WHAT IS DATA ANNOTATION
Data annotation is the process of labeling data that are available from various sources in different formats such as text, video or images and having to supervise machine learning so as to aid AI to clearly distinguish and comprehend input patterns to facilitate efficiency in their respective fields. Several programs from MP.BPO are available to annotate images and other formats of data, or manual tagging services, but the accuracy of the annotation relies on choosing the right program for the task as per the needs of the customer.
DATA ANNOTATION BENEFITS
One of the advantages that data annotation produces for the digital marketing and search engine optimization aspect of the industry is the predictive capabilities. That enable a more responsive system to the end-user such as a Chabot system to answer any and all queries from being train, which using a machine learning algorithm or auto filling google web search engines with predictive texts of the users plausible query or even sifting out the relevant wanted but missed information to the end-user (medium). This is the reason why MP.BPO always tries the best to meet the highest standard of clients and increase business reputation along the quality of services.
The constant growth over time for the consumption of internet, artificial intelligence and machine learning has shown a definite need for data annotation and therefore, the market has been foretasted to show a CAGR of 15.1% between the periods of 2020 and 2030 (Leyland, F. P., 2020). The primary reason for the extraordinary growth can be linked back to the high digitalization of consumer products and services from simple smartphone facial recognition to advanced biomedical, medical and pharmaceutical services. However, even as the trend of data annotation in majorly seen in the manual input perspective through using human capital which is seen as expensive due to time and error rate/accuracy, automatic annotation has seen to be on the rise forecasting to increase the base CAGR of 15.1% to 17% during the aforementioned period (Ana, I. C., 2020). MP.BPO realize that the increase is a welcomed benefit but not necessarily an effective one as although large amounts of data can be annotated in less time by having machines teach machines, it will not overcome or solve all issues as manual supervision is needed to overcome complicated problems that automation tends to glide over (medium).
As prior mentioned, data annotation in the medical sector is imperative especially when it comes to recognizing diseases and identifying pathological markers such as outlining malignant/benign tumors, ECG rhythm identification and pinpointing distinct cells amongst other medical uses. A recent good example of a trending and beneficial use is with the study and creation of the covid-19 vaccine (factmr). Technologies such as data annotation and machine learning have become vital in decoding, predicting and assembling genomes and viruses to study and reserve engineer a cure. One such newly developed tool that enabled the combat and study is the machine learning based Vaxign-ML reverse vaccinology tool to predict covid-19 vaccine candidates. This tool enabled the medical society to comprehend the virus more deeply in a short period of time such as understanding the covisd-19 strand is an amalgamation of the SARS-CoV and MERS-Cov (frontiersin).
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