Home » Artificial Intelligence Of Neuromorphic Systems: From Digital, Analogue, Quantum, And Brain-oriented Computing To Hybrid Ai
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Klaus Mainzer

Artificial Intelligence Of Neuromorphic Systems: From Digital, Analogue, Quantum, And Brain-oriented Computing To Hybrid Ai

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€167.40
(Linear and Nonlinear) Pattern Recognition
A01=Klaus Mainzer
Action Potential
Activation Function
Age Group_Uncategorized
Age Group_Uncategorized
Analogue Computer
and Real Weights)
Arithmetical and Analytical Hierarchy
Artificial General Intelligence (AGI)
Author_Klaus Mainzer
automatic-update
Banach-Mazur Computability
Bayesean Reasoning
Black Holes
Brain Research
Category1=Non-Fiction
Category=PBCD
Category=UYQ
Causal Learning
Cellular Neural Networks
ChatGPT
Cognitive Science
Complex (Number) Algorithm
Complex Dynamical System
Computability Over a Ring
Computable Real Numbers
Computational Complexity Over a Ring
Computational Time
Computing Costs
Convolutional Neural Network
COP=Singapore
Decidability Over a Ring
Deep Learning
Delivery_Pre-order
Digital Computability
Edge of Chaos
Energy Efficiency
Entanglement
Environmental Impact
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Finite Automata
General Relativity Theory
Graphic (BSS = Blum
Hopfield Neural Network
Huxley-Hodgkin Equations
Innovation Dynamics
Inverse Imaging Problem
Language_English
Large Language Model (LLM)
Laser Light Model
Lava Language
Learning Algorithms
LIF Neuron
Limits of Digital Computability
Local Activity Principle
Loihi Chip
Mach-Zehnder Interferometer (MZI) Mesh
Machine Learning
Malament-Hogarth Event
Market Competition
Memristor
Memristor Crossbar Architecture
Neural Networks (With Integer
Neuromorphic Computing
Neuromorphic Quantum System
Neuromorphic System
Non-Supervised Learning
Oracle Machine Over a Ring
Oracle Turing Machine
P and NP Problems Over a Ring
P- and Np-problems
PA=Temporarily unavailable
Phase-Change Memory (PCM)
Photonic Crossbar Network
Photonic Micro-Ring Resonator (MRR) Bank
Photonic Neural Network
Photonic Neuromorphic Systems
Photonic Neuron
Photonic Synapses
Price_€100 and above
PS=Forthcoming
Quantum Artificial Intelligence
Quantum Bit
Quantum Circuits
Quantum Complexity
Quantum Computer
Quantum Neural Network
Quantum Operators
Quantum Parallelism
Quantum Pattern Recognition
Rational
Reaction Diffusion Equations
Real (Number) Algorithm
Recognition of Formal Languages
Recurrent Neural Network
Reinforcement Learning
Research Cluster
Research Strategy
Reservoir Neural Network
Responsible AI
Semiconductor
Shor's Quantum Algorithm
Shub
Smale) Machine Over a Ring
SNN Chip
softlaunch
Solvability of Real Optimization Problems
Spiking Neural Network
SpinNNaker Chip
Statistical Learning
Statistical Mechanics
Superposition
Supervised Learning
Sustainability
Tarski's Algorithm
True North Chip
Turing Machine
Undecidability
Unsolvability

Product details

  • ISBN 9789811290077
  • Publication Date: 07 Jan 2025
  • Publisher: World Scientific Publishing Co Pte Ltd
  • Publication City/Country: SG
  • Product Form: Hardback
  • Language: English
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Description
This book argues for neuromorphic systems as a technology of the future, which are oriented towards the energy efficiency of natural brains. Energy efficiency is a dramatic claim in times of environmental and climate challenges which should consider the sustainability goals of the United Nations (UN). Mathematically, neuromorphic computing is connected to analogue ('real') computing, which theoretically overcomes the limits of digital Turing computability. Therefore, the book also considers material sciences and engineering sciences which start to realize neuromorphic computing in hardware. Other mathematical formalisms such as quantum mechanics also open up new solutions (e.g., quantum computing) beyond the limits of digital Turing computability. These research fields are no longer merely of theoretical interest, they promise increasing innovation power of market interest. Nevertheless, neuromorphic computing is connected with deep logical, mathematical, and epistemic questions. Does it open new avenues to Artificial General Intelligence (AGI)? All these tendencies of research and innovation demonstrate that we need more integrated research in the foundations of logic, mathematics, physics, engineering sciences, cognitive science, and philosophy. The book is a plea for this kind of research.