From Artificial Intelligence to Brain Intelligence

The field of AI is not new to researchers, as its foundations were established in the 1950s. After many decades of inattention, there has been a dramatic resurgence of interest in AI, fueled by a confluence of several factors. The benefits of decades of Dennard scaling and Moore's law miniaturi...

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Bibliographic Details
Main Author Joshi, Rajiv
Format eBook
LanguageEnglish
Published River Publishers 2020
Routledge
Edition1
Subjects
Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
General Engineering & Project Administration
General References
Synaptic
Lasso
Artificial intelligence – Congresses
RRAM
Deep Neural Networks
Ai Algorithm
IoT
Intelligence artificielle – Congrès
RRAM Device
SNR
Training Error
Sparse Coding
In-memory Computation
NN Model
Keyword Spotting
Synaptic Plasticity
Exact Bayesian Inference
Anniversary
Vector Matrix Multiplication
AI Research
IBM Research
Neuromorphic Computing
IEEE Circuit
In-memory Computing
Artificial intelligence
Thermodynamic Computing
Arm
RC System
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Cover

Table of Contents:
  • Introduction 7 1. Research Directions in AI Algorithms and Systems 11 2. An Arm Perspective on Hardware Requirements and Challenges for AI 27 3. The New Era of AI Hardware 55 4. AI and the Opportunity for Unconventional Computing Platforms 67 5. Thermodynamic Computing 85 6. Brain-like Cognitive Engineering Systems 101 7. BRAINWAY and nano-Abacus Architecture: Brain-inspired Cognitive Computing Using Energy Efficient Physical Computational Structures, Algorithms and Architecture Co-Design 135 8. The Loihi Neuromorphic Research Chip 161 9. RRAM Fabric for Neuromorphic Computing Applications 175 About the Editors 191 About the Authors 199
  • Title Page Introduction Table of Contents 1. Research Directions in AI Algorithms and Systems 2. An ARM Perspective on Hardware Requirements and Challenges for AI 3. The New Era of AI Hardware 4. AI and the Opportunity for Unconventional Computing Platforms 5. Thermodynamic Computing 6. Brain-Like Cognitive Engineering Systems 7. BRAINWAY and Nano-Abacus Architecture: Brain-Inspired Cognitive Computing Using Energy Efficient Physical Computational Structures, Algorithms and Architecture Co-Design 8. The Loihi Neuromorphic Research Chip 9. RRAM Fabric for Neuromorphic Computing Applications About the Editors About the Authors