People who care about cutting-edge technology have an experience, that is, the recent technological terms are particularly large, especially when the concept of cloud computing, Internet of things, artificial intelligence, big data, and even blockchain are combined. I get lost. In order to keep everyone's heads and minds clear when faced with various situations, this article focuses on the three most frequently occurring concepts: cloud computing, internet of things, and artificial intelligence. Know the concept. 1 Internet of Things I suspect that readers of the internet of things capital theory are most familiar with this term. Yes, the essence of the Internet of Things lies in the “Internet of Everythingâ€. Looking directly at these four words may be somewhat abstract. In contrast to the Internet, we can imagine the Internet of Things as an extension of the Internet. The terminals of the Internet are computers (PCs, servers). All the programs we run are nothing but computers and networks. Data processing and data transmission. The nature of the Internet of Things is still the Internet, but terminal devices are not limited to computers, but more embedded computer systems and their associated sensors, such as wearable devices, environmental monitoring devices, and virtual reality devices, are more diverse in form, but they all have The hardware or product is connected to the Internet and data interaction occurs. This forms the Internet of Things. The standard IoT system can be roughly divided into four levels: Perceptual Recognition Layer, Network Construction Layer, Management Service Layer, and Comprehensive Application Layer. 2 cloud computing On the whole, Cloud Computing is the product of the convergence of traditional computing and network technologies such as distributed computing, parallel computing, utility computing, network storage, virtualization, load balancing, and hot standby redundancy. In fact, the initial cloud computing is more inclined to distributed computing, and it can simply be considered as separating the calculation tasks and merging the calculation results. After solving the problems of efficiency and calculation, people gradually discovered that this capability can also be provided for external use. Therefore, public cloud computing emerged and the computer's computing power was sold directly on the Internet. It often has the following forms: IaaS: Infrastructure as a service, such as hardware server rental. PaaS: platform-as-a-service, such as custom development of software. SaaS: Software as a service, such as Google. Traditional applications are becoming more and more complicated: more concurrent numbers, faster computing power, stronger stability, etc. In order to support these ever-increasing demands, enterprises are in hardware devices, software configuration, and management and maintenance personnel. The costs and expenses are rising. So bigger, faster and stronger cloud computing has emerged. After deploying applications to the cloud, you don’t have to pay attention to those vexing hardware and software problems that will be solved by the cloud service provider’s professional team. We also see two characteristics of cloud computing that are different from traditional computing platforms: 1. Computing resources are virtualized and purchased in terms of computing power. 2, elastic computing capabilities of cloud computing capabilities. When we purchase services on Alibaba Cloud, Tencent Cloud and other platforms, it will be clear that your bills are determined by these two characteristics. 3 artificial intelligence Artificial intelligence is not only a concept within the scope of computer science, but it is a discipline that studies certain thinking processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.) that make computers simulate people, mainly including principles and manufacturing of computer-implemented intelligence. Computers that are similar to human brain intelligence enable computers to implement higher-level applications. The whole process involves computer science, psychology, philosophy and linguistics. The simplest idea of ​​artificial intelligence is to let the machine achieve the task that only humans can accomplish, and its core is a variety of algorithms. In terms of natural language processing, speech recognition, expert systems, and computer vision, artificial intelligence has begun to affect our lives. Applications such as Apple Siri, Baidu Duwei, Microsoft Xiaobing and other intelligent assistants and smart chat apps to Google's Alpha Dog and driverless vehicles are all artificial intelligence. From the perspective of classification, pattern recognition, machine learning, data mining, and intelligent algorithms are currently the four major branches of artificial intelligence; from the composition point of view, there are two necessary prerequisites that cannot be ignored. To train a huge neural network (NN) Have big data. 4 The three links The above mentioned that the Internet of Things is characterized by a large number of computing nodes and terminals. Unlike ordinary software services, the demand for computing power of the Internet of Things when dealing with massive amounts of data is very high, and cloud computing can just take up this role. . Of course, cloud computing can also be used directly as the brain of a computing network, playing a pivotal role in the Internet of Things. On the cloud computing platform, the key factor in determining the final performance is the application of various algorithms, which is also the role of artificial intelligence. Artificial intelligence is also inseparable from big data. At the same time, it is also relying on cloud computing platforms to complete deep learning and evolution. At the same time, although the core of artificial intelligence is the algorithm, it is based on a large amount of historical data and real-time data to predict the future. Therefore, the importance of large amounts of data to artificial intelligence is self-evident. The more data it can process and learn from, the higher the accuracy of its prediction. Artificial intelligence requires continuous data inflows, and the mass of nodes and applications generated by the Internet of Things are also sources. On the other hand, for IoT applications, the real-time analysis of artificial intelligence can help companies improve their operating performance and find new business scenarios through data analysis and data mining. At this level, the Internet of Things is the goal, and artificial intelligence is the way to achieve it. The realization of the Internet of Things is inseparable from the development of artificial intelligence. AI calculations, processing, analysis, and planning issues, while the Internet of Things focuses on the landing, transmission, and control of solutions that complement each other. Therefore, we can see that through the Internet of Things, we collect and collect vast amounts of data stored on cloud platforms, and through big data analysis, even higher forms of artificial intelligence provide better services for human production activities and living needs. Artificial intelligence is the result of a combination of program algorithms and big data. You can simply think of settings: artificial intelligence = cloud computing + big data (mostly from the Internet of Things). As the Internet of Things is rolled out in life, it will become the largest and most accurate source of big data.
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