Data processing

If your work involves data analysis, SEO optimization, or any role that requires sifting through digital content, understanding how to effectively extract keywords is essential. This skill streamlines data management and accessibility, representing a significant advancement in data processing and analysis methodologies. Right at the center of this ability is Natural Language Processing. This cutting-edge technology empowers computers to understand human language, effectively narrowing the divide between digital data…

Real-time machine learning refers to the application of machine learning algorithms that continuously learn from incoming data and make predictions or decisions in real-time. Unlike batch machine learning, where data is collected over a period and processed in batches offline, real-time ML operates instantaneously on streaming data, allowing for immediate responses to changes or events. Common use cases include fraud detection in financial transactions, predictive maintenance in manufacturing, recommendation systems in…

Neuromorphic computing is an intriguing and fast-expanding area that creates brain-like computer systems by drawing inspiration from the human brain. In this essay, we will look at the basics of neuromorphic computing, its components, and its applications in artificial intelligence and computing. Neuromorphic Computing Basics Terminology Before we delve into the structure of neuromorphic computing, let’s familiarize ourselves with some key terminology: Neuromorphic Hardware: Specialized hardware designed to mimic the…

In the "bygone era," invoices were traditionally dispatched in paper format and painstakingly transcribed into the recipient's ERP system facilitating subsequent data processing. As indicated by Brendan Foley, among others, a significant proportion—around 80 to 90 percent—of data from documents like invoices and emails continues to be manually extracted (2019). However, there has been a notable shift in recent years towards the exclusively digital transmission of documents such as business invoices, accompanied by…

Digital transformation is the goal of each business in the retail industry today. It is the tool used by various businesses across the world to understand and modify their business models. A digital transformation is a strategic approach through which businesses access a wider market. It is a process by which the company integrates new technologies into its operations. Different departments within the company can rely on the technology for data analytics, especially with the growing customer base. As a result, digital…

In the ever-evolving landscape of the Financial Services Industry (FSI), organizations face a multitude of challenges that hinder their journey toward AI-driven transformation. Legacy systems, stringent regulations, data silos, and a lack of agility have created a chaotic environment in need of a more effective way to use and share data across the organization. In this two-part series, I delve into my own personal observations, break open the prevailing issues within the FSI, and closely inspect the factors holding back…

Data volumes are exploding. As developers build ever more complex applications powered by technologies like artificial intelligence and machine learning, the data demands continue to grow staggeringly. IDC predicts that by 2025, the global datasphere will reach 175 zettabytes. Meeting these massive data demands is an increasingly complex challenge, especially for developers. Managing enormous volumes of structured and unstructured data across on-premise and multi-cloud environments has become an unwieldy task that eats…

Graphic Processing Units (GPUs) have crossed new horizons and demonstrated notable advantages in Big Data processing and other computation-intensive operations. Apart from their most widely known application in rendering 2D/3D graphics and animations in the gaming industry, modern GPUs can also be coded to perform complex computations such as image processing for scientific simulations and architecture projects, blockchain/cryptocurrency development, and mining, Data Analytics, AI/ML development, and handling…

In the ever-evolving landscape of software architecture, the integration of artificial intelligence (AI) into microservices architecture is becoming increasingly pivotal. This approach offers modularity, scalability, and flexibility, crucial for the dynamic nature of AI applications. In this article, we'll explore 10 key microservice design patterns that are essential for AI development, delving into how they facilitate efficient, robust, and scalable AI solutions. 1. Model as a Service (MaaS) MaaS treats each AI model as…

Developing an application or software for operating businesses has become mainstream these days. Most entrepreneurs can do that, whether an eCommerce business owner or travel insurance service provider. But being at the forefront of one’s industry is something that is not easy at all. One needs to have an innovative mind and exceptional expertise in the tech domain to stay ahead of their competitors and achieve a greater share of the market. Yes, because only then they will be able to develop useful features and…