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Books > Computing & IT > Applications of computing > Artificial intelligence
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Applied Edge AI - Concepts, Platforms, and Industry Use Cases (Hardcover)
Loot Price: R3,176
Discovery Miles 31 760
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Applied Edge AI - Concepts, Platforms, and Industry Use Cases (Hardcover)
Expected to ship within 12 - 17 working days
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The strategically sound combination of edge computing and
artificial intelligence (AI) results in a series of distinct
innovations and disruptions enabling worldwide enterprises to
visualize and realize next-generation software products, solutions
and services. Businesses, individuals, and innovators are all set
to embrace and experience the sophisticated capabilities of Edge
AI. With the faster maturity and stability of Edge AI technologies
and tools, the world is destined to have a dazzling array of
edge-native, people-centric, event-driven, real-time,
service-oriented, process-aware, and insights-filled services.
Further on, business workloads and IT services will become
competent and cognitive with state-of-the-art Edge AI
infrastructure modules, AI algorithms and models, enabling
frameworks, integrated platforms, accelerators, high-performance
processors, etc. The Edge AI paradigm will help enterprises evolve
into real-time and intelligent digital organizations. Applied Edge
AI: Concepts, Platforms, and Industry Use Cases focuses on the
technologies, processes, systems, and applications that are driving
this evolution. It examines the implementation technologies; the
products, processes, platforms, patterns, and practices; and use
cases. AI-enabled chips are exclusively used in edge devices to
accelerate intelligent processing at the edge. This book examines
AI toolkits and platforms for facilitating edge intelligence. It
also covers chips, algorithms, and tools to implement Edge AI, as
well as use cases. FEATURES The opportunities and benefits of
intelligent edge computing Edge architecture and infrastructure
AI-enhanced analytics in an edge environment Encryption for
securing information An Edge AI system programmed with Tiny Machine
learning algorithms for decision making An improved edge paradigm
for addressing the big data movement in IoT implementations by
integrating AI and caching to the edge Ambient intelligence in
healthcare services and in development of consumer electronic
systems Smart manufacturing of unmanned aerial vehicles (UAVs) AI,
edge computing, and blockchain in systems for environmental
protection Case studies presenting the potential of leveraging AI
in 5G wireless communication
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