IS 130 Final Topic 15

Question 1

What is Artificial Intelligence?

Answer 1

A subfield of computer science that studies the thought processes of humans and recreates the effects of those processes through information systems

Question 2

What technological advancements led to AI advancements?

Answer 2

• Advancements in chip technology
• Big Data
• The internet and cloud computing
• Improved algorithms

Question 3

Define Machine Learning

Answer 3

Application of AI with ability to automatically learn and improve experience without additional programming

Question 4

Define Deep Learning

Answer 4

a subset of machine learning in which artificial neural networks learning from large amounts of data
- can be supervised, semi-supervised and unsupervised
- can solve complex problems with unstructured and diverse data sets
- can discover new patterns in data

Question 5

What is supervised learning?

Answer 5

Human gives labeled data to system for predictive output

Question 6

What is semi-supervised learning ?

Answer 6

Humans only provide small amounts of data and large amounts of unlabeled data for the system to process

Question 7

What is unsupervised learning?

Answer 7

No pre-existing labeled data. Systems look for undetected patterns in the data with minimal human supervision

Question 8

What are expert systems?

Answer 8

Computer systems that attempt to mimic human experts by applying expertise in a specific domain

Question 9

What are Neural Networks?

Answer 9

A set of virtual neurons (nodes) that work in parallel to simulate the way the human brain works

Question 10

What are Recurrent Neural Networks (RNNs) ?

Answer 10

designed to access previous data such as sequential data or time series data during iterations of input

Question 11

What are Convolutional Neural Networks (CNNs) ?

Answer 11

designed to separate areas of image inputs by extracting features to identify edges, curves, and color density and then recombine these inputs for classification and prediction

Question 12

What are Generative Adversarial Networks (GANs) ?

Answer 12

consists of two neural networks that compete in a zero-sum game in an effort to segregate real data from synthetic data. GANs separate real data from noise. They perform well in applications where filling in missing or incomplete data may be required.

Question 13

Examples of artificial intelligence

Answer 13

• Computer vision
• Natural language processing
• Robotics
• Speech recognition

Question 14

What are Intelligent Agents?

Answer 14

Programs that assists users or acts on their behalf, in performing computer-related tasks

Question 15

What are the 2 types of intelligent agents?

Answer 15

• Information agents
• Monitoring and surveillance agents