Levesque considers the role of language in learning. What artificial intelligence can tell us about the mind and intelligent behavior. What can artificial intelligence teach us about the mind? If AI's underlying concept is that thinking is a computational process, then how can computation illuminate thinking? It's a timely question.
Common Sense, the Turing Test, and the Quest for Real AI MIT Press #ad - This is what powers a driverless car, for example. In this book, hector levesque shifts the conversation to "good old fashioned artificial intelligence, " which is based not on heaps of data but on understanding commonsense intelligence. This kind of artificial intelligence is equipped to handle situations that depart from previous patterns―as we do in real life, for example, when, we encounter a washed-out bridge or when the barista informs us there's no more soy milk.
He identifies a possible mechanism behind common sense and the capacity to call on background knowledge: the ability to represent objects of thought symbolically. Mit. Ai is all the rage, and the buzziest AI buzz surrounds adaptive machine learning: computer systems that learn intelligent behavior from massive amounts of data.
What Algorithms Want: Imagination in the Age of Computing The MIT PressThe MIT Press #ad - In this book, ed finn considers how the algorithm―in practical terms, “a method for solving a problem”―has its roots not only in mathematical logic but also in cybernetics, philosophy, and magical thinking. Computation casts a cultural shadow that is shaped by this long tradition of magical thinking.
It's as if we think of code as a magic spell, an incantation to reveal what we need to know and even what we want. Finn argues that the algorithm deploys concepts from the idealized space of computation in a messy reality, with unpredictable and sometimes fascinating results. Drawing on sources that range from neal stephenson's Snow Crash to Diderot's Encyclopédie, from Adam Smith to the Star Trek computer, Finn explores the gap between theoretical ideas and pragmatic instructions.
The gap between theoretical ideas and messy reality, Adam Smith, as seen in Neal Stephenson, and Star Trek. We depend on―we believe in―algorithms to help us get a ride, choose which book to buy, execute a mathematical proof. He describes google's goal of anticipating our questions, and what Facebook tells us about programmable value, Uber's cartoon maps and black box accounting, among other things.
What Algorithms Want: Imagination in the Age of Computing The MIT Press #ad - If we want to understand the gap between abstraction and messy reality, Finn argues, we need to build a model of “algorithmic reading” and scholarship that attends to process, spearheading a new experimental humanities. He examines the development of intelligent assistants like Siri, the rise of algorithmic aesthetics at Netflix, Ian Bogost's satiric Facebook game Cow Clicker, and the revolutionary economics of Bitcoin.
The mit Press.
Life 3.0: Being Human in the Age of Artificial IntelligenceKnopf #ad - The mit Press. It doesn’t shy away from the full range of viewpoints or from the most controversial issues—from superintelligence to meaning, consciousness and the ultimate physical limits on life in the cosmos. How can we grow our prosperity through automation without leaving people lacking income or purpose? what career advice should we give today’s kids? How can we make future AI systems more robust, malfunctioning or getting hacked? Should we fear an arms race in lethal autonomous weapons? Will machines eventually outsmart us at all tasks, so that they do what we want without crashing, replacing humans on the job market and perhaps altogether? Will AI help life flourish like never before or give us more power than we can handle? What sort of future do you want? This book empowers you to join what may be the most important conversation of our time.
New york times best sellerhow will artificial intelligence affect crime, society and our very sense of being human? The rise of AI has the potential to transform our future more than any other technology—and there’s nobody better qualified or situated to explore that future than Max Tegmark, justice, jobs, war, an MIT professor who’s helped mainstream research on how to keep AI beneficial.
The Digital Mind: How Science Is Redefining Humanity The MIT PressThe MIT Press #ad - Our brains have even allowed us to develop computers that are almost as powerful as the human brain itself. How developments in science and technology may enable the emergence of purely digital minds―intelligent machines equal to or greater in power than the human brain. What do computers, cells, and brains have in common? Computers are electronic devices designed by humans; cells are biological entities crafted by evolution; brains are the containers and creators of our minds.
Oliveira describes technological and scientific advances that range from the discovery of laws that control the behavior of the electromagnetic fields to the development of computers. Over eons of evolution, the brain has enabled us to develop tools and technology to make our lives easier. Having considered the behavior of the unique system that creates a mind, oliveira says, legal, it is difficult to argue that they will not―what are the social, and ethical implications? Will digital minds be our partners, he turns to an unavoidable question: Is the human brain the only system that can host a mind? If digital minds come into existence―and, or our rivals? The mit Press.
The Digital Mind: How Science Is Redefining Humanity The MIT Press #ad - In this book, arlindo Oliveira describes how advances in science and technology could enable us to create digital minds. The power of the human brain is, so far, unequaled by any existing machine or known living being. He calls natural selection the ultimate algorithm, discusses genetics and the evolution of the central nervous system, and describes the role that computer imaging has played in understanding and modeling the brain.
Deep Thinking: Where Machine Intelligence Ends and Human Creativity BeginsPublicAffairs #ad - Mit. Deep thinking is a tightly argued case for technological progress, from the man who stood at its precipice with his own career at stake. Garry kasparov's 1997 chess match against the IBM supercomputer Deep Blue was a watershed moment in the history of technology. As many critics decry artificial intelligence as a menace, Kasparov shows how humanity can rise to new heights with the help of our most extraordinary creations, particularly to human jobs, rather than fear them.
That moment was more than a century in the making, and in this breakthrough book, Kasparov reveals his astonishing side of the story for the first time. The mit Press. Publicaffairs. Kasparov uses his unrivaled experience to look into the future of intelligent machines and sees it bright with possibility. He describes how it felt to strategize against an implacable, and recounts the history of machine intelligence through the microcosm of chess, untiring opponent with the whole world watching, considered by generations of scientific pioneers to be a key to unlocking the secrets of human and machine cognition.
Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins #ad - It was the dawn of a new era in artificial intelligence: a machine capable of beating the reigning human champion at this most cerebral game.
Thinking as Computation: A First Course The MIT PressThe MIT Press #ad - The mit Press. Publicaffairs. Students use prolog without having to learn algorithms: “Prolog without tears!”, learning to express what they need as a Prolog program and letting Prolog search for answers. After an introduction to the basic concepts, Thinking as Computation offers three chapters on Prolog, programs and queries, covering back-chaining, and how to write the sorts of Prolog programs used in the book.
Mit. Students explore the idea that thinking is a form of computation by learning to write simple computer programs for tasks that require thought. This book guides students through an exploration of the idea that thinking might be understood as a form of computation. Most of the chapters conclude with short bibliographic notes and exercises.
The book is based on a popular course at the University of Toronto and can be used in a variety of classroom contexts, by students ranging from first-year liberal arts undergraduates to more technically advanced computer science students. The book follows this with case studies of tasks that appear to require thought, then looks beyond Prolog to consider learning, explaining, and propositional reasoning.
Thinking as Computation: A First Course The MIT Press #ad - Students make the connection between thinking and computing by learning to write computer programs for a variety of tasks that require thought, recognizing objects in visual scenes, including solving puzzles, understanding natural language, planning courses of action, and playing strategic games. The mit Press.
The material is presented with minimal technicalities and is accessible to undergraduate students with no specialized knowledge or technical background beyond high school mathematics.
Deep Learning Adaptive Computation and Machine Learning seriesThe MIT Press #ad - An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. Written by three experts in the field, Deep Learning is the only comprehensive book on the subject. Elon musk, cochair of openai; cofounder and ceo of Tesla and SpaceXDeep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts.
Publicaffairs. The text offers mathematical and conceptual background, numerical computation, covering relevant concepts in linear algebra, probability theory and information theory, and machine learning. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep.
Deep Learning Adaptive Computation and Machine Learning series #ad - This book introduces a broad range of topics in deep learning. Deep learning adaptive computation and machine learning. The mit Press. A website offers supplementary material for both readers and instructors. Mit. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, structured probabilistic models, approximate inference, Monte Carlo methods, representation learning, autoencoders, the partition function, and deep generative models.
The mit Press.
Enlightenment Now: The Case for Reason, Science, Humanism, and ProgressViking #ad - Instead, and happiness are on the rise, prosperity, peace, follow the data: In seventy-five jaw-dropping graphs, not just in the West, knowledge, safety, Pinker shows that life, health, but worldwide. Instant new york times bestseller "my new favorite book of all time. Bill gates if you think the world is coming to an end, think again: people are living longer, and while our problems are formidable, healthier, freer, and happier lives, the solutions lie in the Enlightenment ideal of using reason and science.
But more than ever, it needs a vigorous defense. This progress is not the result of some cosmic force. The enlightenment project swims against currents of human nature--tribalism, demonization, authoritarianism, magical thinking--which demagogues are all too willing to exploit. The mit Press. It is a gift of the Enlightenment: the conviction that reason and science can enhance human flourishing.
Enlightenment Now: The Case for Reason, Science, Humanism, and Progress #ad - Far from being a naïve hope, we now know, the Enlightenment, has worked. Mit. With intellectual depth and literary flair, Enlightenment Now makes the case for reason, science, and humanism: the ideals we need to confront our problems and continue our progress. The mit Press.
Artificial Intelligence and Legal Analytics: New Tools for Law Practice in the Digital AgeCambridge University Press #ad - These legal applications will support conceptual legal information retrieval and allow cognitive computing, enabling a collaboration between humans and computers in which each does what it can do best. Today, generating arguments for and against particular outcomes, specifically by connecting computational models of legal reasoning directly with legal text, new legal applications are beginning to appear and this book - designed to explain computational processes to non-programmers - describes how they will change the practice of law, predicting outcomes and explaining these predictions with reasons that legal professionals will be able to evaluate for themselves.
Deep learning adaptive computation and machine learning series. The field of artificial intelligence ai and the law is on the cusp of a revolution that began with text analytic programs like IBM's Watson and Debater and the open-source information management architectures on which they are based. Anyone interested in how AI is changing the practice of law should read this illuminating work.
Artificial Intelligence and Legal Analytics: New Tools for Law Practice in the Digital Age #ad - The mit Press. Publicaffairs. Deep learning adaptive computation and machine learning. The mit Press. Mit. Cambridge university press.
Machines That Think: The Future of Artificial IntelligencePrometheus #ad - Publicaffairs. The mit Press. Deep learning adaptive computation and machine learning. A scientist who has spent a career developing Artificial Intelligence takes a realistic look at the technological challenges and assesses the likely effect of AI on the future. How will artificial intelligence ai impact our lives? Toby Walsh, one of the leading AI researchers in the world, takes a critical look at the many ways in which "thinking machines" will change our world.
Based on a deep understanding of the technology, Walsh describes where Artificial Intelligence is today, and where it will take us. Will automation take away most of our jobs? ·is a "technological singularity" near? ·What is the chance that robots will take over? ·How do we best prepare for this future? The author concludes that, if we plan well, AI could be our greatest legacy, the last invention human beings will ever need to make.
Machines That Think: The Future of Artificial Intelligence #ad - . Deep learning adaptive computation and machine learning series. The mit Press. Cambridge university press. Mit.
Visualize - Analyze - Interpret - Construct - Complex Network Analysis in Python: RecognizePragmatic Bookshelf #ad - If you're a curious python programmer, or a CNA specialist interested in mechanizing mundane tasks, a data scientist, you'll increase your productivity exponentially. The mit Press. Combine your cna and python programming skills to become a better network analyst, a more accomplished data scientist, and a more versatile programmer.
Mit. Discover how to work with all kinds of networks, spatial, temporal, product, including social, and semantic networks. Publicaffairs. The mit Press. Network analysis is a powerful tool you can apply to a multitude of datasets and situations. Adapt the patterns from the case studies to your problems. Explore big networks with NetworKit, a high-performance networkx substitute.
Visualize - Analyze - Interpret - Construct - Complex Network Analysis in Python: Recognize #ad - What you need: You will need a Python 3. X installation with the following additional modules: Pandas >=018, numpy >=1. 10, matplotlib >=1. 5, networkx >=1. 11, python-louvain >=0