Problem 1

Question 1

When is machine learning most useful ?

Answer 1

Environments with a high degree of complexity

–> because we live in a world where the amount of complexity increases exponentially

Question 2

Why is machine learning so helpful and useful ?

Answer 2

Its accuracy in Prediction, meaning anticipating what will happen in the future

–> take info one has to generate info one previously didnt have

Question 3

Judgment

Answer 3

Refers to the ability to make considered decisions

–> understanding the impact different actions will have on outcomes in light of predictions

Question 4

Why is machine learning so efficient and often times more efficient than human learning ?

Answer 4

Because it

a) analyzes thousands of human-to-human actions
b) incorporates the feedback on actions + outcomes to develop a more accurate prediction + new strategies

Question 5

Cognitive science

Answer 5

Refers to the study of the mind + its processes

–> one studies intelligence + behavior, focusing on how NS represent, process + transform info

Question 6

The mind cannot be understood if it is only studied at a single level.

Name its 3 levels of analysis.

Answer 6

1. Computational level
2. Representational + alghorithmic level
3. Hardware implementation level (Physical level)

Question 7

Computational level

Answer 7

Specifies the goals of a process + the logic behind the manner with which it is executed

e.g.: What does the system do ?

Question 8

Representational + algorithmic level

Answer 8

Adresses how the process can be executed

e.g.: what steps does the system go through

Question 9

Hardware implementation level

Answer 9

Adresses how algorithm + representation may be physically realized

e.g.: In what ways are the steps the system goes through implemented

Question 10

Name a few of the different methods that are used to study cognitive science.

Answer 10

1. Behavioral experiments
2. Brain imaging
3. Computitonal modeling
   - -> mathematically formal representation of the problem

Question 11

Artifical intelligence 
(AI)

Answer 11

Refers to technology designed to perform activities that normally require human intelligence

–> emulates complex human behavior that is capable of

a) reasoning
b) learning
c) acting upon an environment autonomously

Question 12

Turing test

Answer 12

Refers to a method for judging the intelligence of machines

–> to pass it, a computer program must impersonate a human real-time written conversation sufficiently enough, so the judge can’t reliably tell whether it was a human or machine that wrote it

Question 13

Name the most important branches of AI.

Answer 13

1. Machine learning
2. Natural language processing
   - -> how computers process human natural languages

Question 14

Algorithms

Answer 14

Refer to sets of unambiguous instructions that a mechanical computer can execute

–> capable of learning from data as they can better themselves by learning new strategies that worked in the past

Question 15

There are 4 approaches to AI.

Name them.

Answer 15

1. Symbolism
   - -> formal logic
2. Bayesian inference
   - -> Bayes theory is used
3. Nearest neighbor
4. Artificial networks

Question 16

How has psychology contributed to the fields of AI ?

Answer 16

Hebbs theory for how neurons learn through the strengthening of connections between them formed the basis for “Mark 1 perceptron”

–> first mashing that learn on its own

Question 17

What is the aim of Cognitive science ?

Answer 17

1. To describe different kinds of problem solving and learning
2. Learning how the mind carries out these operations

Question 18

Computational representational understating of the mind

CRUM

Answer 18

Suggests that thinking results from the representational structures in the mind + computational procedures that operate on those mental representations

–> in order to produce thought + action

Question 19

Ai predictions can be divided into 4 types.

Name them

Answer 19

1. Timeline + outcome predictions
   - -> when we will achieve AI milestones
2. Scenarios
   - -> conditional predictions; if certain conditions are met, certain outcome will follow
3. Plans
   - -> when deciding to implement a certain plan, they’ll be successful
4. Issues + meta-statements

Question 20

Are there any disadvantages to implementing AI ?

Answer 20

1. Several legal + ethical issues
2. Displaces human workers
3. Have the potential to repair or improve general cognitive abilities by making humans into cyborgs
4. Unknown outcomes associated with technology that approaches human general intelligence