Artificial intelligence (AI) can be said to be a big leap in the era of scientific and technological information. It has a certain human-like logic, but also has powerful computing power and data storage capabilities. Although the industry is not in a good state of investment, AI technology is still considered to be the next big breakthrough to bring huge economic benefits and improve social productivity.
In fact, in the past two years, concepts such as AI, robotics, and autonomous driving have become the most advanced cultural and political terms. Many studies believe that we are currently at such a turning point: computing power is faster and faster, data sources are more abundant, deep learning algorithms are maturing, professional hardware (chip) and open source code are gradually emerging, more and more practical Sexual AI came into being.
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The following are the dry goods presented by the smart internal reference:
The three main pushers behind AI: data, chips, algorithms
1. Mobile networks are popularizing data structuring or outbreaks.
Data can be said to be the key to machine learning. The ubiquitous connectivity of devices around the world, including mobile devices and the Internet of Things, has led to a proliferation of unstructured data, which means that machine learning algorithms can be used to simulate, train, and test data sources more abundantly.
For example, the Tesla Connected Cars have been used. As of now, Tesla has a total journey of 780 million miles, and the company's platform-driven extra-connected cars have also traveled 1 million miles. In terms of wireless operations, Verizon announced new transmission standards in August, making remote sensors connect to cloud software faster. At the same time, the new 5G network will also facilitate the transmission of data. IDC expects that the average annual data volume will reach 44 Zebytes (that is, 44 trillion bytes) by 2020, and the compound annual growth rate will reach 141% in the next five years. Big data technology will gradually penetrate the practical field.
At the same time, the cost of building large-scale databases and cloud processing technologies on mobile networks is also decreasing. Smart things have also been cited in the 111th Intelligent Internal Reference to the World Economic Forum: It is expected that 90% of people will have unlimited free data storage supported by advertisers in less than three years. This is because the cost of hard drives continues to decline, stimulating the creation of data. In fact, nearly 90% of the data was created in the past two years.
* IDC research data volume growth trend
2, GPU application trend new hardware is more suitable for parallel structure
GPUs are considered to be low-cost, high-computing processing units, especially for cloud services and new neural network architectures, which increase accuracy and computational speed. The GPU-based parallel architecture allows for a faster machine learning training system that is far superior to the currently widely used CPU-based data architecture. In addition, with an additional graphics card network, the GPU system can speed up iterations for more accurate and fast training.
*GPU-based cloud computing
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