Session 1: What are the big AI questions
1. Can we build machines that think?
2. Can we build machines that learn?
3. Can we build machines that are
... [Show More] more intelligent than us?
4. Can we build machines that are creative?
5. Can we build machines that have emotions?
6. Can we build machines that are conscious?
Session 1: What is AI?
Artificial: Computational agents, either robotic or software.
Intelligence: Agents capable of achieving goals in the world.
"the science of making machines do things that would require intelligence if done by men"
Brainpower
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Session 1: What are the goals of AI?
Strong AI vs Weak AI
General AI vs Narrow AI
Science AI vs Enginereeing AI
Session 1: What is Strong AI
The goal is to understand the human
mind/brain as a computational device.
Specific in the sense that we are
focused on the human mind/brain.
General in the sense that humans can solve an astonishingly wide range of problems.
can construct machinery capable of
thought, emotions, and any other
quality we attribute to humans.
Session 1: What is Weak AI
The goal is to develop intelligent
machinery that is not necessarily like
us, but nevertheless solves some
problem.
Specific in the sense that a single,
isolated problem is usually considered.
General in the sense that any kind of
problems/techniques might be
entertained.
We are interested in machines that
solve tricky problems in ways perhaps
not found in nature, independent of
whether "strong AI" is possible
Session 1: What is general AI
Real progress is likely to come from
viewing intelligent systems as whole.
Set human level performance as the
goal, and abandon efforts incapable of
reaching this goal.
Seek early integration of AI's
subfields.
Session 1: What is narrow AI
Real progress is likely to come from
breaking the big problems down, and
tackling smaller problems.
Seek incremental improvements.
Rome wasn't built in a day.
Let each subfield solve it's own
problem first.
Session 1: What is Science AI
Reverse-engineer the mind/brain.
The object of interest exists in nature.
Investigate the hypothesis that
humans are machines.
AI as a science could fail.
Session 1: What is Engineering AI
Engineer clever machines.
The objects of interest are unknown,
and are to be discovered/created.
Independent of human nature, can we
construct clever machines?
AI as engineering Has already
succeeded.
Session 1: What examples illustrate the
diversity of AI? in goals of AI.
Session 2: What is the origin of computers
The workers carrying out these calculations were called "computers".
De Prony lead this huge effort.
Session 2: What did Alan Turing contribute to cognition and computation
Alan Turing asked the question "Can
machines think?" rather than "Is the
mind a computer?
I Turing considered the similarity "very
superficial".
Session 2: When did the first programmable computers
arrive?
ww2 1939
Session 2: What did Newell and Simon
hypothesize and what was it called?
The physical symbol system hypothesis:
a physical symbol system has
the necessary and sufficient means for
general intelligent action.
Session 2: How did Newell and Simon
view computers?
as symbol manipulators
Session 2: Who was the person that said to replace people with a machine as computers?
1812 Charles Babbage
Session 2: Who was the one to notice the resemblance between mind/brain in computation and cognition
Alan turing
Session 2: What is computation?
Defining it is arguably impossible
There are different models of universal computation
Session 2: What does computation rely on?
The Turing machine
Session 2: What is Computational
intractability?
Session 2: What are computational Intractable problems?
are those that demand infeasible resources to solve. Key resources are time ( the solution takes too long to compute) and space (the solution required too much memory).
the time required to solve instances of the problem grows exponentially with the size of the instances.
Session 2: What are computational Uncomputable problems?
problems that cannot be solved by any computer. Some problems are provable uncomputable.
Session 2: What are the limits of computation?
Computability and intractability.
Session 2: What kind of problems are computationally intractable?
problems that require superpolynomial time to solve
Session 2: How do humans deal with computationally intractable problems?
On the Traveling salesperson problem, very well.
Session 2: What do we mean by computational tractability?
Session 2: Do humans struggle with intractable problems?
Session 3: What is Turing's proposal
to replace the question with the imitation game
Session 3: What question did Turing want to address?
"Can machines think?"
Session 3: What is the problem with what Turing wants to address?
the terms "machine" and "think" are too vague [Show Less]