Intro to AI 1 Summary
Lesson 1
1. What is AI?
Definition of Artificial Intelligence
- Artificial = non-biological (material) / constructed by humans (origin) computational
agents, either robotic or software
- Intelligence = computational part of the ability (in AI sense) agents capable of
achieving goals in the world
Think Act (behaviour)
Humanly Rationally (Ideal performance)
1. Acting humanly Turing Test
NLP, knowledge representation, automated reasoning, ML, computer vision, robotics
Study underlying principles > duplicate
2. Thinking humanly cognitive modeling
Introspection, psychological experiments, brain imaging
Sufficiently precise theory express it as computer program
3. Thinking rationally laws of thought approach
Based on logic, inference
Difficulties: putting informal knowledge that’s not 100% correct into formal terms,
solving in principle vs solving in practice
4. Acting rationally rational agent approach
More general, more amendable to scientific development
Carbon chauvinism
- Must real intelligence be made from biological stuff?
- The assumption that the chemical processes of hypothetical extraterrestrial life must be
constructed primarily from carbon (organic compounds) because carbon's chemical and
thermodynamic properties render it far superior to all other elements
Big AI questions
- Think, learn, intelligent, creative, emotions, conscious
- Is there a limit of machine?
2. What is the goal of AI?
The Dartmouth Summer Research Project on Artificial Intelligence (1956)
- “Every aspect of learning or any other feature of intelligence can in principle be so
precisely defined that a machine can be made to simulate it" (Thinking humanly)
Strong AI vs Weak AI
- Understand human mind as computational device
- Machines that solve some problems
, AI as science vs AI as Engineering
- Humans as machines, reverse engineering of mind/brain, study of nature, can fail
- Construct clever machines, independent of human nature, already succeeded
Artificial General Intelligence vs Narrow AI
- Intelligent systems as a whole vs breaking the big problems down and tackling smaller
problems
3. What does AI as a field of research look like?
AI as part of cognitive sciences
- Collaborative/interdisciplinary field
- Insights from multiple different disciplines are needed to inform the study of cognition
mutually beneficial
- Cognitivism = understand brain processes as computational systems manipulating
representations
Fragmentation of AI Research
- Most AI researches don’t tackle the big AI questions directly
Lesson 2
1. Why is thought/mental activity computational?
1. Mental activity is the act of calculation (Leibniz).
2. Creative, inspired human thought was beyond mere calculation (Romantacism).
3. Employ people to perform calculations, call them computers (De Prony).
4. Replace these people with a machine, call it a computer (Babbage).
5. Devise programmable computers (WW2).
6. Notice how computers resemble the mind/brain (Turing).
7. Hypothesize that cognition is symbol manipulation, we are members of a broader class (Newell
and Simon).
8. Mental activity is the act of computation.
Cognitive revolution
- Started by Newell and Simon’s crucial realization
- Computers as symbol manipulators more than calculation, more general purposes
- Mental chemistry with symbols as atoms
The physical symbol system hypothesis
- The ability to manipulate symbols is necessary and sufficient for intelligent action
Lesson 1
1. What is AI?
Definition of Artificial Intelligence
- Artificial = non-biological (material) / constructed by humans (origin) computational
agents, either robotic or software
- Intelligence = computational part of the ability (in AI sense) agents capable of
achieving goals in the world
Think Act (behaviour)
Humanly Rationally (Ideal performance)
1. Acting humanly Turing Test
NLP, knowledge representation, automated reasoning, ML, computer vision, robotics
Study underlying principles > duplicate
2. Thinking humanly cognitive modeling
Introspection, psychological experiments, brain imaging
Sufficiently precise theory express it as computer program
3. Thinking rationally laws of thought approach
Based on logic, inference
Difficulties: putting informal knowledge that’s not 100% correct into formal terms,
solving in principle vs solving in practice
4. Acting rationally rational agent approach
More general, more amendable to scientific development
Carbon chauvinism
- Must real intelligence be made from biological stuff?
- The assumption that the chemical processes of hypothetical extraterrestrial life must be
constructed primarily from carbon (organic compounds) because carbon's chemical and
thermodynamic properties render it far superior to all other elements
Big AI questions
- Think, learn, intelligent, creative, emotions, conscious
- Is there a limit of machine?
2. What is the goal of AI?
The Dartmouth Summer Research Project on Artificial Intelligence (1956)
- “Every aspect of learning or any other feature of intelligence can in principle be so
precisely defined that a machine can be made to simulate it" (Thinking humanly)
Strong AI vs Weak AI
- Understand human mind as computational device
- Machines that solve some problems
, AI as science vs AI as Engineering
- Humans as machines, reverse engineering of mind/brain, study of nature, can fail
- Construct clever machines, independent of human nature, already succeeded
Artificial General Intelligence vs Narrow AI
- Intelligent systems as a whole vs breaking the big problems down and tackling smaller
problems
3. What does AI as a field of research look like?
AI as part of cognitive sciences
- Collaborative/interdisciplinary field
- Insights from multiple different disciplines are needed to inform the study of cognition
mutually beneficial
- Cognitivism = understand brain processes as computational systems manipulating
representations
Fragmentation of AI Research
- Most AI researches don’t tackle the big AI questions directly
Lesson 2
1. Why is thought/mental activity computational?
1. Mental activity is the act of calculation (Leibniz).
2. Creative, inspired human thought was beyond mere calculation (Romantacism).
3. Employ people to perform calculations, call them computers (De Prony).
4. Replace these people with a machine, call it a computer (Babbage).
5. Devise programmable computers (WW2).
6. Notice how computers resemble the mind/brain (Turing).
7. Hypothesize that cognition is symbol manipulation, we are members of a broader class (Newell
and Simon).
8. Mental activity is the act of computation.
Cognitive revolution
- Started by Newell and Simon’s crucial realization
- Computers as symbol manipulators more than calculation, more general purposes
- Mental chemistry with symbols as atoms
The physical symbol system hypothesis
- The ability to manipulate symbols is necessary and sufficient for intelligent action
