Building Machines That See Think And Act Like Humans
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Building Machines That See, Think, and Act Like Humans
Building Machines That See, Think, and Act Like Humans Engineering Conscious Machines Through Visual Understanding Can a machine see the world as we do,and understand it with human-like intelligence? This groundbreaking book tackles one of the greatest challenges in Artificial General Intelligence (AGI, machines with broad, human-level cognitive abilities): designing systems that perceive, reason, and act with the flexibility, adaptability, and awareness of the human mind. Core Strength of My AGI Systems Unlike traditional devices, my invention doesn’t just recreate images it provides semantic, context-aware visual understanding, making it ideal for assisting the blind in real-world environments with navigation, object recognition, and safety. This book can help creating many AGI devices. For example: Governments can’t afford to install and monitor CCTV cameras in every park or public space, it’s expensive and often reactive rather than preventative. Yet we continue to witness assaults, even murders, in parks and places where joggers, seniors, and children spend time, crimes that often go unpunished due to a lack of evidence or witnesses. In my book, I introduce a groundbreaking solution: using Visual AGI to develop affordable, intelligent systems that can monitor public spaces, detect criminal behavior, and respond in real time. These systems don’t just record footage, they understand context, recognize patterns of violence, and alert authorities immediately, even when no one else is around. Unlike traditional surveillance, these AI-driven devices can be lightweight, low-cost, and highly adaptive, offering protection in the places where people are most vulnerable. My goal is to inspire innovators to build safer communities through intelligent technology that sees, thinks, and acts with purpose. One expertly combines insights from neuroscience, cognitive science, machine learning, and robotics to build the technical and conceptual foundation for visual AGI, machines that don’t just recognize images but comprehend context, infer meaning, and make decisions as conscious agents. 🔍 What sets this book apart: Full-color illustrations that clarify complex biological and computational concepts Rigorous mathematical equations supporting key models and algorithms In-depth coverage of embodied cognition, neuromorphic vision, and multimodal intelligence Innovative robot designs capable of human-like perception and goal-driven behavior Advanced topics including spiking neural networks, event-based sensors, deep reinforcement learning, and more Thoughtful discussions on ethics, bias, explainability, and human alignment in AGI 🧠 From retina to cortex, neurons to algorithms, this book is not just about computer vision. It’s visual understanding for the next generation of conscious machines. Whether you're a researcher, engineer, or visionary in AI and robotics, this book offers a comprehensive, richly illustrated, and mathematically grounded roadmap for creating machines that truly see, think, and act like humans. Whether you're building the next generation of intelligent agents, designing neuromorphic hardware, or researching the future of AI, this book offers a visionary roadmap for constructing systems that can learn, perceive, and act with purpose in the real world. Note: Some illustrations are placed on separate pages to ensure clear, full-color presentation without crowding the text. I recommend buying the color version as I explained human vision in color along with algorithms, they will not show properly in black and white.
digitalSTS
Author: Janet Vertesi
language: en
Publisher: Princeton University Press
Release Date: 2019-05-07
New perspectives on digital scholarship that speak to today's computational realities Scholars across the humanities, social sciences, and information sciences are grappling with how best to study virtual environments, use computational tools in their research, and engage audiences with their results. Classic work in science and technology studies (STS) has played a central role in how these fields analyze digital technologies, but many of its key examples do not speak to today’s computational realities. This groundbreaking collection brings together a world-class group of contributors to refresh the canon for contemporary digital scholarship. In twenty-five pioneering and incisive essays, this unique digital field guide offers innovative new approaches to digital scholarship, the design of digital tools and objects, and the deployment of critically grounded technologies for analysis and discovery. Contributors cover a broad range of topics, including software development, hackathons, digitized objects, diversity in the tech sector, and distributed scientific collaborations. They discuss methodological considerations of social networks and data analysis, design projects that can translate STS concepts into durable scientific work, and much more. Featuring a concise introduction by Janet Vertesi and David Ribes and accompanied by an interactive microsite, this book provides new perspectives on digital scholarship that will shape the agenda for tomorrow’s generation of STS researchers and practitioners.
Artificial Intelligence
For one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence.