Artificial Intelligence (INF36306)
Lecture 1 – Introduction to AI
First industrial revolution – industry 1.0
- From hand production methods to machines
- Transition from predominantly agrarian and rural society to an industrial
and urban society
Second industrial revolution – industry 2.0
- Further advancements in manufacturing and production technology
- Advent of electricity
- Mass production
- Division of labor
Third industrial revolution – industry 3.0
- Invention of the computer
- Intelligent machine that could support the human mental activities
- Development of programming languages
- Automated information processing
- Digital revolution
Fourth industrial revolution - industry 4.0
- Cyber physical systems
- Internet of things
- Networks
Artificial intelligence: intelligence demonstrated by machines, in contrast to
the natural intelligence displayed by humans
The study of intelligent agents: any device that perceives its
environment and takes actions that maximize its chance of successfully
achieving its goals
,Hype cycle
AI winters
Moore’s law: the number of transistors on a computer chip doubles about
every two years, while the costs stays the same or decreases. This leads to
computers becoming faster, smaller and more powerful over time
Artificial Narrow Intelligence (ANI)
- Also referred to as weak AI. Relates to machine intelligence that equals or
exceeds human intelligence for a particular domain
- E.g.: Chess, self-driving cars, smartphone
Artificial General Intelligence (AGI)
- Also known as strong AI
- Intelligence of a machine that has the capacity to understand or learn any
intellectual task that a human being can.
- Able to find a solution to any problem, rather than just one specific
problem
Artificial Super Intelligence (ASI)
- An intellect that is much smarter than the best human brains in practically
every field, including scientific creativity, general wisdom and social skills.
- The degree of intelligence in ASI can range from just a little smarter than a
human to one that is billions and trillions of times smarter
,The waves of computing
What is AI?
- Thinking humanly
o “The exciting new effort to make computers think … machines with
minds, in the full and literal sense.”
o “[The automation of] activities that we associate with human
thinking, activities such as decision-making, problem solving,
learning…”
- Acting humanly
o “The art of creating machines that perform functions that require
intelligence when performed by people”
o “The study of how to make computers do things at which, at the
moment, people are better.
- Thinking rationally
o “The study of mental faculties through the use of computational
models”
o “The study of the computations that make it possible to perceive,
reason and act.
- Acting rationally
o “Computational intelligence is the study of the design of intelligent
agents”
o “AI is concerned with intelligent behavior in artifacts”
Acting humanly - Turing test: was designed to provide a satisfactory
operational definition of intelligence. A computer passes the test if a human
interrogator, after posing some written questions, cannot tell whether the written
responses come from a person or from a computer.
Required capabilities
- Natural language processing: to enable it to communicate successfully
in English
, - Automated reasoning: to use the stored information to answer
questions and to draw new conclusions
- Knowledge representation: to store what it knows or hears
- Machine learning: to adapt to new circumstances and to detect and
extrapolate pattern
Total turing test
- Verbal behaviors are not the sole standard for intelligence: other behaviors
are examined too
- The candidate must be able to do, in the real world of objects and people,
everything that real people can do
- Can only be applied to a robot, or some other agent that is situated and
embodied in the physical world.
- Includes a video signal so that the interrogator can test the subject’s
perceptual abilities
- To pass the total turing test, the computer will need:
o Computer vision to perceive objects
o Robotics to manipulate objects and move about
Variations of the turing test
- The coffee test: a machine is given the task of going into an average
home and figuring out how to make coffee.
- The robot college student test: task of enrolling in a university, taking
and passing the same classes that humans would and obtaining a degree
- The employment test: the task of working an economically important
job and must perform as well or better than the level that humans perform
at in the same job
Thinking humanly – cognitive science
- How do humans think? To find out:
o Introspection: trying to catch our own thoughts as they go by
o Psychological experiments – observing a person in action
o Brain imaging – observing the brain in action
- Cognitive science: brings together computer models from AI and
experimental techniques from psychology to construct precise and testable
theories of the human mind
Thinking rationally – laws of thought
- Logicians in the 19th century developed a precise notation for statements
about all kinds of objects in the world and the relations among then
- Logicist tradition within AI hopes to build on such programs to create
intelligent systems
- Problems:
o Not easy to take informal knowledge and state it in the formal terms
required by logical notation, particularly when the knowledge is less
than 100% certain
o High demand for computational resources
Acting rationally
Lecture 1 – Introduction to AI
First industrial revolution – industry 1.0
- From hand production methods to machines
- Transition from predominantly agrarian and rural society to an industrial
and urban society
Second industrial revolution – industry 2.0
- Further advancements in manufacturing and production technology
- Advent of electricity
- Mass production
- Division of labor
Third industrial revolution – industry 3.0
- Invention of the computer
- Intelligent machine that could support the human mental activities
- Development of programming languages
- Automated information processing
- Digital revolution
Fourth industrial revolution - industry 4.0
- Cyber physical systems
- Internet of things
- Networks
Artificial intelligence: intelligence demonstrated by machines, in contrast to
the natural intelligence displayed by humans
The study of intelligent agents: any device that perceives its
environment and takes actions that maximize its chance of successfully
achieving its goals
,Hype cycle
AI winters
Moore’s law: the number of transistors on a computer chip doubles about
every two years, while the costs stays the same or decreases. This leads to
computers becoming faster, smaller and more powerful over time
Artificial Narrow Intelligence (ANI)
- Also referred to as weak AI. Relates to machine intelligence that equals or
exceeds human intelligence for a particular domain
- E.g.: Chess, self-driving cars, smartphone
Artificial General Intelligence (AGI)
- Also known as strong AI
- Intelligence of a machine that has the capacity to understand or learn any
intellectual task that a human being can.
- Able to find a solution to any problem, rather than just one specific
problem
Artificial Super Intelligence (ASI)
- An intellect that is much smarter than the best human brains in practically
every field, including scientific creativity, general wisdom and social skills.
- The degree of intelligence in ASI can range from just a little smarter than a
human to one that is billions and trillions of times smarter
,The waves of computing
What is AI?
- Thinking humanly
o “The exciting new effort to make computers think … machines with
minds, in the full and literal sense.”
o “[The automation of] activities that we associate with human
thinking, activities such as decision-making, problem solving,
learning…”
- Acting humanly
o “The art of creating machines that perform functions that require
intelligence when performed by people”
o “The study of how to make computers do things at which, at the
moment, people are better.
- Thinking rationally
o “The study of mental faculties through the use of computational
models”
o “The study of the computations that make it possible to perceive,
reason and act.
- Acting rationally
o “Computational intelligence is the study of the design of intelligent
agents”
o “AI is concerned with intelligent behavior in artifacts”
Acting humanly - Turing test: was designed to provide a satisfactory
operational definition of intelligence. A computer passes the test if a human
interrogator, after posing some written questions, cannot tell whether the written
responses come from a person or from a computer.
Required capabilities
- Natural language processing: to enable it to communicate successfully
in English
, - Automated reasoning: to use the stored information to answer
questions and to draw new conclusions
- Knowledge representation: to store what it knows or hears
- Machine learning: to adapt to new circumstances and to detect and
extrapolate pattern
Total turing test
- Verbal behaviors are not the sole standard for intelligence: other behaviors
are examined too
- The candidate must be able to do, in the real world of objects and people,
everything that real people can do
- Can only be applied to a robot, or some other agent that is situated and
embodied in the physical world.
- Includes a video signal so that the interrogator can test the subject’s
perceptual abilities
- To pass the total turing test, the computer will need:
o Computer vision to perceive objects
o Robotics to manipulate objects and move about
Variations of the turing test
- The coffee test: a machine is given the task of going into an average
home and figuring out how to make coffee.
- The robot college student test: task of enrolling in a university, taking
and passing the same classes that humans would and obtaining a degree
- The employment test: the task of working an economically important
job and must perform as well or better than the level that humans perform
at in the same job
Thinking humanly – cognitive science
- How do humans think? To find out:
o Introspection: trying to catch our own thoughts as they go by
o Psychological experiments – observing a person in action
o Brain imaging – observing the brain in action
- Cognitive science: brings together computer models from AI and
experimental techniques from psychology to construct precise and testable
theories of the human mind
Thinking rationally – laws of thought
- Logicians in the 19th century developed a precise notation for statements
about all kinds of objects in the world and the relations among then
- Logicist tradition within AI hopes to build on such programs to create
intelligent systems
- Problems:
o Not easy to take informal knowledge and state it in the formal terms
required by logical notation, particularly when the knowledge is less
than 100% certain
o High demand for computational resources
Acting rationally
