":
blind
we move through the space without worrying about what is
coming next, but recognising the answer if we see it
informed
we guess what is ahead, and use that information to decide
where to look next.
We may want to search for the first answer that satisfies our goal, or
we may want to keep searching until we find the best answer.
35. Knowledge Representation & Reasoning
The second most important concept in AI
If we are going to act rationally in our environment, then we must
have some way of describing that environment and drawing
inferences from that representation.
how do we describe what we know about the world ?
how do we describe it concisely ?
how do we describe it so that we can get hold of the right piece of
knowledge when we need it ?
how do we generate new pieces of knowledge ?
how do we deal with uncertain knowledge ?
36. Knowledge
Declarative Procedural
• Declarative knowledge deals with factoid questions
(what is the capital of India? Etc.)
• Procedural knowledge deals with “How”
• Procedural knowledge can be embedded in
declarative knowledge
37. Planning
Given a set of goals, construct a sequence of actions that
achieves those goals:
often very large search space
but most parts of the world are independent of most other
parts
often start with goals and connect them to actions
no necessary connection between order of planning and order
of execution
what happens if the world changes as we execute the plan
and/or our actions don’t produce the expected results?
38. Learning
If a system is going to act truly appropriately, then it
must be able to change its actions in the light of
experience:
how do we generate new facts from old ?
how do we generate new concepts ?
how do we learn to distinguish different
situations in new environments ?
39. Interacting with the Environment
In order to enable intelligent behaviour, we will
have to interact with our environment.
Properly intelligent systems may be expected
to:
accept sensory input
vision, sound, …
interact with humans
understand language, recognise
speech,
generate text, speech and graphics,
…
modify the environment
40. History of AI
AI has a long history
Ancient Greece
Aristotle
Historical Figures Contributed
Ramon Lull
Al Khowarazmi
Leonardo da Vinci
David Hume
George Boole
Charles Babbage
John von Neuman
As old as electronic computers themselves (c1940)
42. History of AI
Origins
The Dartmouth conference: 1956
John McCarthy (Stanford)
Marvin Minsky (MIT)
Herbert Simon (CMU)
Allen Newell (CMU)
Arthur Samuel (IBM)
The Turing Test (1950)
“Machines who Think”
By Pamela McCorckindale
43. Periods in AI
Early period - 1950’s & 60’s
Game playing
brute force (calculate your way out)
Theorem proving
symbol manipulation
Biological models
neural nets
Symbolic application period - 70’s
Early expert systems, use of knowledge
Commercial period - 80’s
boom in knowledge/ rule bases
44. Periods in AI cont’d
? period - 90’s and New Millenium
Real-world applications, modelling, better
evidence, use of theory, ......?
Topics: data mining, formal models, GA’s, fuzzy
logic, agents, neural nets, autonomous systems
Applications
visual recognition of traffic
medical diagnosis
directory enquiries
power plant control
automatic cars
45. Fashions in AI
Progress goes in stages, following funding booms and crises: Some examples:
1. Machine translation of languages
1950’s to 1966 - Syntactic translators
1966 - all US funding cancelled
1980 - commercial translators available
2. Neural Networks
1943 - first AI work by McCulloch & Pitts
1950’s & 60’s - Minsky’s book on “Perceptrons” stops nearly all work on nets
1986 - rediscovery of solutions leads to massive growth in neural nets research
The UK had its own funding freeze in 1973 when the Lighthill report reduced AI work
severely -Lesson: Don’t claim too much for your discipline!!!!
Look for similar stop/go effects in fields like genetic algorithms and evolutionary
computing. This is a very active modern area dating back to the work of Friedberg in
1958.
46. Symbolic and Sub-symbolic AI
Symbolic AI is concerned with describing and
manipulating our knowledge of the world as explicit
symbols, where these symbols have clear
relationships to entities in the real world.
Sub-symbolic AI (e.g. neural-nets) is more concerned
with obtaining the correct response to an input
stimulus without ‘looking inside the box’ to see if parts
of the mechanism can be associated with discrete
real world objects.
This course is concerned with symbolic AI.
57. AI Applications
Other application areas:
Bioinformatics:
Gene expression data analysis
Prediction of protein structure
Text classification, document sorting:
Web pages, e-mails
Articles in the news
Video, image classification
Music composition, picture drawing
Natural Language Processing .
Perception.