3 min to read
How does artificial intelligence learn?
Building essential learning data for advanced artificial intelligence generation. Introducing its importance and DSLabGlobal's automated data labeling technology.
How DS2.AI’s Auto Labeling is Different?
This blog post deals with the definition of data labeling, its technical strengths and effects.
● What is data labeling and why is it necessary?
Have you ever seen a newborn baby?
Babies right after childbirth can only use a few facial expressions and cries to convey their condition. However, as time goes by, humans naturally understand the characteristics and properties of things by seeing, touching, and taking them into their mouths. As humans gain experience and memorize the words that people use, they learn that the birds fly in the sky and that trees provide us with a cool shade. Walking down the street, a person sees the street food vendors and think it will be delicious. This whole process is called 'socialization'.
In fact, all AI models are created as a newborn baby. Only through a “socialization” process that informs various information and checks whether it is accurately recognized, just like raising a child, can we operate a real-world AI model.
(Just like teaching children, we need to teach AI)
As such, AI needs "data labeling" for performing through cameras and perceives through the human eyes during the socialization process in order to recognize various elements of human society. Looking at the picture above, we naturally think of dogs and cats, but AI is not able to distinguish the difference between the two until it is trained. Therefore, we have to show various samples and make them aware that they are dogs and cats.
In the applied learning, we can also train vehicles and pedestrians on the road. AI that has learned this data can be applied to various fields such as autonomous driving and crackdown cameras.
(Autonomous driving through data labeling)
● DS2.AI’s Auto Labeling If a person labels all the data one by one, it will take a lot of time and labor to prepare the training data, even before utilizing in the industry.
DS2.AI has developed automated data labeling based on deep-learning to dramatically increase efficiency. If you make 10 labels as a sample, AI will automatically process a lot of data based on these samples.
Therefore, DS2.AI's auto-labeling works at around 20% of the existing market's data labeling unit price. Also, in terms of time, one of our customers, Autonomia, completed the data labeling process in about six months, which would otherwise take two to three years.
In addition, DS2.AI’s automated labeling AI performs automatic labeling with the same performance as long as the project changes a small amount of sample data. It’s like a smart factory that quickly changes and accommodates internal production lines according to its purpose.
(Deep Learning-Based Data Labeling Comparison)
In this post, the significant “socialization” process of learning AI were discussed.
Unlike other companies, DS2.AI’s data labeling process emphasizes the automation of the whole labeling process. In the next post, we’ll be looking at the impact of introducing this automation technology on ‘crowdsourcing’.
Check Labeling AI that helps automatic data labeling !