Crowdworks Registers US Patent for ‘Method for Selecting Worker According to Feature of Project Based on Crowd Sourcing’

Crowdworks (CEO Park Min-woo), an Artificial Intelligence (AI) training data platform company, announced that it has completed the registration of a US patent for ‘method for selecting worker according to feature of project based on crowd sourcing’.

When operating a crowdsourcing-based AI data project, this technology checks the functional elements included in the project to be opened and selects workers (data labelers) who are proficient in the task in consideration of the worker’s work performance for the functional element. For each data labeling project, it automatically creates and provides real-time worker pools of optimal workers.

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In case of using patented technology, it is possible to reduce time and cost by selecting optimal workers according to the characteristics of the project. Furthermore, it allows to maximize their data project efficiency.

Crowdworks is the largest patent holder in the AI data labeling technology field in Korea, applying for over 180 Korean and international technology patents essential to the advancement of AI data labeling technology and securing market competitiveness.

Crowdworks’ Machine Learning (ML) and AI-based technologies, which are protected by more than 180 patents, improve the productivity and efficiency of AI training data construction tasks, and manage the quality of the result data. The AI training data constructed in this way has been provided to customers and society to help the development of various AI fields.

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Crowdworks’ has been steadily securing US patents since its first US patent registration in March of this year. Crowdworks is continuously developing the North American and Europe markets by securing global patents and participating in Epicenter Accelerate – K-Startup Program in Sweden. The company is also planning its CES 2023 exhibit.

Park Min-woo, CEO of Crowdworks, said, “As data-centric AI is now a global topic, securing technological competitiveness for high-quality data is essential.” And he continued “We are aiming to lead the global AI training data market by actively securing intellectual property rights.”

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