AI Bibliography
AI Bibliography |
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Lee, Y.-L., Tsung, P.-K., & Wu, M. 2018, Techology trend of edge ai. Paper presented at 2018 International Symposium on VLSI Design, Automation and Test (VLSI-DAT). |
| Resource type: Proceedings Article BibTeX citation key: Lee2018a View all bibliographic details  |
Categories: Artificial Intelligence, Computer Science, Data Sciences, Engineering, General, Innovation, Military Science Subcategories: Big data, Cloud computing, Command and control, Cross-domain deterrence, Cyber, Edge AI, Internet of things, JADC2, Machine learning, Mosaic warfare, Neural nets, Q-learning Creators: Lee, Tsung, Wu Publisher: Collection: 2018 International Symposium on VLSI Design, Automation and Test (VLSI-DAT) |
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| Abstract |
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Artificial intelligence (AI), defined as intelligence exhibited by machines, has many applications in today's society, including robotics, mobile devices, smart transportation, healthcare service, and more. Recently, lots of AI investment in both big companies and startups have launched. Besides cloud-based solution, AI on the edge devices (Edge AI) takes the advantages of rapid response with low latency, high privacy, more robustness, and better efficient use of network bandwidth. To enable Edge AI, new embedded system technologies are desired, including machine learning, neural network acceleration and reduction, and heterogeneous run-time mechanism. This paper introduces challenges and technologies trend of Edge AI. In addition, it illustrates edge AI solutions from MediaTek, including the dedicated AI processing unit (APU) and NeuroPilot technology, which provides superior Edge AI ability in a wide range of applications.
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