In 2016, a prosperous man-machine battle, Google's DeepMind's Go program AlphaGo won with a score of 5 games and 4 wins, set off the people of the world, especially the Chinese people, the unprecedented enthusiasm for AI, the concept of deep learning Also from the laboratory, textbooks for the first time into the general public's vision. Many people have learned the charm of AI for the first time through the Internet. However, the application of AI is far more than that of Internet companies. It has penetrated into various industries such as security, public security ISV, research institutions, finance, and medical care.
Throughout 2017, the most mentioned word in the Internet circle must be “artificial intelligenceâ€, and this “artificial intelligence†is not only the AlphaGo that will play chess in 2016, it has become an omnipotent assistant steward. Can talk to you (smart audio), can help the public to arrest people (face recognition), and also start to grab the old driver's work (unmanned). Today's artificial intelligence is no longer the "it" of more than 70 years ago.
Made in China 2025 - Intelligent Manufacturing EngineeringIn the 2025 China manufacturing strategy, smart manufacturing is a very important goal. By 2020, the level of intelligence in the key areas of manufacturing will increase significantly. The operating cost of pilot demonstration projects will be reduced by 30%, the production cycle will be shortened by 30%, and the defective product rate will be reduced by 30%. By 2025, the key areas of manufacturing will be fully intelligent, the operating costs of pilot demonstration projects will be reduced by 50%, the production cycle will be shortened by 50%, and the defective product rate will be reduced by 50%.
Intelligent manufacturing engineering promotes the intelligent transformation of manufacturing industry and promotes the industry to the mid-to-high end; the high-end equipment innovation project focuses on breaking through the industrial application of a number of major equipments and provides advanced production tools for upgrading various industries. Focus on the "Five, Three, and Fifty" key tasks, namely: to overcome five key technical equipments, consolidate the three foundations of intelligent manufacturing, foster and promote five new intelligent manufacturing models, and promote the integration of intelligent manufacturing complete sets of equipment in ten key areas.
So how do you accelerate the development of smart manufacturing? Realize a wide range of industry applications as soon as possible?
The view of fault-tolerant server experts believes that the development of artificial intelligence with edge computing will strongly promote the process of manufacturing intelligence and make artificial intelligence more "smart".
At present, trained artificial intelligence systems have surpassed humans in specific areas, and behind the rapid development of related software technologies, the use of edge computing solutions has made artificial intelligence more powerful. The Internet of Things (IoT) is expected to evolve into AIOT (AI+IoT). The blooming of intelligent robots may still be just the beginning. The edge computing power of artificial intelligence terminals will bring more value to people.
The fault-tolerant edge computing team believes that artificial intelligence terminals based on edge computing solutions will bring changes in all walks of life, thus changing the future direction. The hardware architecture of traditional artificial intelligence computing mainly includes a central processing unit (CPU), a graphics processing unit (GPU), and a field programmable array (FPGA).
Dedicated artificial intelligence systems in specific fields, due to clear application background requirements, deep domain knowledge, and simple and feasible model calculation, the intelligence level of individual tests can now surpass human intelligence and achieve concrete results in many fields. The technical challenge today is how to develop low-power, high-accuracy cognitive computing, including new computing architecture circuit design, algorithms, and so on. In the future, artificial intelligence will accelerate various neural network algorithms including ConvoluTIon Neutral Network and Recursive Neutral Network by specific algorithm accelerators. Edge computing drives artificial intelligence to achieve transformative development, which is a step that must be achieved to achieve intelligent manufacturing.
Although the current mainstream research in the field of artificial intelligence is artificial intelligence computing on the server, there are more and more applications that need to perform real-time operations on the terminal. This technology is the application of edge computing. This trend will change the design and technical requirements of the overall artificial intelligence computing system architecture.
Fault-tolerant experts believe that the continuous expansion of artificial intelligence on the edge side is one of the key links to control data torrents and an important trend in the future development of the Internet of Things. With the rapid development of artificial intelligence, massive data needs to analyze and extract insights quickly and efficiently, which greatly enhances the need for edge computing.
Two issues are worth considering. The first is the edge-side trend toward load consolidation. Many of the previous data are structured data that can be maintained and managed through an Excel spreadsheet or a simple relational database. However, in the future, more and more unstructured data will need to be processed to discover the internal correlation, which requires edge computing and artificial intelligence technology.
Second, build an end-to-end system of edge collaboration. In an edge-to-end system where edges are coordinated, because the power consumption, computing performance, and cost of different network sources are different, there are often specific requirements when selecting a hardware architecture. Provide different architecture solutions according to user needs, including Xeon processor, Xeon Phi processor, Movidius/Nervana neural network processor and hardware platforms such as FPGA, network and storage technology, as well as a variety of software tools and function libraries. Optimize the open source framework to allow them to make their own choices.
Fault-tolerant servers and fault-tolerant software, with ftServer's Lock Step and everRun Check Point technologies, have unique advantages in real-time, reliability, security and privacy, based on a wide range of industrial automation (IA) customer applications. Helping the development of innovative technologies in the edge computing industry.
Fault-tolerant servers, under the goal of China Manufacturing 2025, assist the Edge Computing Industry Alliance to establish an open and innovative platform, industry practice and demonstration platform. Join hands with artificial intelligence technology to accelerate the process of manufacturing China 2025.
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