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Gone are the days when bankers had to deal with a huge pile of paperwork, and customers at banks had to wait in long queues to get a transaction done.
All thanks to technology, which has the potential to transform banking at an exponentially faster pace.
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.
The AI Security & Governance Report by Immuta analysed how data experts view artificial intelligence (AI). According to the report, 80% of these experts agree that AI is leading to more data security issues. As we move further into the age of AI-powered search systems, worries about privacy are growing for both businesses and individuals. These systems collect and use a lot of personal data, raising questions about how that information is handled. Let’s take a closer look at how these search systems work and why protecting privacy is so important.
Outsourcing software development is a popular and efficient way for companies to meet their goals. It helps businesses save money, grow their teams more quickly, and connect with highly skilled workers worldwide. However, outsourcing doesn’t come without challenges. One of the biggest concerns is cybersecurity. When companies outsource, they must take extra care to ensure that their sensitive information and systems remain protected. This guide explores essential cybersecurity practices that can help in-house and outsourced teams work together safely, preventing costly breaches and errors.
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.
The AI Security & Governance Report by Immuta analysed how data experts view artificial intelligence (AI). According to the report, 80% of these experts agree that AI is leading to more data security issues. As we move further into the age of AI-powered search systems, worries about privacy are growing for both businesses and individuals. These systems collect and use a lot of personal data, raising questions about how that information is handled. Let’s take a closer look at how these search systems work and why protecting privacy is so important.
The digital world moves faster every day. Businesses need software that works well to stay ahead. If there’s a bug or a delay, users quickly get frustrated and look for other options. AI-powered Quality Assurance (QA) helps solve these problems. It speeds up testing and makes it more accurate. It finds bugs early, which helps businesses keep customers happy.
Reliable software isn’t just nice to have anymore but it’s something every company must deliver. Let’s explore how AI improves testing, saves time, and helps companies create better software for their users.
What Are AI Chatbots, and Why Should We Care?
AI chatbots are more than just smart assistants. They’re tools powered by artificial intelligence to interact with humans naturally. But beyond their basic function, AI chatbots are transforming how education works and are providing the way for a more personalized and accessible learning experience for every student. Let’s take a closer look at how they’re reshaping the educational landscape.
Gone are the days when bankers had to deal with a huge pile of paperwork, and customers at banks had to wait in long queues to get a transaction done.
All thanks to technology, which has the potential to transform banking at an exponentially faster pace.
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.
When you're entrusting important business operations to an external partner, the stakes are high. Your success depends not just on their technical or operational capabilities, but on the strength of your relationship with them. Long-term outsourcing partnerships require more than transactional interactions and they demand a foundation built on trust, transparency, and mutual respect.
Creating a Minimum Viable Product (MVP) and growing it into a successful digital product is tough. It needs the right partner. Picking the wrong agency can cause delays, missed chances, and a less than perfect product. But how do you make sure you pick the right agency for your MVP? We'll help you check out agencies, see what they know, and find the best one for your business.
In the fast-paced world of product development, launching a successful MVP is key. It helps businesses test their ideas, get customer feedback, and set the stage for growth. The key to success lies in picking the right core features and KPIs that match your goals and what users want.
This article will walk you through the steps to pinpoint the core elements for your MVP's success.
The world of tech is growing fast. New and cool things are popping up all the time. However, this surge in innovation has created a parallel challenge and that is the gap of skills among the vast options available in tech. The demand for highly skilled developers, data scientists, cybersecurity experts, and other tech talent far outpaces the supply when we see from the perspective of a single technology culture enforced in an organization. That forces businesses to spend time and resources in upskilling developers in new cultures.
Looking for an exceptional team that is dedicated to delivering exceptional solutions? Rollout IT has you covered. Established in 2018, we are a team of award-winning professionals ready to take on whatever challenges thrown our way. We’re committed to guiding our partners and delivering the best solutions they need to excel.
Are you excited to work on the development of your digital products but overwhelmed and confused? Are you looking for a checklist to build up your confidence to develop your product (and earn profits)? Then, this is the right reading for you. We are providing you with a seven-step process that will help you out in your digital product development journey.
IT is one of the core expensive components of any enterprise. Most of these industries require IT developers for digital product development. Companies implement this strategy by hiring skilled professionals from other sources, typically through staffing agencies or specialized firms, to work on in-house projects. According to the Bureau of Labor Statistics, the demand for IT Staff Augmentation roles is expected to grow 35% by 2030.
Gone are the days when bankers had to deal with a huge pile of paperwork, and customers at banks had to wait in long queues to get a transaction done.
All thanks to technology, which has the potential to transform banking at an exponentially faster pace.
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.
The AI Security & Governance Report by Immuta analysed how data experts view artificial intelligence (AI). According to the report, 80% of these experts agree that AI is leading to more data security issues. As we move further into the age of AI-powered search systems, worries about privacy are growing for both businesses and individuals. These systems collect and use a lot of personal data, raising questions about how that information is handled. Let’s take a closer look at how these search systems work and why protecting privacy is so important.
Outsourcing software development is a popular and efficient way for companies to meet their goals. It helps businesses save money, grow their teams more quickly, and connect with highly skilled workers worldwide. However, outsourcing doesn’t come without challenges. One of the biggest concerns is cybersecurity. When companies outsource, they must take extra care to ensure that their sensitive information and systems remain protected. This guide explores essential cybersecurity practices that can help in-house and outsourced teams work together safely, preventing costly breaches and errors.
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.
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.
Blockchain technology has gained widespread attention in recent years, and its impact on business and industry is expected to be significant. A blockchain is a decentralized, digital ledger that is used to securely record transactions and other data in a tamper-proof manner. This technology has the potential to revolutionize the way that businesses operate and interact with one another.
Blockchain development is a rapidly growing field that has the potential to revolutionize a wide range of industries. From finance and healthcare to supply chain management and voting systems, the potential applications of blockchain technology are virtually limitless.
The digital world moves faster every day. Businesses need software that works well to stay ahead. If there’s a bug or a delay, users quickly get frustrated and look for other options. AI-powered Quality Assurance (QA) helps solve these problems. It speeds up testing and makes it more accurate. It finds bugs early, which helps businesses keep customers happy.
Reliable software isn’t just nice to have anymore but it’s something every company must deliver. Let’s explore how AI improves testing, saves time, and helps companies create better software for their users.
As we usher in a new era of digital innovation, the development of digital products continues to evolve at a rapid pace. It’s an exciting time, filled with infinite possibilities. Yet, with this progress comes increased competition and more discerning consumers. To navigate this landscape successfully, the importance of user testing and User Experience (UX) research in digital product development cannot be overstated.
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.
Peer review dates back to 1731 when the Royal Society of Edinburgh had a system in place to review medical articles for publications, scientists used to circulate their research papers among their peers to elicit responses or critiques which helped them better their work, from then on peer review has trickled down to every field that requires constant improvement and innovations.
Did you know that 88% of online consumers are less likely to return to a website after a bad experience? That’s like losing almost nine out of every ten visitors because they couldn’t navigate smoothly. Think of the impact on your business if this happens repeatedly.
This statistic highlights the importance of user experience in digital product design. Design Thinking plays a key role here by focussing on the user experience right from the start to make every step intuitive and seamless. Let’s explore how this methodology transforms digital design.
What if the digital product you've built and invested time into is unknowingly excluding millions of potential users? In our rush to create sleek, feature-rich websites and apps, we may be building barriers instead of bridges? We often tend to overlook digital accessibility but it has a deep impact.
You may face a wake-up call when it comes to digital accessibility and conducting its audit. Perhaps we should realize that creating truly inclusive digital products isn't just a nice-to-have feature but it's essential.
The Apple Vision Pro has swiftly become a focal point in the tech world, captivating both users and observers. Videos circulating on social media platforms like TikTok showcase individuals navigating streets, riding the tube, and interacting with their surroundings in seemingly unconventional ways, such as waving their hands or pointing into the void.
Apple Vision Pro is set to redefine the boundaries of technology. With expectations of unparalleled computational power, superior graphics, and innovative user interfaces, Apple is poised to set a new benchmark in technological prowess. The implications for businesses are vast, offering tools and features that were, until now, the stuff of imagination.
At Rollout IT, we are excited to embrace the frontier of Apple VisionOS, a groundbreaking platform that represents a quantum leap in the realm of spatial computing. Our focus is to harness the full capabilities of VisionOS to develop high-level professional applications that redefine user experience and interaction. Here’s how we are gearing up to master the technical intricacies and possibilities of VisionOS.
In the vast ocean of tech innovation, few brands make as resounding a splash as Apple. And with the introduction of the Vision Pro, Apple has once again set the gold standard for future devices. While the device itself boasts a litany of cutting-edge features, the true potential of the Vision Pro is unlocked when developers rise to the challenge, leveraging its capabilities to birth groundbreaking applications. This article serves as a compass, guiding developers through the intricacies of mastering development for this technological marvel.
As we usher in a new era of digital innovation, the development of digital products continues to evolve at a rapid pace. It’s an exciting time, filled with infinite possibilities. Yet, with this progress comes increased competition and more discerning consumers. To navigate this landscape successfully, the importance of user testing and User Experience (UX) research in digital product development cannot be overstated.
Navigating the digital universe often feels like solving a Rubik’s cube: intriguing yet complex, challenging yet rewarding. One of the most consequential choices in this voyage is selecting the perfect tech stack for your digital product — a decision that CTOs, developers, and top managers grapple with as they balance project requirements, market trends, and future growth prospects.
As we move into a new era of technological innovation, user interfaces (UI) are evolving at a rapid pace. Voice and conversational interfaces are emerging as a key component in the future of UI, offering users a more natural and intuitive way to interact with digital products.
Gone are the days when bankers had to deal with a huge pile of paperwork, and customers at banks had to wait in long queues to get a transaction done.
All thanks to technology, which has the potential to transform banking at an exponentially faster pace.
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?
Evolution of cloud computing has significantly transformed how modern applications are designed and deployed. For organizations aiming to scale their operations and designing a robust and scalable cloud-native architecture is no longer optional.
What is Cloud-Native Architecture?
Cloud-native architecture refers to an approach for designing applications that fully exploit the inherent benefits of cloud computing. These benefits include scalability, flexibility, high availability, and cost efficiency. This model leverages advanced concepts like microservices, containerization, and orchestration to ensure applications are optimized for dynamic, distributed environments.
Having delved into the foundational concepts and strategic implementations of cloud technologies in the previous parts, it’s essential to address the challenges that startups might face. Moreover, staying updated with future trends and having the right resources at hand can be the difference between mere survival and thriving in the competitive landscape.
In Part 1, we explored the foundational concepts of scalability and the basics of cloud technologies. As we venture further, it’s crucial to understand how startups can strategically implement these technologies. Moreover, real-world case studies can offer invaluable insights into the practical applications and benefits of cloud scalability.
In the dynamic world of startups, scalability isn’t just a buzzword; it’s a necessity. As startups grow, their infrastructure and operations must evolve to handle increased demand. Enter cloud technologies, a game-changer that offers startups the flexibility, cost-efficiency, and global reach they need to scale effectively.
The digital age has given rise to a vast array of software architecture patterns. Two of the most debated structures are microservices and monolithic architectures. While both have their merits, each also has its own set of drawbacks. If you’re a software architect, CTO, or any stakeholder in the IT industry, understanding these patterns can greatly influence the efficiency, scalability, and long-term success of your applications. Let’s embark on a journey to dissect these architectures and weigh their pros and cons.
In the landscape of digital transformation, cloud computing has become a critical pillar. It has fundamentally reshaped how businesses operate and innovate, offering scalability, flexibility, and cost-effectiveness. As cloud computing continues to evolve, new trends are emerging, offering novel ways to leverage this transformative technology. This article explores three of these key trends: serverless computing, edge computing, and hybrid cloud.
The business world is in the midst of a seismic transformation, fueled by the rapid pace of technological advancement and an ever-increasing demand for operational efficiency. At the epicenter of this shift, cloud-native application development stands as a powerful tool that can reshape not just how businesses operate, but how they create, adapt, and deliver value.
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?
In this guide, we'll show you how to use Cursor AI along with Superwhisper to create a Python script without typing code. This means you can build, edit, and troubleshoot your code just by using your voice.
Whether you're someone who prefers hands-free interaction or just looking to boost productivity, these tools make coding more accessible and efficient.
Today, we're diving into Git rebase, a tool that, once mastered, can help us manage branches in a clean and efficient manner, ensuring our commit history remains tidy and linear. We’ll discuss how to use Git rebase effectively, including practical tips and common pitfalls.
Artificial intelligence is rapidly transforming how developers approach coding tasks, and Cursor AI is one of the tools that aims to improve the way we code by offering powerful AI integrations. One of Cursor AI's standout features is its ability to customize and apply AI rules to different coding environments, enhancing the precision and efficiency of your code generation process.
Did you know that developers spend an average of 17.3 hours per week debugging code? That's nearly half of a typical work week! But what if we told you there's a tool that could dramatically reduce this time and boost your overall productivity? Cursor AI is the new Integrated Development Environment (IDE) that's revolutionizing the way we code and debug.
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.
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