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Grand Time
Grand Time

Data Marking and the Grand Time project

Artificial intelligence technologies are changing the surrounding life. And the success of any project in this area depends on the dataset that we feed into the machine learning algorithm.

In addition, in order to obtain accurate results and forecasts in the development of artificial intelligence, high-quality data labeling is of paramount importance. By focusing on delivering a high-quality data set, providing feedback, and managing the workforce effectively, you can deliver top-notch AI projects that achieve a higher level of accuracy.

Data labeling is a detailed process that includes the following steps to categorically train AI models:

1) Collection of datasets through strategies, e.g. in-house, open source, vendors.

2) Labeling of datasets according to the capabilities of computer vision, deep learning and neurolinguistic programming.

3) Testing and evaluation of produced models to determine the intelligence within the deployment.

4) Satisfying the acceptable quality of the model and, ultimately, releasing it for comprehensive use.

There are different types of data labeling:

🟡 Audio classification includes: audio collection, segmentation and transcription.

🟡 Image labeling consists of: collecting, classifying, segmenting and labeling data by key points.

🟡 Text Marking includes: text extraction and classification.

🟡 Video tagging includes elements such as: video collection, classification, and segmentation.

🟡 3D marking: features of object tracking and segmentation.

In the modern world, digitalization of various aspects of life is becoming the main trend in the development of society. This process is inextricably linked with the use of artificial intelligence, one of the elements of which are machine learning and digital data labeling.

The Grand Time project also aims to take part in the development of artificial intelligence according to the information provided in the White Paper. For example, it is planned to involve project participants in the digital marking of data on a cryptocurrency crowdsourcing platform, for which users will receive a reward in the form of a Grand token.

This is an excellent example of the symbiosis of artificial intelligence and blockchain technologies.

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