Choose your interest – from EdTech to AI – and dive into stories, insights and expert takes
Designing student-centric EdTech is more than creating beautiful interfaces. It’s about understanding how students think, behave, and interact with technology. When UX is aligned with student needs, engagement doesn’t just improve but it transforms the learning experience. Let’s dive into the best UX practices to build EdTech that keeps students interested, active, and thriving.
The AI users are always on the lookout for smarter, faster, more intuitive tools. Yet, their first encounter with AI-driven products often leads to confusion, mistrust, or outright abandonment. Artificial Intelligence promises efficiency and personalization, but too often delivers a cold experience that pushes away the very users it aims to help.
Creating AI-powered products comes with a key challenge, how to make them smart, predictive, and scalable without losing clarity, user control, or trust. This article explores practical and strategic ways to design AI-first solutions that not only meet technical goals but also deliver experiences that truly connect with users.
About 67% of students find learning more motivating when it includes game-based elements. That’s a powerful number, and it highlights something important for everyone involved in education today. Online learning is booming, but keeping students engaged remains one of the biggest challenges. This is where gamification steps in as a strategic research-backed solution.
Artificial Intelligence is accelerating at an unprecedented pace, but so too are the costs and scaling challenges of running these powerful systems.
In early 2025, OpenAI faced one of the most unexpected performance stress tests: the viral Studio Ghibli prompt trend. Millions of users flooded the system, asking ChatGPT to generate dreamy, whimsical images styled like a Ghibli movie.
According to the Cloud Native Computing Foundation (CNCF), Cloud-Native adoption has soared in recent years, with over 5.6 million developers using Kubernetes alone as of 2021. Leading companies like Netflix, Spotify, and Airbnb have used cloud-native approaches to power their global operations.
Just moving to the cloud isn’t enough. True success in cloud-native development comes from rethinking how software is built from the ground up. That means embracing flexible architectures, breaking apps into smaller parts that can be deployed independently, automating as much as possible, and focusing on continuous improvement. It’s not about using the cloud. It’s about using the cloud well.
Did you know that software bugs cost the global economy around $2 trillion annually in the US in 2020? The consequences of defective software range from lost revenue to security breaches and system failures. As businesses scale and products grow more complex, ensuring software quality at every stage becomes a mission-critical task. This is where automated testing toolkits play an important role in maintaining reliability and efficiency.
In a world where technology is evolving rapidly, relying solely on manual testing is no longer practical for enterprises that need speed, accuracy, and reliability. Automated testing helps organizations deliver high-quality software while making better use of their resources. Let’s dive into how these toolkits improve quality and efficiency at different stages of software development.
About 93% of online experiences start with a search engine. AI-powered search enhances user engagement by utilizing machine learning and natural language processing to provide more accurate, context-aware, and personalized results.
Let’s explore how AI-driven search is reshaping personalization and user engagement, and why businesses that ignore it risk falling behind.
Have you noticed how online searches have become more conversational? Whether it’s through voice assistants or typing out detailed queries like “What’s the best pizza near me?” or “How do I fix a leaky tap?” The way people search is changing rapidly. This growing trend toward natural language queries highlights the need for businesses to rethink how they handle search functionality and adapt to this new era of AI-powered search.
DeepSeek has made waves in the AI industry by claiming to have trained a 671-billion-parameter model for just $6 million—a fraction of the budget typically required by industry leaders like OpenAI and Meta. To put this into perspective, Meta’s Llama 3 training required 30.8 million GPU hours, while DeepSeek achieved similar results with just 2.8 million hours. This raises an intriguing question: was this cost-saving feat driven by hardware innovations such as TPU clusters, or was it the result of sophisticated software optimizations?
New research from Epsilon shows that most people, about 80%, are more likely to buy something when brands make their shopping experience feel personal and special. This shows how important predictive analytics is for e-commerce businesses. Predicting customer needs using data is essential for staying ahead in the competitive world of e-commerce. Let’s explore how data analytics can help us predict shopping trends, make better decisions, and create personalized experiences that drive success.
Did you know that 35% of what customers purchase on Amazon is directly influenced by its recommendation algorithms? That’s not just a number but a proof of how transformative machine learning (ML) has become in shaping modern e-commerce. In an industry where consumer preferences evolve faster than trends, personalized product recommendations are a key driver for driving sales and enhancing user satisfaction. Let’s dive into how machine learning optimizes product recommendations and why this technology is indispensable for e-commerce businesses.
Artificial intelligence has long struggled to replicate the adaptive reasoning of the human mind. DeepSeek-R1 is a groundbreaking AI model that bridges the gap between machine logic and human-like thinking. It combines cutting-edge techniques like Mixture-of-Experts (MoE) and Multi-Head Latent Attention (MLA) to solve complex problems with unprecedented accuracy and efficiency.
In this article, we’ll explore the science behind DeepSeek-R1, how it mirrors human cognition, and reveal its real-world applications revolutionizing industries from healthcare to finance.
In a world where businesses are rapidly globalizing, the act of scaling beyond one’s borders, especially a robust market like India, is both exhilarating and daunting. India, with its vast consumer base, diverse demographics, and technological adaptability, offers unique opportunities and challenges. However, taking your business beyond this subcontinent requires not just ambition but a well-crafted strategy that ensures both effective and efficient expansion.
In the digital age, where technology reigns supreme, the success of a business hinges heavily on its technical prowess. At the core of this prowess lies a dedicated team of developers, the architects of innovation. But how do you go about assembling this dream team? It starts with recognizing that recruiting top developers isn’t just about evaluating their code; it’s about understanding their aspirations, motivations, and ensuring that they align with your company’s vision.
Navigating the journey from a budding startup to a successful scaleup is a thrilling endeavor. Central to this voyage is the engineering team — the unsung heroes behind every line of code, every feature launched, and every problem solved. However, as your company expands through staff augmentation, so does the complexity of managing and scaling this critical team.
When blockchain technology first emerged, it was seen primarily as the underlying technology for cryptocurrencies like Bitcoin. While cryptocurrencies continue to capture headlines, it’s becoming increasingly clear that blockchain has far broader applications. This technology is poised to disrupt traditional business models and transform various sectors, from healthcare and finance to logistics and real estate. Let’s explore the myriad use cases of blockchain technology and the opportunities it presents for businesses beyond cryptocurrency.
As we propel further into the 21st century, the digital world continues to grow, intertwining itself inextricably into our everyday lives. E-commerce, in particular, has seen exponential growth over the last decade, largely driven by advancements in IT and digital product development.
The road from startup to scaleup is exciting yet filled with hurdles, particularly when scaling the development team. While securing funding is a significant achievement, it comes with an array of challenges that need strategic consideration.
We’ve already discussed what has been going on in the back-end of the Labster platform, an exciting project which glimpses into the future of education. Rollout has been helping Labster with several senior backend, frontend engineers, and QA testers (altogether 11 IT professionals). This time we share Judit’s experience, who was a member of the testing team. She played a crucial role in safeguarding the complex transition of the Labster web portal.
Relate is a web platform, still under development, that brings forward a new way of working with information.
It’s layered and it gives you a very visual way of organizing things in space. Inside this space you can actually work, it’s not just about note taking or organizing. You really bring your information in there to work with it. So while you work, you organize things and it’s easy for people to work with you.
The metaverse is the next big thing in technology. Key stakeholders claim it will change the way we work, relax and socialize, and will allow users to fully immerse themselves in an online tailored experience.
This article will explore the metaverse as an opportunity for developers, identifying the key stakeholders, skills, and opportunities this new technology brings.
Did you know that Google’s monorepo contains over 2 billion lines of code across 9 million source files? This staggering scale highlights the immense challenges developers face when working with large codebases.
Git, the distributed version control system created by Linus Torvalds, has become the de facto standard for managing source code. Its powerful branching and merging capabilities make it an excellent choice for handling code repositories. However, as we’ll see, Git faces some challenges when dealing with extremely large repositories.
Today we will learn about how developers can easily manage the monorepo codebase in git using git’s sparse index feature.
In software development, AI-powered tools have emerged as a developer productivity suite, and Cursor AI is at the forefront of this improved productivity workflow. As seasoned developers, we’ve seen many IDEs and code editors. But when Cursor AI burst launched, it was clear that this was something special. In this article, we’ll dive deep into why Cursor AI is winning the hearts (and keystrokes) of developers worldwide.
In the world of mobile app development, developers are always looking to improve efficiency, speed, and reliability. Rust is a programming language that’s becoming more popular for this reason. It offers unique features that make it great for creating apps that run fast, are secure, and can handle a lot of users.
This article will show how Rust can make your mobile app development better. We’ll talk about how it helps with performance, keeps data safe, handles many tasks at once, and works on different platforms.
Rust is a systems programming language which has captured the attention of developers worldwide. Its implementation of speed, safety, and concurrency has driven many to explore its potential. However, understanding Rust’s ecosystem is crucial for effectively leveraging its power. This blog will explain the core components, tools, and give exposure to the libraries that shape Rust’s ecosystem, providing insights for digital product developers.
Many companies write softwares that faces security threats and vulnerabilities. These threats can lead to data breaches and cyber-attacks, costing companies a lot of money and damaging their reputation. Consequently, the loss of trust also causes a decline in customer confidence. Since the digital age began, developers have written software in many programming languages. However, human errors and complex code can expose a company’s data. These problems create vulnerabilities that stress the IT department and company stakeholders.
The foundation of technology and its advancement rely on the excellence of programming and development. The dramatic shift of day-to-day activities toward digital means is a testament to the spectacular growth of computer systems and software. This excellence would have never occurred without programming technologies like Rust.
