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26 March 2019 AI: from deep learning to in-memory computing
Hsiang-Lan Lung
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Proceedings Volume 10959, Metrology, Inspection, and Process Control for Microlithography XXXIII; 109591J (2019) https://doi.org/10.1117/12.2517237
Event: SPIE Advanced Lithography, 2019, San Jose, California, United States
Abstract
In the past few years, Artificial Intelligence (AI) has been a subject of intense media hype. Machine learning, deep learning (DL), and AI come up in countless articles, often outside of technology-minded publications. As the AI hype keeps growing, it is important to be able to recognize the signal in the noise, to tell apart world-changing developments from what are merely over-hyped press releases. This paper tries to explain how deep learning is working and how GPU (Graphic Processing Unite) can make it a reality. Finally, in-memory computing (IMC) for DL is introduced to point out future high performance and low power DL hardware development direction.
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Hsiang-Lan Lung "AI: from deep learning to in-memory computing", Proc. SPIE 10959, Metrology, Inspection, and Process Control for Microlithography XXXIII, 109591J (26 March 2019); https://doi.org/10.1117/12.2517237
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Cited by 2 scholarly publications.
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KEYWORDS
Artificial intelligence
Neurons
Machine learning
Image filtering
Evolutionary algorithms
Matrix multiplication
Neural networks
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