Why Data Annotation Redefines Scalability
Data Annotation is the reason your AI and ML models understand and make decisions the way they do, and without the training provided by data annotation, these models more likely than not, will remain clueless of the actions to be taken.
But what exactly is data annotation?
Well, simply defined, data annotation is the process of using metadata to label data that is to be used for training purposes. Think of it like labelling your spice jars with name tags to easily understand what to pick when the need arises. But it’s a little more complicated than that. Supervised ML and AI models are taught how to recognize patterns when presented with different data, and unannotated data to qualify for becoming usable models. More like replacing your labelled jars with new ones (without labels) to see if you can recognize the spices without any help.
For example – You type in your everyday browser the word “contract”, the browser will try to understand your intent behind this query, which could either be that you are looking for a legal agreement related information or something related to contracting a virus. It is the algorithm that understands the intent because it has been trained how to recognize patterns, by human-powered data annotators.
And data annotation is not just text labelling, it is also image labelling, wherein the system is fed tons of images with labels and categories for it to understand and be able to differentiate between different objects.
For example – An autonomous vehicle that uses computer vision, knows when the light is green it’s time to move, and when its red its time to stop. It can understand the difference between these signals because of all the labelled images that were used to train the model in such a way that it can independently function with ease while making the right decisions.
It is because of that particular reason, the surge of image data annotation tools and services is being witnessed.
The global data annotation tools market size was valued at USD 494.0 million in 2020 and is expected to expand at a compound annual growth rate (CAGR) of 27.1% from 2021 to 2028, as per a research from Grand View Research.
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Last Update : Jun 25, 2021 10:49 AM
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