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
Corporate Author: AI Compute Symposium Yorktown Heights, N.Y.)
Other Authors: Joshi, Rajiv., Ziegler, Matt., Kumar, Arvind ., Alarcón, Eduard.
Format: eBook
Language: English
Published: Gistrup, Denmark : River Publishers, [2020]
Series: Tutorials in circuits and systems.
Subjects:
Artificial intelligence > Congresses.
elektronické knihy
electronic books
ISBN: 9788770221245
8770221243
9781003338215
1003338216
9781000795820
1000795829
1000792501
9781000792508
9788770221238
8770221235
Physical Description: 1 online resource (207 pages) : color illustrations

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Table of contents

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111 2 |a AI Compute Symposium  |n (1st :  |d 2018 :  |c Yorktown Heights, N.Y.)  |j author. 
245 1 0 |a From artificial intelligence to brain intelligence /  |c Rajiv Joshi, Matthew Ziegler, Arvind Kumar, Eduard Alarcon, [editors]. 
264 1 |a Gistrup, Denmark :  |b River Publishers,  |c [2020] 
300 |a 1 online resource (207 pages) :  |b color illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Tutorials in circuits and systems 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a 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 miniaturization, coupled with the rise of highly distributed processing, have led to massively parallel systems well suited for handling big data. The widespread availability of big data, necessary for training AI algorithms, is another important factor. Finally, the greatly increased compute power and memory bandwidths have enabled deeper networks and new algorithms capable of accuracy rivaling that of human perception. Already AI has shown success in many diverse areas, including finance (portfolio management, investment strategies), marketing, health care, transportation, gaming, defense, robotics, computer vision, education, search engines, online assistants, image/facial recognition, anomaly detection, spam filtering, online customer service, biometric sensors, and predictive maintenance, to name a few. Despite these remarkable advances, the human brain is still superior in many ways - including, notably, energy efficiency and one-shot learning - giving researchers new areas to explore. In summary, AI research and applications will continue with vigor in software, algorithms, and hardware accelerators. These exciting developments have also brought new questions of ethics and privacy, areas which must be studied in tandem with technological advances. To continue the success story of AI, the AI Compute symposium was launched with the sponsorship of IBM, IEEE CAS and EDS for the first time. The aim of this publication is to compile all the materials presented by the renowned speakers in the symposium into a book format, serving as a learning tool for the audience. This book contains two broad topics: general AI advances (chapters 1-5) and neuromorphic computing directions (chapters 6-9). Technical topics discussed in the book include: Research Directions in AI algorithms and systems An ARM perspective on hardware requirements and challenges for AI The new Era of AI hardware AI and the Opportunity for Unconventional Computing Platforms Thermodynamic Computing Brain-like cognitive engineering system BRAINWAY and Nano - Abacus architecture: Brain-inspired Cognitive Computing using Energy Efficient Physical Computational Structures, Algorithms and Architecture Co-Design Applying Lessons from Nature for Today's Computing Challenges Emerging Memories - RRAM Fabric for Neuromorphic Computing Applications. 
505 0 |a 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. 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Artificial intelligence  |v Congresses. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Joshi, Rajiv. 
700 1 |a Ziegler, Matt. 
700 1 |a Kumar, Arvind . 
700 1 |a Alarcón, Eduard. 
776 0 8 |i Print version:  |a AI Compute Symposium (1st : 2018 : Yorktown Heights, N.Y.).  |t From artificial intelligence to brain intelligence.  |d Gistrup, Denmark : River Publishers, [2020]  |z 9788770221238  |w (OCoLC)1109791447 
830 0 |a Tutorials in circuits and systems. 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpFAIBI008/from-artificial-intelligence?kpromoter=marc  |y Full text 

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