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Why crowdsourcing is the solution to data annotation

It is easy to get confused when there are so many different areas of AI, but simply put, AI is the ability for a computer to do work normally done by humans by imitating human intelligence...


Artificial intelligence is a versatile technology that sees use in a diverse range of industries. It would seem there’s nothing AI isn't capable of as we continue to push the boundaries of automation. Many processes and jobs can now be completed with much greater efficiency thanks to the aid of AI models. However, despite rapid advancement in AI over the last few years, most Machine Learning models still rely on education from humans in the form of data annotation.


The process of annotating data to prepare high-quality training data is a major hurdle in any AI development project. For small teams of data scientists, having to manually label enough data points to create good training data consumes a lot of valuable time. This time is better used making insights and working on other areas of development, so many companies choose to outsource their annotation work to specialised data annotation companies.


There are a number of different ways to get data properly labelled and annotated, each with its own advantages and disadvantages. At Tictag, we have tapped on the power of crowdsourcing to accomplish this task swiftly and accurately.



What is crowdsourcing?