Artificial Intelligence

Synopsis

Thelong-anticipated revision of ArtificialIntelligence: A Modern Approach explores the full breadth and depth of the field of artificialintelligence (AI). The 4th Edition brings readers up to date on the latest technologies,presents concepts in a more unified manner, and offers new or expanded coverageof machine learning, deep learning, transfer learning, multi agent systems,robotics, natural language processing, causality, probabilistic programming,privacy, fairness, and safe AI.

Summary

Chapter 1: Introduction

* Defines AI as the simulation of human intelligence by machines.
* Explores the history and current state of AI.
* Real example: Self-driving cars use AI to navigate and make decisions without human input.

Chapter 2: Machine Learning

* Introduces machine learning as a subtype of AI where computers learn from data without explicit programming.
* Explains supervised, unsupervised, and reinforcement learning methods.
* Real example: Recommendation engines use supervised learning to predict user preferences based on past data.

Chapter 3: Natural Language Processing

* Covers AI techniques for understanding and generating human language.
* Discusses text classification, sentiment analysis, and machine translation.
* Real example: Virtual assistants like Siri use NLP to interpret user commands and provide appropriate responses.

Chapter 4: Computer Vision

* Explores AI algorithms that enable computers to "see" and interpret visual data.
* Explains image recognition, object detection, and semantic segmentation.
* Real example: Security cameras use computer vision to identify and track individuals.

Chapter 5: Reasoning and Knowledge Representation

* Discusses how AI systems represent and reason about the world around them.
* Covers logical reasoning, knowledge graphs, and ontologies.
* Real example: Medical diagnosis systems use knowledge representation to identify potential diseases based on patient symptoms.

Chapter 6: Robotics

* Explores the intersection of AI and robotics.
* Discusses perception, planning, and control in AI-powered robots.
* Real example: Industrial robots use AI to perform complex tasks such as welding and assembly.

Chapter 7: Ethical and Societal Implications

* Examines the potential benefits and risks of AI.
* Discusses issues of privacy, bias, and job displacement.
* Real example: Facial recognition software raises concerns about surveillance and discrimination.

Chapter 8: The Future of AI

* Speculates on the future trajectory of AI.
* Explores advancements in deep learning, quantum computing, and other emerging technologies.
* Real example: AI-powered virtual reality experiences could revolutionize education and entertainment.