What does an artificial intelligence data annotator do?

Artificial intelligence data annotator refers to the person who is responsible for annotating, classifying and annotating a large number of original data. In machine learning, deep learning and other fields, training algorithms need enough high-quality data sets to support them, and these data often need to be labeled before they can be used by algorithms. Therefore, artificial intelligence data annotator plays a vital role in the development of artificial intelligence technology.

The main work of artificial intelligence data annotator includes:

1. Data preprocessing: primarily screen and clean up the original data, remove useless information and wrong data, and organize the data into a fixed format.

2. Labeling and classification: classify, label or annotate data according to task requirements, such as image target recognition, text segmentation or named entity recognition.

3. Quality control: check the quality of marked data, ensure the accuracy and consistency of marking, and find and correct errors in time.

4. Data management: Make statistics, arrangement and storage of the marked data, and establish a good data management system to facilitate the subsequent algorithm training and optimization.

In a word, artificial intelligence data annotators play an indispensable role in the development of artificial intelligence technology, and their work can improve the accuracy and efficiency of the algorithm, thus promoting the development of artificial intelligence technology.