… to machines that think

ABOUT THIS GRAPHIC STORY

Section 1 of this story looks at Simple Machines — see https://ai-ed.ca/simple-machines

Section 2 (see below) looks at Machines that “Think”.

Get the PDF.


MACHINES THAT THINK

MENU

Let’s learn about machines that think:

  1. Can machines think
  2. Learning like a baby
  3. What do machines see?
  4. Reinforcement learning
  5. Supervised learning
  6. Unsupervised learning
  7. Machine + personality?

PAGE 17 – can machines think?

REFLECT

  • What does it mean to think? Give an example.
  • What does it mean to learn? Give an example.

Thinking and learning are intertwined.

Let’s take a closer look at how machines learn …


PAGE 18 – learning like a baby


PAGE 19 – more learning like a baby


REFLECT

Do you learn from playing?

What do you learn from playing?

  • Give an example of a playing situation, and describe what you learned.

PAGE 20 – learning from surprises


REFLECT

Do you learn from playing?

What do you learn from playing?

  • Give an example of a playing situation, and describe what you learned.

PAGE 21 – learning from play


REFLECT

View the video of the iCub robot learning by interacting with its environment.

  • What is interesting?
  • What is surprising?
  • What questions do you have?

PAGE 22 – what do thinking machines see?


ABSTRACT MACHINES

Automata do not have to be physical. They can be abstract.

Like a diagram of how a mechanism works.

Example: Let’s build abstract automata of how turnstiles and vending machines work.

  • Abstract automata help describe, analyze, and understand discrete systems, like computers.
  • The inputs and outputs of discrete systems are either ON or OFF (1 or 0).
  • Abstract automata are used in the development of computational theory.

Extend: Work with a partner to create the abstract automaton for a vending machine where snacks cost 25 cents


PAGE 23 – machine learning through reinforcement


PAGE 24 – human learning through reinforcement


PAGE 25 – supervised machine learning


PAGE 26 – supervised human learning


PAGE 27 – unsupervised learning


PAGE 28 – more about unsupervised learning


PAGE 29 – does a thinking machine have a personality?


REFLECT

What did you learn about machines that learn?

What else do you want to know?