Why Data & Data Annotation Make or Break AI


Everything in this universe is captured and preserved in the memory, in large scale we can refer it as Databases. Before we can proceed on how Data can make or break AI, let’s see what Data Annotation is. Data annotation is the process of appending important data to the original data. This dataset is without form or clarity at the beginning phase and therefore it is ambiguous to computers. Data without identifiers is just chaos, for a machine learning algorithm. However, this chaos can be converted into a structured training program by annotation which has an effect all the way up the queue. Let’s go back to our Search Engine scenario to explain this. The IAI integrated Technology must include a datasets of text samples annotated for entity extraction in order to create an entity extractor. Fortunately, there are a bunch of different ways of tagging also within attribute selection which will help to educate the system for marginally multiple tasks. Data annotators build metadata that defines or categorizes data in the form of code snippets. In the past, businesses used data annotation to define structures and allow data easily accessible. Now although, companies are concentrating their efforts …

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