Data Labeling — Nine Questions to Ask before Selecting a Data Annotation Company
Data Annotation Service
Data annotation technique is applied to make the objects recognizable and understandable for AI models. It is critical for the application of machine learning in security, autonomous driving, aerial drones, and many other industries.
Data Annotation Outsourcing Service and Its Current Situation
There is no doubt that the performance of an AI system depends more on the training data than the code.
However, data annotation is a repetitive, time-consuming, and laborious processing regarding the tremendous volumes of raw data required for machine learning algorithms.
Therefore, many ML companies prefer outsourcing services so that they can focus on technology development, which in turn helps them get a competitive advantage in the AI industry.
There are a variety of outsourcing companies available in the data annotation market, and the traditional data annotation outsourcing workflow goes in this way:
a. Defining the work and outlining the project’s requirement
b. Looking for a trustworthy service provider and signing contracts on the project
c. The outsource company screening and training the skilled annotators
d. Project launch
e. Data quality verification and inspection
As you can see from the process, it usually takes at least one week on project analysis and project team building before the data annotation starts, which lowers the efficiency.
Moreover, the pricing is not always transparent. Usually, they charge per hour. For computer vision data this is usually around $5-$10 per hour per worker.
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How to Select a Data Annotation Outsourcing Company?
Here are some questions you may take into account while choosing the partner.
1 What datatypes do you support?
2 How about the data quality control?/How to ensure high-quality data?
3 Is the data labeled manually?/How is the data labeled, manually or semi-automatic labeled?
4 Do I need to form my own in-house team?
5 Tell me more about our data security process
6 How you ensure project scalability
7 Compared to other platforms, why yours is better?
8 Do you have a free trial?
9 Pricing
ByteBridge.io, a Human-Powered Data Labeling Platform(SAAS)
ByteBridge is a human-powered data collection and labeling platform(saas) with robust tools and real-time workflow management. It provides accurate and consistent high-quality training data for the machine learning industry.
Via the ByteBridge dashboard, you can seamlessly upload your project and utilize end-to-end data labeling solutions such as visualizing labeling rules. Through the dashboard, you can also manage and monitor your project in real-time.
As you can manage your project in real-time, you can initiate or terminate your task as you wish according to your own timeline.
Meanwhile, the transparent pricing which eliminated the various heavy commissions apparent in the current market lets you save resources for more important investments.
End
“High-quality data is the fuel that keeps the AI engine running smoothly. The more accurate annotation is, the better algorithm performance will be,” said Brian Cheong, founder, and CEO of ByteBridge.
Designed to empower AI and ML industry, ByteBridge.io promises to usher in a new era for data labeling and accelerates the advent of the smart AI future.
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Data Labeling — Nine Questions to Ask before Selecting a Data Annotation Company was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.
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