Emerging Hybrid Models for Neuromorphic AI by Surbhi Bhatia Khan(.PDF)
File Size: 37.7 MB
Emerging Hybrid Models for Neuromorphic AI and Quantum Computing by Surbhi Bhatia Khan, Shikha Khullar, Muhammad Attique Khan, Udit Mamodiya, Manju Lata Joshi
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Overview: As Artificial Intelligence (AI) systems confront the limits of classic computing, emerging models that integrate Neuromorphic AI with Quantum Computing create a compelling path forward. Neuromorphic tools inspire the dynamics of the human brain, while quantum computing promises speedups for certain classes of complex optimization and probabilistic problems. By uniting these models, hybrid neuromorphic–quantum models aim to overcome efficiency and learning constraints that challenge each approach in isolation. Emerging Hybrid Models for Neuromorphic AI and Quantum Computing explores two technological revolutions, AI, powered by intricate networks of artificial neurons, and Quantum Computing, which harnesses the counterintuitive principles of quantum mechanics. It examines the future of computation within sophisticated hybrid models. Covering topics such as AI, Quantum Computing, and hybrid models, this book is an excellent resource for software developers, technology developers, business organizations, academicians, researchers, and graduate students.
Genre: Non-Fiction > Tech & Devices
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