WHY ARTIFICIAL INTELLIGENCE IS INCOMPLETE WITHOUT DATA ANNOTATIONS 

Introduction:

Data Annotations Services in simple words can be described as sets of data given to machines to understand what the specific data is. The labelling or tagging of information on datasets provided for the machine learning models to let it understand what the data sets are. Data sets come in formats such as text, audio, video, and image. 

The data annotators at Globose Technology Solutions tag different elements on the information provided in the various formats so that the machine retains the data processes it then prepares itself for any enhancements required in the future based on the existing information provided. Data annotation is a time-consuming process. It takes several hours to feed the data bit by bit, pixel by pixel into the system precisely. The data annotators ensure to deliver the best and most accurate result as the best data collectors provide the exact information required. 

Text annotation- This annotation where the sentences, texts, phrases, and messages are being tagged or labelled according to the requirements. Text annotations involve chat boxes or query corners from an online platform, tags on posts, PDFs, DOCs, ODTs etc, on an adverse scale. Since the text annotation is the fundamental process in developing NPL, text annotation is considered as an important phenomenon.

Audio annotations- Categorising this as speech annotation, the audio annotators tag or label the raw audio data collected in the form of speech or other sounds. As an example, we can consider virtual voice assistance. The machine model is trained in a way where it can recognize and respond to the user's needs in a fraction of a second, irrespective of the language used, or different spoken dialects. Thus, the audio annotators collect and feed the data into the Keeping in mind the data annotations we have categorised the annotations into 4 major categories.

Image annotation- This is a basic annotation where the images or objects are tagged individually. This gives the liberty to tag objects, and background details such as landscapes, animals, birds, and even their sounds can be labelled in it. Several details can be annotated. system for it to understand and respond to the users accurately. 

Video annotation- video annotation is very similar to image annotation in terms of purpose but differs as the video tags moving objects like car number plates of the person driving can be identified in the video annotation. They are individually identified and boxed similarly to the image annotations. Video annotations become important for video surveillance, moving vehicles, etc.

We know that artificial intelligence is a major part of software tools nowadays and is undoubtedly the fastest growing stream in computer systems as it is programmed in a way where it can respond to human intelligence and sense, has the ability for decision making or even understanding and translating languages in other various languages. 

AI is a replacement for many tasks that used to be performed before. Commands at the tip of your tongue or even at your fingertips. Simple switches turn on with simple claps. Artificial intelligence is ruling major parts of our daily lives today.

Now for this to have an idea of what data is fed into the system, there must be a tool/program to provide the same. Here data annotation comes into the picture. AI Data Annotation Company helps in making such tasks easier by providing detailed information in terms of text, data, images, videos, and even sounds. Techniques such as polygons annotation, landmarks annotation, 2D annotation, 3D annotation, Bounding box annotation, masking annotation, tracking annotation, polyline annotation, etc are used to feed the data accordingly.

AI is a self learning model but with some backlogs, and such gaps can be filled by these procedures to make it more efficient. We as humans understand and recognise the basic facial features, emotions, differentiate between the objects as we have the ability to do so. But as machines we need to enhance the ability of the software model to make it more reliable and accurate. That is done by data annotations. From basic phone assistance to capturing data from space,capturing road traffic to speeding vehicles, in the field of medicine to having self functioning robots in restaurants.  AI has grown with the help of data annotations that provide very specific details to the images, text, audios, videos, etc. Thus summarising, AI is incomplete without the specific information provided by Data annotations.