The next-gen technologies such as Artificial Intelligence (AI), Machine Learning (ML), Robotic Process Automation (RPA), etc., present unique opportunities for businesses to cope with the pandemic’s fallout and expand paradigms—and developing such automated applications and machines require training data sets.
The training datasets for machine learning algorithms are created via the data annotation process—labels are added to the input datasets, thus helping the smart models calculate attributes easily. The input data can be texts, videos, images, etc., whereas the labels are added in the form of tags, metatags, and descriptions. Computer vision-based models and Natural Language Processors (NLP) can detect and identify the object of interest accurately via these labels.
Developing the training sets to be fed into the machine learning algorithms is an uphill task. Accuracy and precision of outcomes are directly relevant to the quality of input sets since the AI/ML model is as smart as the data it is fed with. Errors or redundancies in the data annotation process can deviate from the results and create roadblocks in the business transformation plans.
Instead, engaging in professional data annotation services makes complete business sense. The outsourcing companies have the potential required to label data sets efficiently. They deliver constant streams of high-quality, precise, and accurate data within the stipulated time and budget. Offshoring is, therefore, not only a cost-friendly option for organizations but also allows the management to concentrate better on core competencies.
Apart from operational expense optimization, growth-focused players enhance the cognitive bandwidth of employees and increase their productivity. Organizations can harness the true potential of AI/ML technologies and expand paradigms to ace their peers in the industry. They reap a plethora of benefits as elucidated here:
· Professional Excellence
The outsourcing companies have a pool of data professionals, accredited annotators, multi-linguistic experts, and subject matter experts (SMEs) to prepare enhanced training sets for the computer-vision models. They work as an extended in-house team for clients across industries and verticals to help them fuel their AI/ML models. Having the right blend of skills and experience ensures excellence in the data labeling process.
· Technological Advantage
Equipped with the latest technologies and streamlined workflows, the professionals know what it takes to develop enhanced training sets. They use techniques like semantic segmentation, 2D bounding box, 3D point cloud labeling, entity linking, phrase chunking, etc., to label the data sets pixel-by-pixel. This helps the machine learning algorithms to calculate attributes easily.
· Quality with Accuracy
One of the greatest advantages of engaging in outsourcing data annotation services is the quality of outcomes. The professionals have proper model behavior understanding and develop the training sets according to their future use cases. Their flexible delivery models ensure efficient and thorough outputs across different industry verticals. The QA teams ascertain that the input data sets are up to 99.99% accurate and relevant to the model’s use case.
· Assured Data Security
Data security is one of the major concerns for businesses offshoring their annotation and labeling tasks. Outsourcing companies, therefore, offer utmost data security. The professional’s leverage File Transfer Protocol (FTP), Secured File Transfer Protocol (SFTP), and Virtually Protected Network (VPN), to access and retrieve data. They follow stringent data security protocols and all their practices are legally compliant.
· Comprehensive Suite of Offerings
Every business has different requirements. Addressing this fact, the external vendors offer custom data annotation services catering to the client’s needs. Reputed companies usually offer a comprehensive suite of offerings—text annotation, video annotation, image annotation, 2D bounding box, 3D point cloud labeling, etc., everything under a roof. All you need to do is pay for the services availed and get quality outcomes!
To add up, businesses that engage in professional data annotation services make a smarter move. They get access to constant streams of high-quality accurately labeled data in real-time. Stakeholders are assured of professional excellence and technological competence since the offshoring companies already have what is required to label data sets accurately. Hence, you must begin with streamlining your requirements and finding the right outsourcing partner!
Source: Accelerate AI/ML Models via Professional Data Annotation Services
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