Hey, Remotasker! If you’ve been hanging around Remotasks for a while, chances are you’ve heard the term “data labeling” used in the context of a Task. Of course, literally speaking, “data labeling” might have to do with labeling data, right? This is correct at some level, but there’s a deeper meaning behind the concept that enables us Remotaskers to help improve smart technology today.
Wait, what does labeling have to do with AI and machine learning?
In the context of artificial intelligence and machine learning, Data Labelling is the process of identifying and attaching informative and meaningful labels to raw data like videos, images, and text. That way, AI and machine learning can use the labels and the raw data to learn certain functions and mechanisms. For instance, data labeling can pave the way to help a self-driving car separate other cars from the road, pedestrians, and traffic elements.
Data labeling can help artificial intelligence and machine learning models make more insightful insights towards elements interacting in various media. However, since there are different kinds of raw data available, different kinds of data labeling use exist for AI and machine learning models to use. Here are some of the mechanisms used for data labeling:
If you’re interested in helping AI identify objects more accurately, then you might want to become a part of the Remotasks team! In our earnings platform, we pay Remotaskers to do a variety of Tasks and project types related to AI - including Data Labelling! In fact, Data Labelling is one of the most popular project types among our repertoire of task categories. Just sign up on our website for free, get trained without charge, and start getting paid for doing Data Labelling tasks!