Data serves as the foundation for any artificial intelligence or machine learning project. An AI/ML model requires carefully annotated and labelled data, called training data, to learn how to recognize patterns and make decisions. The results an AI/ML model produces is heavily influenced by its training data, which is why high-quality training data forms the basis of an effective and successful model.
What are the different methods for data annotation?
Labelling and annotating data is usually done manually using a specially designed software called a data annotation tool. Data annotation tools can be used to add labels to various data types such as images, text files, audio files, and more.
One of the most important things to consider when starting an AI development project is deciding how to obtain the initial set of training data. In general, there are four main ways of converting raw data into training data:
Using open source tools with internal annotators
This first method probably seems like the simplest and cheapest solution, and it can be, but there are a few issues with this method that can easily be overlooked.
What does it take to build?
Artificial intelligence, or AI, is quickly changing the world and how we live in it. Its influence can be seen all around us in many different forms. From online shopping recommendations to self-driving cars and more, AI is already here and improving our lives in many ways. Given that so many aspects of modern society are steadily becoming integrated with AI, the importance of understanding the technology and its development has become clear.
What is Artificial Intelligence?
When met with the question “what is artificial intelligence” people often have some trouble finding the right answer. AI itself is a broad field and there are a number of different subsets to AI like machine learning, natural language processing, computer vision and so on.
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. The key aspect separating AI from normal computer programs is that AI is able to perform tasks in unfamiliar situations and improve as it encounters more problems.