From shared bicycles to autonomous driving, from smart homes to unattended stores, we have fully entered the “Internet of Things†era from the “people networking†era. In the new era of interconnected intelligence, the exponential explosion of data volume requires not only the analysis of big data in the cloud to translate into insight, but also the higher requirements for extracting analytical data at the edge. Play a key role in the development of networking. As an innovative method for analyzing and mining data values, artificial intelligence can make full use of and release data values, and it also brings new development opportunities to edge computing.
To deal with the challenges posed by the flood of data, edge computing is crucial. First of all, if all the massive data emerging from the blowout type are gathered in the cloud, there is a great demand for bandwidth and a serious computational burden. This requires the necessary filtering and throttling of corresponding data at the edge, and at the same time providing Part of the computing power, so that different data can be reasonably configured to the appropriate storage and computing resources. Second, many Internet of Things scenarios require very high data real-time performance, while edge computing can handle data more agilely and efficiently. In addition, edge computing can also better protect data and meet security needs.
The Internet of Things is an end-to-end system that emphasizes edge computing and does not negate the tremendous role and value of cloud computing. Cloud computing and edge computing are two different characteristics of data processing methods. Edge computing deals with local data. Forming complete insight into data also requires comprehensive analysis of data collected at different edges in the cloud. Reciprocal complementarity. Edge computing is an inevitable result of the intelligent extension of cloud intelligence to the end. The future trend is not to replace cloud computing with edge computing, but rather to achieve benign collaboration between the two to jointly promote the development of the Internet of Things.
We also see that edge-side load consolidation finds a breakthrough for artificial intelligence in edge computing applications. "Connecting" to the Internet will generate a huge amount of data. Data will become new oil. Artificial intelligence will provide a new driving force for data collection, analysis and value-added, and it will also provide new momentum for the development of the entire Internet of Things. Virtualization technology integrates independent loads on different devices onto a unified high-performance computing platform, enabling each subsystem to effectively share computing, storage, and network resources while maintaining certain independence. Edges are load-integrated and the resulting nodes are both a summary node of data and a control center. Artificial intelligence can collect analysis data at nodes, and can also extract insights from nodes to make decisions.
How to apply artificial intelligence to the edge? Network optimization will be one of the key technologies. Intel believes that network optimization can be achieved through low bit, pruning and parameter quantification. The low bit means that the storage and computational load is reduced by reducing the accuracy without affecting the final identification. Pruning means cutting unnecessary computational requirements, thereby reducing computational complexity. Parametric quantification refers to clustering based on the characteristics of a parameter and expressing it with relatively simple symbols or numbers, thereby reducing the need for artificial intelligence for storage.
The combination of edge computing and artificial intelligence to promote the development of the Internet of Things is a long-term process. Intel will accelerate the development of edge computing from the end-to-end platform strategy, in-depth cooperation in the vertical industry, and open ecosystem construction to promote the entire process of the Internet of Things.
As Intel CEO Ke Zaiqi said, data is the most important force in today's world. The data flow brought by smart connected devices is the lifeblood of future technological innovation. Intel is committed to collaborating with industry partners through cloud-to-edge computing solutions, bringing AI to the edge, accelerating the development of the Internet of Things, harnessing the torrents of data, and unlocking the value of data.
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