Since China proposed to develop the big data industry in the 13th Five-Year Plan, the data labeling and auditing industry has developed rapidly in China. It is estimated that the market scale will exceed 3 billion yuan around 2023. At the same time, with the popularization and landing of 5G and the Internet of Things, more data will be generated in the future, which can greatly promote the development of the data label industry. With the development of the industry, not only major Internet companies, but also some established traditional manufacturers are actively deploying their own artificial intelligence fields. For example, Haier refrigerator hopes to use artificial intelligence technology to distinguish which ingredients in the refrigerator are about to deteriorate and expire, and the realization of this function is also inseparable from data labeling. The so-called artificial first, then intelligent, as long as the artificial intelligence industry continues to improve and the functional requirements grow steadily, the data label industry will accompany its long-term development.

Artificial intelligence scene: fingerprint identification

At the same time, in daily life, artificial intelligence involves many fields, such as education, security, finance, transportation, medical care, e-commerce and so on. While joining the artificial intelligence industry as a data annotator, you can get in touch with the future development direction of all walks of life and the real scene of future life earlier. Let us take the lead and open our eyes to see the future development and demand, so as to find more chances of survival in the time difference.

What does the data annotator do?

Data annotation is the process of annotating unprocessed non-institutional raw data (including voice, picture, text, video, etc.). After a lot of human processing, they are converted into machine-readable information. The original data is generally obtained through data collection, and the subsequent data annotation is equivalent to processing the data and then conveying it to artificial intelligence algorithms and models to complete the call.

Semantic segmentation of data annotation

Data annotators annotate images, sounds, words and other raw data in different ways. Common data labeling tasks include classification labeling, frame labeling, area labeling, point labeling and other labeling.