Shulou(Shulou.com)06/03 Report--

As the three decisive factors of artificial intelligence, algorithm, computing power and data have always been the top priority of industry research.

However, compared with algorithms and computing power, the data field has obviously received much less attention. In particular, the data tagging industry, as the cornerstone of the artificial intelligence industry, is so rough and simple compared with the whole industry of AI in the spotlight.

However, with the development of the times, this situation has changed greatly, and the importance of data annotation has been more and more recognized by the whole AI industry. AI has higher and higher requirements on the quality, scale and scene of data, and refinement and territorialization have become a new standard for labeling data.

1. What is data annotation?

Data annotation is a branch of AI industry. The current artificial intelligence algorithms are data-driven, and a good model needs high-quality data resources to support.

If you want to understand what data tagging is, you must first understand the goal of artificial intelligence: machines take the place of human cognition and thinking.

Think back to how we understood the world when we were young, such as cars. When we saw the car for the first time, we didn't know what it was called. Our parents will tell us that this thing is pronounced "car". It is in this shape and can drive.

Analogical machine learning. If we want the machine to understand what a car is, we can only give the machine a picture of the car, mark the outline of the car, and mark the name "car". At this time, the machine can recognize the car in this picture.

However, compared with humans, machines do not have the ability to think and associate. After changing a picture, the machine may not recognize the "car" in it. What shall I do? At this time, you need to label a large number of pictures to the machine, so that the machine can find the common characteristics of the cars in these pictures, so that other cars can be identified later.

To put it simply: data annotation is a kind of behavior that data annotators process artificial intelligence learning data with the help of marking tools.

two。 What are the data annotation tools?

The basic data types of data annotation include text, picture, video, voice, numerical data and so on.

Manfu Technology Voice tagging platform

The commonly used data annotation tools are 2D box, polygon segmentation, semantic segmentation, point annotation, line annotation, video annotation, 3D cube annotation and so on.

Data annotation tools: 2D box

3. New trend of data tagging industry

At present, artificial intelligence technology is gradually moving from laboratory to reality, and landing products put forward new requirements for the quality of labeled data.

According to the current situation of data collection and labeling, the traditional general data has obviously been unable to meet the requirements of the industrial scene, and fine, high-quality tagged data has become a new demand of the industry.

In this context, the data annotation industry is in urgent need of a change. Efficient data annotation tools and high-quality data annotators will become an important part of the future development of the industry, and fine labeling data will constitute the strongest cornerstone of the future development of the AI industry.

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