Chapter 1: Artificial Intelligence Overview

A mathematical representation of what an AI agent or a system aims to achieve.

The principle that reason and logical thought are the primary sources of knowledge.

The belief that everything in the universe, including the mind, can be explained in terms of matter and physical laws.

The idea that AI aims to make choices using logic and mathematical reasoning.

The process of drawing general conclusions from specific observations or experiences.

The relationship between cause and effect; how events are connected.

The idea that exposure to repeated experiences leads to learning and improvement.

A graph that shows how learning progresses over time, with experience on the horizontal axis and learning on the vertical axis.

A machine or mechanism designed to follow a predetermined set of operations or instructions.

Invented by Alan Turing to assess a machine's ability to exhibit intelligent behavior by engaging in a conversation that is indistinguishable from a human conversation.

A field of study dedicated to creating machines that can think, learn, and solve problems like humans.

A programming language specifically designed for AI applications, widely used for solving problems like fraud detection and web design.

American scientist who coined the term "artificial intelligence" and made significant contributions to the field, including the development of the Lisp programming language.

Early AI researcher and cognitive scientist who, along with John McCarthy, founded the MIT Artificial Intelligence Laboratory.

A group of female mathematicians who played a key role in the development of the ENIAC computer, a significant step in the history of computing.

A linguist and philosopher whose work on language theory had a profound impact on the development of AI.

A significant and rapid change in society marked by the adoption of new technologies that dramatically impact how people live, work, and interact.

A process where creative individuals make discoveries or inventions that address human needs and interests, often leading to major societal changes.

The invention of the printing press by Gutenberg in 1440, enabling the mass production of books and the widespread distribution of information and knowledge.

The discovery of the process for synthesizing ammonia by Fritz Haber in 1910, leading to increased agricultural yields and supporting larger populations.

The splitting of the atom by Ernest Rutherford in 1917, marking the beginning of nuclear physics and leading to the development of the atomic bomb.

A technology developed during World War II for controlling torpedoes, now used in various telecommunications applications like Bluetooth.

The current period characterized by rapid advancements in artificial intelligence (AI) and its potential to revolutionize various aspects of human life.

These devices use sensors and AI algorithms to provide assistance with tasks like health monitoring and safety. They work by collecting data and analyzing it to provide helpful insights or warnings.

This type of AI works alongside human experts, taking on tasks where machines excel. Humans still control the overall process, but get help from AI for specific areas.

This involves AI systems making decisions and taking actions without humans in the loop. Examples include self-driving cars and robots that handle warehouse tasks.

This is a type of AI where systems are trained on data and learn to perform a specific task without explicit programming. They can improve with experience.

This involves AI systems that can understand and respond to natural language like humans. They're used for things like chatbots and voice assistants.

This is a type of AI that seeks to mimic the human brain's structure and function. This field is still in its early stages, but there are potential applications in areas like robotics and medical diagnosis.

AI systems are designed to complete a task without human supervision, but these systems need careful consideration of ethical implications, especially in areas like autonomous driving where life-or-death decisions may be made.

The future of AI is constantly evolving, with new advancements happening all the time. It's hard to predict exactly what the future holds, but it's exciting to consider the potential impact of AI on various aspects of our lives.

A game of strategy and complexity, often considered too challenging for AI due to the vast number of possible moves.

A Go-playing AI system developed by DeepMind, which beat professional Go player Lee Sedol in 2016.

A type of AI training where a system learns by playing against itself and improving its strategies.

A system that learns Go solely through self-play, surpassing the performance of AlphaGo.

The interconnected network of devices embedded in everyday objects, sending and receiving data.

The use of AI to analyze data generated by IoT devices and provide customized services.

The potential for AI to be used for both beneficial and harmful purposes.

The collection and use of personal data from smart devices raise concerns about privacy and ethical implications.

Funders stop supporting AI research when it fails to deliver promised results.

When AI research relies on expensive technology that suddenly becomes cheaper, funding may shift towards the less costly alternative.

When AI relies on massive amounts of data and processing power, but these resources are not readily available, the project might be seen as a failure.

AI research projects that fail to deliver expected results can lead to funding cuts and a decline in overall interest.

AI research can advance only when both computing power and data availability improve significantly.

Even though AI research 'winters' can lead to setbacks, they also provide an opportunity to reassess and improve research direction.

AI research can be revived and progress can be made through reforms and advancements in technology.

The 'Mansfield Amendment' restricted funding for AI research to projects directly related to specific military missions.