Creating high-quality multimodal training data is essential yet complex, involving challenges in synchronization, scalability, context capture, and tooling.
This article discuss how the original Agile Manifesto anticipated the rise of AI — and why both AI maximalists and AI luddites misunderstand its true message.
GPT-OSS:20B's MXFP4 quantization requires H100+ GPUs. Use GGUF quantized versions from Hugging Face for dramatically faster consumer hardware performance.
A simple AI-powered chatbot that work a contextual search engine powered by RAG and essentials concepts of AI like vector embeddings and cosine similarity search.
This blog provides a tutorial on how to integrate AI agents, specifically MCP agents, into your coding workflow using the DevoxxGenie plugin for JetBrains IDE.
Learn how to create a team chat application using Spring Boot and LangChain4j, featuring two AI assistants that communicate both with you and with each other.
MCP makes AI integration easy but opens new security risks-like shadow servers, prompt hijacking, and connector exploits. Learn how to secure your AI-powered workflows.
This guide covers AI infrastructure, from hardware acceleration and model serving to monitoring and security, with tools, patterns, and strategies proven in production.
October 2, 2025
by Vidyasagar (Sarath Chandra) Machupalli FBCS
CORE
This article demonstrates how we can run vLLM on Kubernetes for a centralized LLM serving engine that is production-ready and can be used by multiple applications.
This article demonstrates how vLLM is a game-changer for efficient GPU memory utilization and what makes it a high-throughput serving and inference engine.
Claude is a leading LLM for front-end development, though success ultimately depends more on implementation practices than on picking a single “best” model.