A Fortune 500 company with a large marketplace has recently partnered with Tasq.ai, an ultra-scale data labeling platform. The purpose of this partnership is the creation of high-quality datasets for training computer vision machine learning (ML) models to recognize products accurately, collect metadata, and better understand the intent of customers using the marketplace.
Tasq.ai accomplishes this task by using Tasqers – a diverse, unbiased global crowd of filtered human annotators. Tasqers have high cognitive abilities allowing Tasq.ai’s platform to manage the process of creating training datasets faster and with higher accuracy.
This process is carried out by using a codeless workflow data pipeline of nano-tasks. These nano-tasks are sent to Tasqers for human annotation and verification.
It does this by screening millions of online users in seconds to find those with the necessary cognitive capabilities to excel in a specific task. It then incentivizes those users to complete the task accordingly.
Tasq.ai achieves high-quality results with committed quality through the following methodology