Artificial Intelligence Concepts and Turing Test

A rule of logic that states if a statement is true, and a second statement states that if the first statement is true then a third statement is true, then the third statement must also be true.

A statement that is always true, regardless of the situation.

A statement that is known to be true in a specific scenario or context.

The process of using logical rules to draw conclusions from given information.

The conclusion drawn from applying the Modus Ponens rule.

The ability of artificial intelligence to perform actions it was not designed to do, suggesting independent decision-making.

The branch of computer science that focuses on creating machines capable of performing tasks that typically require human intelligence.

A type of AI that focuses on creating machines that act like humans, even if they don't necessarily think like them.

A type of AI that focuses on creating machines that think rationally, even if they don't necessarily act like humans.

A type of AI that focuses on creating machines that think like humans, using similar mental processes and reasoning skills.

The process of finding the best solution among a set of possible choices, often used in AI systems for decision-making.

This area of AI focuses on techniques that allow machines to classify patterns and make predictions from data, often used in areas like image recognition and spam filtering.

The field of AI that aims to create machines that can learn and improve their performance over time without being explicitly programmed.

The study of how the human mind works, focusing on testable theories and principles.

The goal of AI is to create machines that can perform tasks that normally require human intelligence.

A logical structure for arguments that ensures correct conclusions if the premises are true.

A common approach in AI involves taking a task that humans are good at and developing a computer system to perform it effectively.

The Turing Test is a way to assess whether a computer can exhibit intelligent behavior that is indistinguishable from a human.

A reasoning rule that states: if 'A' is true, and 'if A then B' is true, then 'B' must be true.

A statement that can be either true or false.

The Turing Test involves a human interrogator interacting with a computer and a human without knowing which is which.

The process of analyzing information to identify the basic statements that form the premise of an argument.

The Turing Test aims to provide an objective measure of intelligence, focusing on the content of answers rather than internal processes.

Represented by 'A' in the Modus Ponens Rule, this is the initial or known statement that is assumed to be true.

The Turing Test aims to avoid philosophical debates about the true nature of intelligence.

Examples of tasks that AI systems are being developed to perform include proving mathematical theorems, playing chess, diagnosing diseases, and driving cars.

Represented by 'B' in the Modus Ponens Rule, this is the statement that is concluded to be true based on the truth of statement 'A' and the conditional statement 'if A then B'.

A conditional statement that expresses a relationship between two statements. It's represented as 'if A then B' in the Modus Ponens Rule.

The Turing Test was proposed by Alan Turing in his 1950 paper 'Computing Machinery and Intelligence.'

Facebook's facial recognition system, launched in 2014, capable of matching human faces with near-human accuracy.

A deep learning architecture, published by Ashish Waswani in 2017, that revolutionized natural language processing by leveraging attention mechanisms.

A groundbreaking language model released by OpenAI in 2020, significantly advancing natural language processing capabilities.

Khalifa University's efforts to implement AI in diverse fields, including security, healthcare, and maintenance.

An AI application that recognizes faces for security purposes, including access control, surveillance, and identification.

An AI application that utilizes facial recognition for ticketing, eliminating the need for physical gates or booths.

An AI application that analyzes tissue samples for early detection and prognosis of colorectal cancer.

An AI application that automatically identifies and classifies nuclei in Whole Slide Images (WSI) through graph-based analysis and convolutional neural networks.

An AI application for automated screening of passenger baggage, aiming to enhance security measures at airports and other transportation hubs.

An AI application that monitors flare activity using vision-based systems, promoting enhanced safety and environmental protection.

The first mathematical model of a neural network, published in 1943 by McCulloch and Pitts. This model laid the foundation for modern neural network research.

A test proposed by Alan Turing in 1950 to assess a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human.

The year when the term 'Artificial Intelligence' was officially coined at the Dartmouth Workshop in 1956.

The first artificial neural network capable of learning, developed by Frank Rosenblatt in 1957. It could learn to recognize patterns from data.

A natural language processing program created by Joseph Weizenbaum in 1965-1967. ELIZA could simulate conversation by using simple pattern matching and substitution rules, fooling many users into believing they were interacting with a real person.

Programs designed to mimic human expertise in specific domains, like financial forecasting or medical diagnoses. They became popular in the 1980s.

A major milestone in AI. It refers to the development of neural networks with multiple layers, enabling them to learn more complex patterns from data.

The study of how to make machines that can perceive, reason and act.

A scene in "2001 Space Odyssey" where HAL 9000, an onboard computer system, appears to disobey instructions. This raises questions about its 'self-control' and possible independent actions.

Systems that aim to mimic human intelligence, typically focusing on either acting or thinking like humans.

The process of finding the best solution among multiple options. This is often used in AI systems for decision-making.

AI systems that use algorithms to learn from data and make predictions. This allows AI to improve its performance without explicit programming.

The ability for AI to improve its performance over time without being explicitly programmed. This is done by learning from data using things like machine learning.

The branch of AI that focuses on making machines that can learn and improve their performance over time without being explicitly programmed.

AI is the art of creating machines that perform functions that require intelligence when performed by humans.

The Imitation Game is an operational test for intelligent behavior, where a machine tries to convince a human interrogator that it is also human.

A facial recognition system developed by Facebook in 2014, achieving near-human accuracy in recognizing faces.

A groundbreaking deep learning architecture published in 2017, significantly impacting natural language processing by leveraging attention mechanisms.

A powerful language model released by OpenAI in 2020, marking a significant advancement in natural language processing capabilities.

Applications of AI for surveillance and security using facial recognition technology, including access control and identification.

AI applications in healthcare for diagnosing Down syndrome based on facial features.

AI-powered tissue analysis for detecting and predicting the likelihood of colorectal cancer.

AI for identifying and classifying nuclei in whole slide images (WSI) using graph analysis and deep convolutional neural networks.

AI-powered automated screening of passenger baggage to enhance security at airports and other transportation hubs.

AI for monitoring flare activity using vision-based systems, ensuring safety and environmental protection.

The use of AI to predict potential failures in assets based on data from sensors, networks, and images.

An agent's ability to act independently without human intervention.

An agent's ability to perceive and interact with its environment.

A system that aims to mimic human intelligence.

An agent that uses a model to keep track of parts of the environment that it can't directly observe.

An agent that takes actions to achieve specific goals by reasoning about the consequences of its actions.

AI systems that use algorithms to learn from data and make predictions, such as image recognition or spam filtering.

A type of AI system where the environment changes over time, such as a self-driving car navigating a busy city.

Describes a system where the variables are continuous and can take any value within a range, like road positions on a map.

AI systems consider uncertainties, like unpredictable pedestrian behavior, when making decisions.

A type of AI system where the variables are discrete and can only take a limited number of values, like traffic light states (red, yellow, green).

Agent programs that respond directly to the current situation (percept) without considering past experiences or future consequences.

Agent programs that continuously learn and improve their performance based on feedback received from the environment. They adapt to changing conditions and acquire new knowledge.

Agent programs that interact with other agents or humans. They coordinate actions and exchange information to achieve common goals.

The environment changes while the agent is making a decision.

The agent has to act quickly or keep updating its choices because the situation is changing.

The agent might have to make decisions in a real-time setting where delays could be harmful.

The agent's actions can influence the environment and change future decisions.

The ability for an agent to adapt to unexpected changes in the environment and learn from its experiences.

An environment where the environment itself doesn't change, but the agent's performance score or preferences may change over time.