The design and implementation of systems that possess, reason with, and acquire knowledge is arguably the ultimate intellectual challenge. So why then, when we open almost any
book on Artificial Intelligence, does it open with a painstaking, almost defensive, definition
of what AI is and what AI is not?
This is powerpoint on" ARTIFICIAL INTELLIGENCE".
AI is a Shining field of future technology.
Artificial intelligence,Machine Learning,and Robotics is a major advance technology of coming soon" ERA".
History of AI, Current Trends, Prospective TrajectoriesGiovanni Sileno
Talk given at the 2nd Winter Academy on Artificial Intelligence and International Law of the Asser Institute. The birth of AI: Dartmouth workshop. The biggest AI waves: classic symbolic AI (reasoning, knowledge systems, problem-solving), machine learning (induction). Current problems: explainability, trustworthyness, impact and transformation on society and people, the rise of artificially dumber systems.
The design and implementation of systems that possess, reason with, and acquire knowledge is arguably the ultimate intellectual challenge. So why then, when we open almost any
book on Artificial Intelligence, does it open with a painstaking, almost defensive, definition
of what AI is and what AI is not?
This is powerpoint on" ARTIFICIAL INTELLIGENCE".
AI is a Shining field of future technology.
Artificial intelligence,Machine Learning,and Robotics is a major advance technology of coming soon" ERA".
History of AI, Current Trends, Prospective TrajectoriesGiovanni Sileno
Talk given at the 2nd Winter Academy on Artificial Intelligence and International Law of the Asser Institute. The birth of AI: Dartmouth workshop. The biggest AI waves: classic symbolic AI (reasoning, knowledge systems, problem-solving), machine learning (induction). Current problems: explainability, trustworthyness, impact and transformation on society and people, the rise of artificially dumber systems.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
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
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
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
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
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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.
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.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
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!
2. 271- Fall 2006
Robotic links
Robocup Video
Soccer Robocupf
Darpa Challenge
Darpa’s-challenge-video
http://www.darpa.mil/grandchallenge05/TechPapers/Stanford.pdf
3. 271- Fall 2006
CS171
Course home page:
http://www.ics.uci.edu/~dechter/ics-171/fall-06/
schedule, lecture notes, tutorials, assignment, grading,
office hours, etc.
Textbook: S. Russell and P. Norvig Artificial
Intelligence: A Modern Approach Prentice Hall, 2003,
Second Edition
Grading: Homeworks and projects (30-40%)
Midterm and final (60-70%)
4. 271- Fall 2006
Course overview
Introduction and Agents (chapters 1,2)
Search (chapters 3,4)
Games (chapter 5)
Constraints processing (chapter 6)
Representation and Reasoning with Logic
(chapters 7,8,9)
Learning (chapters 18,20)
Planning (chapter 11)
Uncertainty (chapters 13,14)
Natural Language Processing (chapter 22,23)
5. 271- Fall 2006
Course Outline
Resources on the Internet
AI on the Web: A very comprehensive list of
Web resources about AI from the Russell and
Norvig textbook.
Essays and Papers
What is AI, John McCarthy
Computing Machinery and Intelligence, A.M.
Turing
Rethinking Artificial Intelligence, Patrick
H.Winston
6. 271- Fall 2006
Today’s class
What is Artificial Intelligence?
A brief History
Intelligent agents
State of the art
7. 271- Fall 2006
What is Artificial Intelligence
(John McCarthy , Basic Questions)
What is artificial intelligence?
It is the science and engineering of making intelligent machines, especially
intelligent computer programs. It is related to the similar task of using
computers to understand human intelligence, but AI does not have to confine
itself to methods that are biologically observable.
Yes, but what is intelligence?
Intelligence is the computational part of the ability to achieve goals in the
world. Varying kinds and degrees of intelligence occur in people, many
animals and some machines.
Isn't there a solid definition of intelligence that doesn't depend on
relating it to human intelligence?
Not yet. The problem is that we cannot yet characterize in general what kinds
of computational procedures we want to call intelligent. We understand some
of the mechanisms of intelligence and not others.
More in: http://www-formal.stanford.edu/jmc/whatisai/node1.html
8. 271- Fall 2006
What is AI?
Views of AI fall into four categories:
Thinking humanly Thinking rationally
Acting humanly Acting rationally
The textbook advocates "acting rationally“
List of AI-topics
9. 271- Fall 2006
What is Artificial
Intelligence?
Human-like (“How to simulate humans intellect and
behavior on by a machine.)
Mathematical problems (puzzles, games, theorems)
Common-sense reasoning (if there is parking-space,
probably illegal to park)
Expert knowledge: lawyers, medicine, diagnosis
Social behavior
Rational-like:
achieve goals, have performance measure
10. 271- Fall 2006
What is Artificial
Intelligence
Thought processes
“The exciting new effort to make computers
think .. Machines with minds, in the full and
literal sense” (Haugeland, 1985)
Behavior
“The study of how to make computers do
things at which, at the moment, people are
better.” (Rich, and Knight, 1991)
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The Turing Test
(Can Machine think? A. M. Turing, 1950)
Requires
Natural language
Knowledge representation
Automated reasoning
Machine learning
(vision, robotics) for full test
12. 271- Fall 2006
What is AI?
Turing test (1950)
Requires:
Natural language
Knowledge representation
automated reasoning
machine learning
(vision, robotics.) for full test
Thinking humanly:
Introspection, the general problem solver (Newell and
Simon 1961)
Cognitive sciences
Thinking rationally:
Logic
Problems: how to represent and reason in a domain
Acting rationally:
Agents: Perceive and act
13. 271- Fall 2006
AI examples
Common sense reasoning
Tweety
Yale Shooting problem
Update vs revise knowledge
The OR gate example: A or B - C
Observe C=0, vs Do C=0
Chaining theories of actions
Looks-like(P) is(P)
Make-looks-like(P) Looks-like(P)
----------------------------------------
Makes-looks-like(P) ---is(P) ???
Garage-door example: garage door not included.
Planning benchmarks
8-puzzle, 8-queen, block world, grid-space world
Abduction: cambridge parking example
14. 271- Fall 2006
History of AI
McCulloch and Pitts (1943)
Neural networks that learn
Minsky (1951)
Built a neural net computer
Darmouth conference (1956):
McCarthy, Minsky, Newell, Simon met,
Logic theorist (LT)- proves a theorem in Principia
Mathematica-Russel.
The name “Artficial Intelligence” was coined.
1952-1969
GPS- Newell and Simon
Geometry theorem prover - Gelernter (1959)
Samuel Checkers that learns (1952)
McCarthy - Lisp (1958), Advice Taker, Robinson’s
resolution
Microworlds: Integration, block-worlds.
1962- the perceptron convergence (Rosenblatt)
15. 271- Fall 2006
The Birthplace of
“Artificial Intelligence”, 1956
Darmouth workshop, 1956: historical meeting of the precieved
founders of AI met: John McCarthy, Marvin Minsky, Alan
Newell, and Herbert Simon.
A Proposal for the Dartmouth Summer Research Project on
Artificial Intelligence. J. McCarthy, M. L. Minsky, N.
Rochester, and C.E. Shannon. August 31, 1955. "We propose
that a 2 month, 10 man study of artificial intelligence be
carried out during the summer of 1956 at Dartmouth College
in Hanover, New Hampshire. The study is to proceed on the
basis of the conjecture that every aspect of learning or any
other feature of intelligence can in principle be so precisely
described that a machine can be made to simulate it." And this
marks the debut of the term "artificial intelligence.“
50 anniversery of Darmouth workshop
16. 271- Fall 2006
History, continued
1966-1974 a dose of reality
Problems with computation
1969-1979 Knowledge-based systems
Weak vs. strong methods
Expert systems:
• Dendral:Inferring molecular structures
• Mycin: diagnosing blood infections
• Prospector: recomending exploratory drilling (Duda).
Roger Shank: no syntax only semantics
1980-1988: AI becomes an industry
R1: Mcdermott, 1982, order configurations of computer
systems
1981: Fifth generation
1986-present: return to neural networks
Recent event:
AI becomes a science: HMMs, planning, belief network
17. 271- Fall 2006
Abridged history of AI
1943 McCulloch & Pitts: Boolean circuit model of brain
1950 Turing's "Computing Machinery and Intelligence"
1956 Dartmouth meeting: "Artificial Intelligence" adopted
1952—69 Look, Ma, no hands!
1950s Early AI programs, including Samuel's checkers
program, Newell & Simon's Logic Theorist,
Gelernter's Geometry Engine
1965 Robinson's complete algorithm for logical reasoning
1966—73 AI discovers computational complexity
Neural network research almost disappears
1969—79 Early development of knowledge-based systems
1980-- AI becomes an industry
1986-- Neural networks return to popularity
1987-- AI becomes a science
1995-- The emergence of intelligent agents
18. 271- Fall 2006
State of the art
Deep Blue defeated the reigning world chess
champion Garry Kasparov in 1997
Proved a mathematical conjecture (Robbins
conjecture) unsolved for decades
No hands across America (driving autonomously 98%
of the time from Pittsburgh to San Diego)
During the 1991 Gulf War, US forces deployed an AI
logistics planning and scheduling program that
involved up to 50,000 vehicles, cargo, and people
NASA's on-board autonomous planning program
controlled the scheduling of operations for a spacecraft
Proverb solves crossword puzzles better than most
humans
DARPA grand challenge 2003-2005, Robocup
19. 271- Fall 2006
Robotic links
Robocup Video
Soccer Robocupf
Darpa Challenge
Darpa’s-challenge-video
21. 271- Fall 2006
Agents
An agent is anything that can be viewed as
perceiving its environment through sensors
and acting upon that environment through
actuators
Human agent: eyes, ears, and other organs
for sensors; hands,
legs, mouth, and other body parts for
actuators
Robotic agent: cameras and infrared range
finders for sensors;
22. 271- Fall 2006
Agents and environments
The agent function maps from percept
histories to actions:
[f: P* A]
The agent program runs on the physical
architecture to produce f
23. 271- Fall 2006
Vacuum-cleaner world
Percepts: location and contents, e.g.,
[A,Dirty]
Actions: Left, Right, Suck, NoOp
24. 271- Fall 2006
Rational agents
An agent should strive to "do the right
thing", based on what it can perceive and
the actions it can perform. The right action
is the one that will cause the agent to be
most successful
Performance measure: An objective
criterion for success of an agent's behavior
E.g., performance measure of a vacuum-
cleaner agent could be amount of dirt
cleaned up, amount of time taken, amount
of electricity consumed, amount of noise
25. 271- Fall 2006
Rational agents
Rational Agent: For each possible
percept sequence, a rational agent
should select an action that is
expected to maximize its performance
measure, given the evidence provided
by the percept sequence and
whatever built-in knowledge the agent
has.
26. 271- Fall 2006
What’s involved in Intelligence?
Intelligent agents
Ability to interact with the real world
to perceive, understand, and act
e.g., speech recognition and understanding and
synthesis
e.g., image understanding
e.g., ability to take actions, have an effect
Knowledge Representation, Reasoning and
Planning
modeling the external world, given input
solving new problems, planning and making decisions
ability to deal with unexpected problems, uncertainties
Learning and Adaptation
we are continuously learning and adapting
our internal models are always being “updated”
• e.g. a baby learning to categorize and recognize
animals
27. 271- Fall 2006
Implementing agents
Table look-ups
Autonomy
All actions are completely specified
no need in sensing, no autonomy
example: Monkey and the banana
Structure of an agent
agent = architecture + program
Agent types
• medical diagnosis
• Satellite image analysis system
• part-picking robot
• Interactive English tutor
• cooking agent
• taxi driver
40. 271- Fall 2006
Agent types
Example: Taxi driver
Simple reflex
If car-in-front-is-breaking then initiate-breaking
Agents that keep track of the world
If car-in-front-is-breaking and on fwy then initiate-
breaking
needs internal state
goal-based
If car-in-front-is-breaking and needs to get to hospital
then go to adjacent lane and plan
search and planning
utility-based
If car-in-front-is-breaking and on fwy and needs to
get to hospital alive then search of a way to get to the
hospital that will make your passengers happy.
Needs utility function that map a state to a real
function (am I happy?)
41. 271- Fall 2006
Summary
What is Artificial Intelligence?
modeling humans thinking, acting, should think,
should act.
History of AI
Intelligent agents
We want to build agents that act rationally
Real-World Applications of AI
AI is alive and well in various “every day” applications
• many products, systems, have AI components
Assigned Reading
Chapters 1 and 2 in the text R&N