The Best Data Labeling Company in 2021

How a Human-Powered Data Labeling Platform Accelerates AI industry’s Development During COVID-19?

The covid-19 epidemic in 2019 disturbs routine life across the globe. Due to the limitation of physical conditions, traditional enterprises are enhancing their strategies for digital transformation and business automation.

Data Labeling is a Simple but Difficult Task

Labeled data is the core of the AI/ML industry. The quality and quantity of data determine the performance of the AI model.

It is shown that an in-house experienced team composed of 10 labelers and 3 QA inspectors is able to complete around 10,000 automatic driving lane image labeling in 8 days.

In fact, training a model needs tens of thousands or even millions of no bias data samples, which takes a lot of time.

During the hard period, some data labeling companies were forced to switch to a work-from-home model, which has posed challenges in terms of communication, data quality, and inspection.

For example, Google Cloud has officially announced that its data labeling services are limited or unavailable until further notice. Users can only request data labeling tasks through email but cannot start new data labeling tasks through the Cloud Console, Google Cloud SDK, or the API.

Insiders say that data labeling is a simple but difficult task. On one hand, once the labeling standard is set, data labelers just need to follow the principles and rules. On the other hand, if the training data has a bias, the algorithm model cannot be well developed, AI company needs to restart the data labeling process again. Timing is important, once the company is behind the schedule, the product may be overtaken by competitors.

A majority of AI organizations said the process of training AI has been more difficult than expected, according to a report released by Alegion. data at scale and quality issues become their main obstacles.

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1 Data Annotation Service and Its Key Advantage — Flexibility

2 Why the High-Quality Training Data is so Important to AI Machine Learning?

3 No Bias Training Data — the New Bottlenecks in Machine Learning

4 Data Labeling — How to Select a Data Labeling Company

5 Data Labeling Service — Four Customer Pain Points in Getting No Bias Training Data