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Optimising Data for AI: 6 Backend Storage Techniques for Fast Model Training
In the age of artificial intelligence, speed is everything. From training models to deploying them in production, efficiency can make or break your competitive edge. And at the heart of it all? Data. More specifically, how that data is stored, retrieved, and processed. In this post, we explore six powerful backend storage techniques that are essential for fast model training and…
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Understanding Angular Change Detection: How It Works and How to Optimize It
Angular is a powerful framework for building dynamic web applications. One of its core features is change detection, a mechanism that keeps your view in sync with your data model. However, when building large-scale applications, change detection can become a performance bottleneck if not properly optimized. This blog will explain how Angular’s change detection works and…
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Vector Databases vs. Relational: 6 Big Differences You Should Care About
In the evolving world of data infrastructure, choosing the right type of database is more crucial than ever. With the rise of AI-powered applications, traditional data systems are being challenged by newer technologies. One debate making waves today is vector databases vs. relational databases two very different approaches to storing and retrieving information. But what sets them…
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Building Fast AI Search: 8 Reasons to Use Vector Databases in Your Backend
Traditional search methods rely on keyword matching, which often fails to capture the intent and context of user queries. As AI-powered applications continue to evolve, vector databases have emerged as a critical solution for enabling fast, intelligent, and accurate search experiences. By leveraging high-dimensional vector representations, vector databases can power real-time AI search with unmatched speed and accuracy. In this article,…
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Node.js Best Practices: 8 Critical Tips for Building Scalable Microservices
Microservices architecture has become a go-to approach for building scalable and maintainable applications, and Node.js is one of the most popular frameworks for developing them. With its event-driven, non-blocking I/O model, Node.js enables high-performance microservices that can efficiently handle concurrent requests.However, building scalable microservices in Node.js requires best practices to ensure performance, reliability, and maintainability. In this guide, we’ll cover eight critical tips to help you design efficient, robust,…
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OpenSearch AI Integration: 6 Smart Ways to Enhance Search with Machine Learning
In the modern digital age, delivering highly relevant and personalised search results is crucial for user satisfaction and business success. Integrating AI and machine learning with your search engine can unlock new levels of intelligence, enabling dynamic results that go beyond traditional keyword matching. OpenSearch, a powerful open-source search engine, provides a flexible platform for integrating AI and machine…
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Scaling OpenSearch: 8 Powerful Strategies for High-Performance Backends
When it comes to powering high-performance search solutions, OpenSearch is a popular choice for many organisations. However, ensuring optimal performance at scale is essential for delivering fast and reliable results. Whether you’re dealing with large datasets or high query volumes, scaling OpenSearch effectively is key to maintaining a responsive and robust backend. In this article, we explore 8 powerful strategies that…
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Node.js and AI: 7 Powerful Libraries for Machine Learning Applications
The rapid advancement of artificial intelligence (AI) and machine learning (ML) has opened new opportunities for developers using Node.js. While Python has traditionally dominated the AI space, JavaScript powered by Node.js is making significant strides in the ML ecosystem. Thanks to a growing number of AI focused libraries, Node.js developers can now build intelligent applications without switching to another programming language. In…
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Backend AI Pipelines: 10 Critical Steps to Automate Machine Learning Workflows
In the world of machine learning (ML), managing the full lifecycle of data from ingestion to model deployment can be overwhelming. Building backend AI pipelines that automate and streamline this workflow is crucial for scaling AI systems and ensuring the quality and consistency of results. In this article, we’ll explore the 10 critical steps to create automated and efficient AI pipelines,…
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Understanding Node.js Event Loop: How It Works and Why It’s Crucial for Performance
In the world of modern web development, performance and scalability are everything. Whether you’re handling a few thousand concurrent users or building real-time applications that respond instantly, one feature in Node.js quietly powers it all: the Node.js Event Loop. Understanding how this mechanism works can help developers write more efficient code, troubleshoot bottlenecks, and build blazing-fast…