Data expansion:
Data tagging refers to the occupation of tagging, classifying, analyzing and cleaning the original data sets of artificial intelligence to help train machine learning algorithms and artificial intelligence models.
According to the National Vocational Skills Standard for Artificial Intelligence Trainers (202 1 Edition), the professional ability is described as "having certain learning ability, expression ability and calculation ability; The sense of space and color vision is normal, and the general education level is "graduated from junior high school (or equivalent education level)".
In other words, this position does not need a high technical and academic threshold, and the amount of data to be marked is huge. Therefore, high demand and low post threshold provide opportunities for people with low academic qualifications to work in the office.
Many people pay attention to the artificial intelligence industry only after seeing the fiery influence of ChatGPT, but in fact, data label companies have been blooming everywhere in small cities in various counties. There are nearly 300 data labeling companies in Zhengzhou and Kaifeng, Henan.
According to unofficial statistics, there are nearly 700,000 data annotators in China, and nearly one million people work part-time in crowdsourcing platforms, and there are countless companies engaged in artificial intelligence industry. The industries that apply data labeling technology include but are not limited to automobile, finance, medical care, logistics, home, monitoring, education, Internet and so on.
Among them, the automotive industry has the greatest demand for data. There are dozens of automobile companies and nearly dozens of intelligent driving technology companies in China. The automobile industry has been pursuing far more than safety and comfort. Now is the pursuit of intelligence. How to make cars intelligent requires numerous data annotators to annotate a large amount of data for car identification.
Therefore, the importance of data annotator is self-evident. At the same time, it is particularly important to establish a mature base team. Some car companies are willing to build their own data annotators.
Some are willing to operate the base jointly with mature data label companies. Although Henan Shuangwhale does not produce a screw, it has become the front-end link of automobile manufacturing with its professional delivery ability and SAIC joint venture base.