[Netease smart news November 4 news] Yesterday morning, 2017 ThunderWord Zhongkeda embedded artificial intelligence technology forum held in Beijing International Convention Center, from the field of artificial intelligence research institutions, technology alliances, SoC vendors, algorithm vendors, etc. Technical experts discuss the development and commercial application of embedded artificial intelligence.
Sun Li, vice president of Zhongke Chuangda mentioned in the keynote speech that artificial intelligence has very great potential for development in the future, but artificial intelligence needs to be embedded in every scene in depth, combining hardware, sensors, and cloud and terminal, and satisfying A customer's demand or improved user experience can ultimately complete its business model.
Embedded artificial intelligence means that devices do not need to be networked to carry out large-scale calculations in the cloud data center to implement artificial intelligence. Instead, they can be calculated locally, and they can do real-time environment awareness, human-computer interaction, and decision control without networking. In many important application scenarios such as smart driving, scene recognition, and smart home, it is necessary to require “intelligence†to operate independently from the Internet.
In addition, Sun Li also said that embedded artificial intelligence is also facing some problems and challenges, and its development is a more difficult process. Because embedded artificial intelligence has very limited computing power, limited power consumption, and computational problems, this is a problem faced by classical embedded devices. The cloud has a particularly big advantage. It has big data and can be brought together. For example, intelligent transportation in the entire city can only rely on the cloud to handle the work of the entire city, which is different from the level of embedded artificial intelligence processing. Therefore, for some time in the future, this must be a process from the underlying hardware, embedded to edge computing, and to cloud collaboration.
"Specifically which ones are placed on the Edge, which are placed on the cloud, and which are placed on the embedded side, there is no uniform line. This is a problem," said Sun Li. (Don Juan)
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