Author: Alex James
Publisher: CRC Press
ISBN: 8770047243
Category : Technology & Engineering
Languages : en
Pages : 340
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Book Description
Intelligence in Chips: Integrated Sensors and Memristive Computing is an authoritative resource that navigates the exciting landscape of in-memory computing, neuromorphic circuits, and memristive technologies. This book curates expert insights from leading researchers like Abu Sebastian, Alex James, Alon Ascoli, Arindam Basu, Cory Merkel, Fernando Corinto, Jason Eshraghian, Rainer Waser, Spiros Nikolaidis, Stephan Menzel, and Vishal Saxena, highlighting some of the important contributions in the field. Through a comprehensive collection of talks, readers will gain deep insights into how memristive neural computing is revolutionizing artificial intelligence. The book covers the latest innovations in memristor array computing, brain-inspired circuits, neuromorphic event-driven vision, bio-inspired computing, and nonlinear phenomena in biological systems. Each chapter is authored by a distinguished expert, offering a multi-perspective analysis on how emerging technologies are pushing the boundaries of edge-AI and mixed-signal hardware. Whether you're a researcher, engineer, or student, this book is an essential guide that explores the confluence of circuit theory, artificial intelligence, and memristor technology, providing readers with practical methodologies and visionary outlooks for the future.
Author: Alex James
Publisher:
ISBN: 9788770228343
Category : Computers
Languages : en
Pages : 0
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Book Description
The book covers the latest innovations in memristor array computing, brain-inspired circuits, neuromorphic event-driven vision, bio-inspired computing, and nonlinear phenomena in biological systems.
Author: professor ibrahim elnoshokaty
Publisher: ibrahim elnoshokaty
ISBN:
Category : Computers
Languages : en
Pages : 400
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Book Description
Consciousness Genesis In Artificial Intelligence" by Professor Ibrahim El Noshokaty, I can provide a preliminary review that outlines the structure and content captured within the initial pages available to me. Below is an overview based on the table of contents and some introductory text: Title: Consciousness Genesis In Artificial Intelligence Author: Professor Ibrahim El Noshokaty Overview: The academic work delves into the complex topic of artificial intelligence and its relation to human-like consciousness. It explores whether AI can be creative, how numerical data and programming languages can emulate human sensory experiences and emotions, and the potential implications of such advances. Chapters and Themes: Introduction and Fuzzy Logic System: Initiates the discussion with fundamental questions about AI creativity and creation, followed by the exposition of fuzzy logic systems. Existential Threat and AI in Hollywood: Examines AI's potential to disrupt industries such as Hollywood, the feasibility of generative AI in original content production, and copyright issues in AI outputs. Hierarchical Fuzzy Deep Learning: Discusses advanced AI techniques to enhance learning and decision making, addressing the concepts of consciousness and fuzzy logic in AI. Algorithms for Modern Fuzzy Logic Systems: Delves into the technical aspects of fuzzy logic systems and algorithms, highlighting methods for system optimization. Development of Conscience in AI: Contemplates the moral aspects and decision-making capabilities of AI systems, along with the incorporation of ethical considerations and human values. Artificial Cognition: Analyzes the notion of machine learning and cognition, transparency within AI mechanisms, and the ethical implications of artificial minds. Artificial Sensations: Explores the development of AI systems capable of mimicking human senses and responses, using advanced materials and devices. Artificial Brain: Concludes with an investigation into mimicking human brain function within AI systems and the potential capacity for AI to evolve with environmental interaction. The work appears to be an exploration of the frontier where technology meets human cognition, emotion, and ethical considerations. The book may offer expertise in several domains, including AI algorithms, deep learning, neuromorphic computing, and the philosophical implications of imbuing AI with aspects of human consciousness. The manuscript's purpose is likely to probe the theoretical boundaries of AI and its future potential, as well as to identify and confront some of the ethical dilemmas that arise as AI systems become increasingly sophisticated. This preliminary review only scratches the surface of what the book contains. For a full review, including critical analysis and conclusions, it would be necessary to read the document in its entirety. If you have any specific areas you'd like me to focus on or if there are particular chapters you want to examine in more detail, please let me know.
Author: Alex James
Publisher: CRC Press
ISBN: 1000873757
Category : Technology & Engineering
Languages : en
Pages : 250
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Book Description
Memristors have provided a new direction of thinking for circuit designers to overcome the limits of scalability and for thinking of building systems beyond Moore’s law. Over the last decade, there has been a significant number of innovations in using memristors for building neural networks through analog computing, in-memory computing, and stochastic computing approaches. The emergence of intelligent integrated circuits is inevitable for the future of integrated circuit applications. This book provides a collection of talks conducted as part of the IEEE Seasonal School on Circuits and System, having a focus on Intelligence in Chip: Tomorrow of Integrated Circuits. Technical topics discussed in the book include: Edge of Chaos Theory Explains Complex Phenomena in Memristor Circuits Analog Memristive Computing Designing energy efficient neo-cortex system with on-device learning Integrated sensors Challenges and recent advances in NVM based Neuromorphic Computing ICs In-memory Computing (for deep learning) Deep learning with Spiking Neural Networks Computational Intelligence for Designing Integrated Circuits and Systems Neurochip Design, Modeling, and Applications
Author: Paul R. Prucnal
Publisher: CRC Press
ISBN: 1498725244
Category : Science
Languages : en
Pages : 445
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Book Description
This book sets out to build bridges between the domains of photonic device physics and neural networks, providing a comprehensive overview of the emerging field of "neuromorphic photonics." It includes a thorough discussion of evolution of neuromorphic photonics from the advent of fiber-optic neurons to today’s state-of-the-art integrated laser neurons, which are a current focus of international research. Neuromorphic Photonics explores candidate interconnection architectures and devices for integrated neuromorphic networks, along with key functionality such as learning. It is written at a level accessible to graduate students, while also intending to serve as a comprehensive reference for experts in the field.
Author: Qing Wan
Publisher: John Wiley & Sons
ISBN: 3527349790
Category : Technology & Engineering
Languages : en
Pages : 258
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Book Description
Explore the cutting-edge of neuromorphic technologies with applications in Artificial Intelligence In Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics, a team of expert engineers delivers a comprehensive discussion of all aspects of neuromorphic electronics designed to assist researchers and professionals to understand and apply all manner of brain-inspired computing and perception technologies. The book covers both memristic and neuromorphic devices, including spintronic, multi-terminal, and neuromorphic perceptual applications. Summarizing recent progress made in five distinct configurations of brain-inspired computing, the authors explore this promising technology’s potential applications in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. The book also includes: A thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms Comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviors Practical discussions of neuromorphic devices based on chalcogenide and organic materials In-depth examinations of neuromorphic computing and perceptual systems with emerging devices Perfect for materials scientists, biochemists, and electronics engineers, Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics will also earn a place in the libraries of neurochemists, neurobiologists, and neurophysiologists.
Author: Satvik Vats
Publisher: Bentham Science Publishers
ISBN: 9815305379
Category : Computers
Languages : en
Pages : 303
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Book Description
This book demonstrates several use cases of how artificial intelligence (AI) and machine learning (ML) are revolutionizing problem-solving across various industries. The book presents 18 edited chapters beginning with the latest advancements in human-AI interactions and neuromorphic computing, setting the stage for practical applications. Chapters focus on AI and ML applications such as fingerprint recognition, glaucoma detection, and lung cancer identification using image processing. The book also explores the role of AI in professional operations such as UX design, event detection, and content analysis. Additionally, the book includes content that examines AI's impact on technical operations wireless communication, VLSI systems, and advanced manufacturing processes. Each chapter contains summaries and references for addressing the needs of beginner and advanced readers. This comprehensive guide is an essential resource for anyone seeking to understand AI's transformative role in modern problem-solving in professional industries.
Author: Erika Covi
Publisher: Frontiers Media SA
ISBN: 2889760006
Category : Science
Languages : en
Pages : 244
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Book Description
Author: Vivienne Sze
Publisher: Springer Nature
ISBN: 3031017668
Category : Technology & Engineering
Languages : en
Pages : 254
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Book Description
This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.
Author: Jordi Suñé
Publisher: MDPI
ISBN: 3039285769
Category : Technology & Engineering
Languages : en
Pages : 244
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Book Description
Artificial Intelligence (AI) has found many applications in the past decade due to the ever increasing computing power. Artificial Neural Networks are inspired in the brain structure and consist in the interconnection of artificial neurons through artificial synapses. Training these systems requires huge amounts of data and, after the network is trained, it can recognize unforeseen data and provide useful information. The so-called Spiking Neural Networks behave similarly to how the brain functions and are very energy efficient. Up to this moment, both spiking and conventional neural networks have been implemented in software programs running on conventional computing units. However, this approach requires high computing power, a large physical space and is energy inefficient. Thus, there is an increasing interest in developing AI tools directly implemented in hardware. The first hardware demonstrations have been based on CMOS circuits for neurons and specific communication protocols for synapses. However, to further increase training speed and energy efficiency while decreasing system size, the combination of CMOS neurons with memristor synapses is being explored. The memristor is a resistor with memory which behaves similarly to biological synapses. This book explores the state-of-the-art of neuromorphic circuits implementing neural networks with memristors for AI applications.
