Artificial Intelligence Fundamentals

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Questions and Answers

What does AI primarily involve in terms of computer programs or machines?

Performing functions that mimic human emotions

Executing tasks that require human-like intelligence (correct)

Analyzing large sets of data without interpretive skills

Creating visual art without human assistance

Which of the following best defines the purpose of AI?

To replace human labor entirely in all fields

To create programs that are faster than human thought

To perform intelligent functions typically done by humans (correct)

To develop machines that enhance human capabilities

Which aspect does AI NOT focus on based on the described functions?

Functionality requiring human intelligence

Operational efficiency in machine tasks

Intelligent task performance

Artistic creativity in programming (correct)

In what way can AI be viewed in relation to human functions?

As a set of systems performing intelligent tasks similar to humans Signup and view all the answers

Which statement about AI's functions is least accurate?

AI exclusively operates within human cognitive limitations. Signup and view all the answers

Which of the following is NOT considered an activity or goal of artificial intelligence?

Emotional intelligence Signup and view all the answers

Among the listed activities, which involves making educated guesses about future events?

Prediction Signup and view all the answers

Which artificial intelligence activity primarily focuses on creating a structured understanding of facts and concepts?

Knowledge representation (using logic) Signup and view all the answers

What is an example of using logic to derive conclusions in artificial intelligence?

Reasoning (using logic) Signup and view all the answers

Which of these activities specifically involves formulating strategies to achieve specific objectives?

Planning (using logic) Signup and view all the answers

What is the primary goal of making computer programs think and act like humans?

To imitate rational and intelligent human behavior Signup and view all the answers

What does cognitive modeling specifically involve?

Simulating human thinking and information processing Signup and view all the answers

Which aspect does NOT pertain to cognitive modeling?

Creating virtual environments for gaming Signup and view all the answers

Which of the following best describes an application of cognitive modeling?

Creating a chatbot that mimics human conversation Signup and view all the answers

What is a potential benefit of cognitive modeling in computer programs?

Improved ability to make human-like decisions Signup and view all the answers

Which of the following terms relates to the process of evaluating opinions in textual data?

Sentiment Analysis Signup and view all the answers

What process involves converting text from one language to another?

Machine Translation Signup and view all the answers

Which term describes the extraction of relevant information from a large set of data?

Information Retrieval Signup and view all the answers

What is the term for the capability of a computer program to understand and respond to human language?

Speech Recognition Signup and view all the answers

Which of the following functionalities assists in managing unwanted or spam emails?

Email Filtering Signup and view all the answers

What is the role of the testing dataset in machine learning?

To evaluate the performance of the trained model Signup and view all the answers

What type of machine learning involves grouping similar data points together?

Clustering Signup and view all the answers

Which of the following describes the output of a classification model?

Categorical labels or classes Signup and view all the answers

What is the primary purpose of association learning in machine learning?

To identify relationships between variables Signup and view all the answers

What is a key step involved in the life cycle of machine learning after the training dataset?

Optimization of model parameters Signup and view all the answers

What is the primary characteristic of supervised learning?

It learns exclusively from labeled data. Signup and view all the answers

Which type of learning uses both labeled and unlabeled data for training?

Semi supervised learning Signup and view all the answers

Unsupervised learning is primarily characterized by its use of:

Unlabeled data sets Signup and view all the answers

What differentiates semi supervised learning from traditional supervised learning?

It uses a smaller amount of labeled data than supervised learning. Signup and view all the answers

Which of the following statements is false regarding unsupervised learning?

It requires labeled data for training. Signup and view all the answers

Study Notes

Introduction to Artificial Intelligence (AI)

AI's birth was in 1956.
AI is a subfield of computer science concerned with how computer programs/machines can think and act like humans.
AI simulates human intelligence in machines, programming them to think like humans and mimic their actions.
AI automates activities associated with human thinking, including decision-making, learning, planning, reasoning, searching, acting, and problem-solving.
It aims to create computer programs or machines to perform functions requiring intelligence when done by people.
AI focuses on automating intelligent behavior based on computational models.

Goals of AI

Artificial: Created by human effort, not naturally occurring.
Intelligence: The ability to acquire knowledge and use it (Pigford and Baur).
AI goals: Making computers more helpful by taking on dangerous or tedious tasks from humans, and understanding the principles of human intelligence.

Organization of AI Definitions

Categorized into four groups:
- Systems that think like humans
- Systems that think rationally
- Systems that act like humans
- Systems that act rationally

What is Artificial Intelligence (AI)?

Making computer programs think and act like humans (rationally and intelligently).

Systems that think like humans: Cognitive Modeling

Cognitive modeling: Process of building computer-based simulations/models to mimic how humans think and process information.
Observing humans from the inside to understand how they think (introspection vs. psychological experiments).
AI goal: Mimic human minds (Haugeland)
Activities like decision-making, problem-solving, and learning are automated. (Bellman)

What about the brain?

Brains excel at making rational decisions(though not perfect).
Brains are analogous to software wings in flight, not modular like software.
Prediction and simulation are key to decision-making.

Systems that think rationally: "Laws of Thought"

Humans are not always rational.
Rationality is defined in terms of logic, but logic cannot encompass everything (e.g., uncertainty).
Logical approaches can be computationally expensive.
Thinking rationally is understanding the mental faculties through computational models.(Charniak and McDermott)
Thinking rationally is understanding computations enabling perception, reasoning, and action.(Winston)

Turing Test

The Turing Test approach: A human questioner cannot differentiate between a computer and a human based on responses.
Intelligent behavior: Human-level performance in all cognitive tasks.
Total Turing Machine: Includes computer vision and robotics to perceive and move objects, respectively.

Cognitive Tasks

Natural Language Processing: For human communication.
Knowledge Representation: Effective and efficient storage of information.
Automated Reasoning: Retrieving and answering questions based on stored information.
Machine Learning: Adapting to new situations.

Artificial Intelligence (AI) Activities/Tasks/Goals

Searching
Planning (using logic)
Knowledge representation (using logic)
Reasoning (using logic)
Prediction
Learning
Decision-making (using logic)
Problem-solving (using logic)
Perception (using logic)
Simulation

Artificial Intelligence (AI) Areas/Applications

Machine learning
Deep learning
Natural language processing (NLP)
Computer vision
Image processing
Internet of things
Robotics
Cyber security
Virtual reality
Social media
Agriculture
Business, marketing, and finance
Industry/manufacturing
Sports
Healthcare
Transportation
Expert systems
Email spam filtering
Climate forecasting
Entertainment
Engineering
Software engineering
Recommendation systems
Game playing (e.g., chess)
Bioinformatics
Politics and intelligence
Music composition
Web search engines
Education
Government (Surveillance)
E-commerce
Technology and smart devices
Travel and logistics

Natural Language Processing Applications

Chatbots
Sentiment analysis
Machine translation
Information retrieval
Question answering
Speech recognition
Email filtering

Some of the Main Activities and Areas of Al and Their Interdependencies

A diagram showing the interconnections between various AI activities (Search, Logic, Knowledge Representation, Machine Learning, Planning, NLP, Vision, Robotics, and Expert Systems).

Systems that Act Rationally: "Rational Agent"

Rational behavior: Doing the correct thing.
The right thing: Maximizing goal achievement given available information.
A rational agent does not need to replicate human thought processes or make the same decisions as humans.
Uses purely logical reasoning instead if necessary.

Rational Agents

An agent is an entity that perceives and acts.
Agents function as a function of perceived histories and taking actions following it.
Seek the agent with the best performance, considering environment and given tasks.
Unattainable perfect rationality due to computational limits.
Design programs that best utilize available machine resources.

Search

Search is the basic technique in AI.
Possible answers, decisions, and actions are structured as an abstract space, and searched through in order to find solutions.
Search can be categorized as uninformed, or informed(with prior assumptions).

Knowledge Representation & Reasoning

Knowledge representation and reasoning are crucial for rational behavior in environments.
Environments need to be described, or represented, allowing for inferences to be made.
Methods used for describing the world effectively: How to describe it concisely? How to get hold of the right information when needed? How do we generate new knowledge? How do we deal with uncertainty?

Advantages of Artificial Intelligence

More powerful and useful computers.
Improved user interfaces.
Solution to new problems
Better information handling
Relieved information overload.
Conversion of information to knowledge

Disadvantages of Artificial Intelligence

High cost
Difficult and costly to develop software.
Few experienced AI programmers.
Little practical AI products that are implemented in the market.

Machine Learning

Machine learning (ML) is a subfield of artificial intelligence (AI) focused on computer programs improving performance through experience using data.

Life Cycle of Machine Learning

Input data (training dataset)
Machine Learning
Testing dataset
Output training model
Output
Predictions, Classification, Clustering, Association, Learning

Types of learning using Machine Learning

Supervised learning: Learning from labelled data.
Unsupervised learning: Learning from unlabeled data.
Semi-supervised learning: Learning from labeled and unlabeled data.
Reinforcement learning: Learning based on feedback.

Machine Learning Tasks

Regression (Prediction)
Classification
Clustering
Association
Learning

Studying That Suits You

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Description

Test your understanding of the key concepts and definitions related to artificial intelligence. This quiz covers the primary functions, goals, and activities associated with AI, as well as cognitive modeling. Challenge yourself to distinguish between accurate and inaccurate statements about AI.