AI: from deep learning to in-memory computing
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...
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| Main Author | |
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| Format | Conference Proceeding |
| Language | English |
| Published |
SPIE
26.03.2019
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| Online Access | Get full text |
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| Summary: | 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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| Bibliography: | Conference Date: 2019-02-24|2019-02-28 Conference Location: San Jose, California, United States |
| ISBN: | 9781510625655 1510625658 |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.2517237 |