artificial intelligence

Question 1

true AI

Answer 1

• capable of consciousness
• unpredictable

Question 2

virtual AI

Answer 2

• not truly conscious
• behavior strictly governed by set of programs

Question 3

turing test

Answer 3

Computers will have achieved true artificial intelligence if a human being could not tell if he/she was talking to a computer or another
human being

Question 4

digital vs analog

Answer 4

Each neuron either fires or doesn’t (digital)
* But…signals of thousands of individual neurons create
continuous “waves” of electrical and magnetic activity (analog)

Question 5

serial vs parallel

Answer 5

• Computers calculate one thing at a time (serial)
• Brain process many different things simultaneously (parallel)

Question 6

Computable vs. Non-computable Problems

Answer 6

• computers need to follow a formula or algorithm to achieve a solution
• Brains can solve problems not reducible to an algorithm

Question 7

Deterministic vs. Non-deterministic

Answer 7

• Computer output determined by its programming
• Hard to explain human behavior as following a set of rules*

Question 8

Dynamic Self-Construction vs. Static Construction

Answer 8

• A computer cannot rebuild, rewire, or redesign itself.
• Brains can adapt and rewire itself in response to learning

Question 9

Advantages of computers over brains

Answer 9

• Speed and Repetition
• Memory Storage and Capacity
• Dimensions of calculation

Question 10

Moore’s law

Answer 10

Computing power doubles every two years
* Pattern has remained true for over 50 years

Question 11

Artificial Neural Networks (ANNs)

Answer 11

The networks are not programmed, they learn from experience

Question 12

example of neural networks

Answer 12

Netflix recommended movies and tv

Question 13

input layer

Answer 13

rods and cones of the retina
- The input layer translates the stimulus into a collection of numbers

Question 14

hidden layer 1

Answer 14

Primary receiving areas
- Patterns in the data are found by changing values based on feedback

Question 15

hidden layer 2

Answer 15

Association areas

Question 16

output

Answer 16

yes or no
- How the network responds.

Question 17

back-propagation

Answer 17

• Network adjusts based on feedback about error signal
• Changes values in the “hidden layers”

Question 18

reinforcement learning

Answer 18

The network’s “behavior” is shaped by feedback that it gets
* Correct outputs are “rewarded,” incorrect output are “punished”
(error signal)
* The process repeats until the error signal is minimized

Question 19

Generative Adversarial Networks (GANs)

Answer 19

One ANN attempts to generate a stimulus (the Generator)
* Another ANN is used to categorize whether the generator was successful

Question 20

emergence

Answer 20

When new abilities are created by the
interaction of simpler units which themselves
don’t have the ability