Is Intelligence An Algorithm
Download Is Intelligence An Algorithm PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Is Intelligence An Algorithm book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Algorithms are Not Enough
"The holy grail of artificial intelligence research has been the achievement of artificial general intelligence. Since the inception of artificial intelligence, machines that can perform any task that a human might have been predicted to be imminent. Some people have been enthusiastic about this prospect, but others have been terrified. Both have been disappointed. In fact, despite all of the progress in solving individual tasks, this research has not been on a road that could ever lead to general intelligence. To paraphrase the Ancient Greek poet, Archilochus, we have been building hedgehogs, when what we are after is a Fox. The fox, he said, knows many things, but the hedgehog knows one big thing. Even a stack of hedgehogs, however, cannot duplicate the intelligence of a fox. This book describes a roadmap for designing a generally intelligent fox that solves the problem of general intelligence. It brings to bear wide swaths of cognitive science, including psychology, philosophy, and history to debunk the barriers to general intelligence by identifying the essential features of intelligence that would be needed to achieve general artificial intelligence. Along the way, it makes it apparent that fears of an imminent explosion of uncontrollable computational intelligence (the so-called "singularity,") are completely unfounded"--
Algorithms of the Intelligent Web
Author: Haralambos Marmanis
language: en
Publisher: Manning Publications
Release Date: 2009
"Algorithms of the Intelligent Web" is an example-driven blueprint for creating applications that collect, analyze, and act on the massive quantities of data users leave in their wake as they use the Web. Readers learn to build Netflix-style recommendation engines, and how to apply the same techniques to social-networking sites.
Grokking Artificial Intelligence Algorithms
”This book takes an impossibly broad area of computer science and communicates what working developers need to understand in a clear and thorough way.” - David Jacobs, Product Advance Local Key Features Master the core algorithms of deep learning and AI Build an intuitive understanding of AI problems and solutions Written in simple language, with lots of illustrations and hands-on examples Creative coding exercises, including building a maze puzzle game and exploring drone optimization About The Book “Artificial intelligence” requires teaching a computer how to approach different types of problems in a systematic way. The core of AI is the algorithms that the system uses to do things like identifying objects in an image, interpreting the meaning of text, or looking for patterns in data to spot fraud and other anomalies. Mastering the core algorithms for search, image recognition, and other common tasks is essential to building good AI applications Grokking Artificial Intelligence Algorithms uses illustrations, exercises, and jargon-free explanations to teach fundamental AI concepts.You’ll explore coding challenges like detecting bank fraud, creating artistic masterpieces, and setting a self-driving car in motion. All you need is the algebra you remember from high school math class and beginning programming skills. What You Will Learn Use cases for different AI algorithms Intelligent search for decision making Biologically inspired algorithms Machine learning and neural networks Reinforcement learning to build a better robot This Book Is Written For For software developers with high school–level math skills. About the Author Rishal Hurbans is a technologist, startup and AI group founder, and international speaker. Table of Contents 1 Intuition of artificial intelligence 2 Search fundamentals 3 Intelligent search 4 Evolutionary algorithms 5 Advanced evolutionary approaches 6 Swarm intelligence: Ants 7 Swarm intelligence: Particles 8 Machine learning 9 Artificial neural networks 10 Reinforcement learning with Q-learning