With the development of artificial intelligence (AI), human society enters into a new era. AI is changing our world and improving our life and work quality. The impact is enormous. The widespread use of smart home products and the development and application of driverless technology, can be attributed to the improvement of AI training data service capacity, in addition to the rapid development of deep learning technology.
A few years ago, IBM Watson defeated human in the knowledge quiz game Jeopardy, which was very sensational. Among AI application examples, machine and human interaction has been considered as the key direction. The human-computer conversational interaction requires the AI machines to be able to listen and speak, as well as understanding the meaning of the language. “Natural language processing" technology makes it possible to interact freely with machines, and enables AI to "understand" the natural speech and respond in a meaningful way. But to develop such products, in order to accurately understand the diversified expression of needs, developers often need to provide adequate training data for the dialogue system, to enable the model to fully understand the language expression habits of users. However, the plan of training data collection directly affects the research and development results, and the high collection cost also sets high threshold for R&D enterprises.
In another example of AI application, computer vision is making great progress, and has been applied in large-scale in the fields of driverless vehicles, navigation, robotics, pattern recognition, and medical diagnosis. Similarly, computer vision enables machines, through complex algorithms, to be trained to recognize the image of a variety of terrain, people and objects, to "see" things, and to make judgment. Besides the core algorithm, and computing power upgrade, the support of large amount of training data is the key to these applications. The cost of data collection and the way to obtain valuable information in the data are also difficulties to be solved.
AI applications are rapidly changing and subverting the development of various industries, but from a technical point of view, the application of AI is inseparable from the three core capabilities: computing power, core algorithm and large-scale data.
Equipped with industry-leading AI training data service capability, and relying on its professional experience accumulated over the years, Datatang provides data service technology solutions for enterprise developers. Through professional technical guidance, it provides effective data collection and annotation solutions for AI research of enterprises, and help corporate customers largely reduce the time and cost of product development. Furthermore, Datatang’s intelligent annotation tools largely improve work efficiency, reduce cost and time of large-scale data production by applying cloud data factory pipeline model. The intelligent machine quality inspection plus three rounds quality inspection conducted by professional team ensure the quality of data delivery, while greatly shortening the delivery time. “Fast speed, high quality and low cost” is our motto.
At present, Datatang has provided data services to well-known domestic and foreign companies such as Baidu, Tencent, Alibaba, Huawei, Ping’an, Microsoft, Apple, Facebook, Intel, NEC, Canon, Samsung, and many other domestic and foreign innovation startup companies. Datatang has internationally leading technologies in unstructured data processing and big data cloud service. More than 50% of its employees are engaged in innovation, research and technology development, and provide smarter data service to customers by building AI capability service systems.
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