Artificial Intelligence Now Current Perspectives from O'Reilly Media

The past year or so has seen a true explosion in both the capabilities and adoption of artificial intelligence technologies. Today’s generalized AI tools can solve specific problems more powerfully than the complex rule-based tools that preceded them. And, because these new AI tools can be deployed in many contexts, more and more applications and industries are ripe for transformation with AI technologies. By drawing from the best posts on the O’Reilly AI blog, this in-depth report summarizes the current state of AI technologies and applications, and provides useful guides to help you get started with deep learning and other AI tools. In six distinct parts, this report covers: The AI landscape: the platforms, businesses, and business models shaping AI growth; plus a look at the emerging AI stack Technology: AI’s technical underpinnings and deep learning capabilities, tools, and tutorials Homebuilt autonomous systems: "hobbyist" applications that showcase AI tools, libraries, cloud processing, and mobile computing Natural language: strategies for scoping and tackling NLP projects Use cases: an analysis of two of the leading-edge use cases for artificial intelligence—chat bots and autonomous vehicles Integrating human and machine intelligence: development of human-AI hybrid applications and workflows; using AI to map and access large-scale knowledge databases The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For computer professionals, linguists, and cognitive scientists interested in artificial intelligence. and applications, and provides useful guides to help you get started with deep learning and other AI tools. In six distinct parts, this report covers: The AI landscape: the platforms, businesses, and business models shaping AI growth; plus a look at the emerging AI stack Technology: AI’s technical underpinnings and deep learning capabilities, tools, and tutorials Homebuilt autonomous systems: "hobbyist" applications that showcase AI tools, libraries, cloud processing, and mobile computing Natural language: strategies for scoping and tackling NLP projects Use cases: an analysis of two of the leading-edge use cases for artificial intelligence—chat bots and autonomous vehicles Integrating human and machine intelligence: development of human-AI hybrid applications and workflows; using AI to map and access large-scale knowledge databases The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For computer professionals, linguists, and cognitive scientists interested in artificial intelligence.