Cloud Computing and Data Annotation Service

The data Annotation service driven by the development of the artificial intelligence industry is now dominating the business space. Data label is the method by which human annotators automatically label various kinds of data including text, video, audio, images etc through computers or mobiles.

The trained computer program identifies patterns and labels every bit of data that comes in. Once completed, this labelled data is then fed to an artificial intelligence algorithm to train a AI system. Hence, once the training is complete, the software starts generating reports at real time.

As the use of big data continues to increase, the need for better quality solutions also increases. To meet up with this requirement, data classification and data Annotation service providers have emerged. The Labelling Software RDD ( Reconstruction, Data Annotation and Classification) project from IBM’s Cognitive Services team is one such example. The project’s developers claim that their RDD can help the industry achieve three major milestones:

“Rank Labels” is probably the most important goal that the software can achieve. At present, it leads the way in terms of its popularity and number of customers. At rank #1, it outranks the likes of Sather and IBM’s Power Watson. The next highest goals in line are: “First Page Results” and “Overall Labelling Popularity.” The popularity achieved by these milestones point to the growing demand for better quality solutions.

With the recent announcements from companies, it is evident that machine learning and automatic application deployment is no longer something that needs special hardware or software. Instead, both of these companies have made it clear that the future of large-scale label and Data Annotation is to be found on the cloud.

This is a very encouraging development for application developers, particularly those who have traditionally worked on traditional platforms like Java, Objective-C, Ruby or Python. Cloud based tools make it possible for them to easily migrate data and label systems to the cloud while retaining access to the tools and guarantees that their programmers and technicians have developed during the lifetime of the program.