AI/ML Resources

MCP Servers: The Technical Debt That Is Coming

MCP servers promise faster AI-driven orchestration through the use of natural language, but they risk becoming technical debt.

May 22, 2025

by Hugo Guerrero

CORE

· 8,342 Views · 3 Likes

Chat With Your Knowledge Base: A Hands-On Java and LangChain4j Guide

In this hands-on guide, you will learn to build a Java RAG chat application with LangChain4j to query your custom knowledge base.

May 22, 2025

by A N M Bazlur Rahman

CORE

· 5,790 Views · 7 Likes

GitHub Copilot's New AI Coding Agent Saves Developers Time – And Requires Their Oversight

GitHub has launched a powerful AI coding agent in Copilot that writes code, fixes bugs, and opens pull requests.

May 22, 2025

by Aminu Abdullahi

· 5,203 Views · 2 Likes

Intro to RAG: Foundations of Retrieval Augmented Generation, Part 2

Dive into different layers of retrieval-augmented generation, including vector RAG, graph RAG and agents, to explore how to create more powerful and effective AI systems.

May 22, 2025

by Jennifer Reif

CORE

· 2,554 Views · 3 Likes

AI Speaks for the World... But Whose Humanity Does It Learn From?

Generative AI claims to reflect humanity, but it mostly replicates the worldview of a connected, Western minority, shaping global outputs from partial data.

May 22, 2025

by Frederic Jacquet

CORE

· 2,892 Views · 1 Like

How To Introduce a New API Quickly Using Quarkus and ChatGPT

Stepping outside of my comfort zone, let’s see how quickly we can introduce an API-First-driven RESTful by leveraging ChatGPT, Quarkus, and Heroku.

May 21, 2025

by John Vester

CORE

· 16,207 Views · 3 Likes

The Future of Java and AI: Coding in 2025

Explore how Java developers are leveraging AI and modern frameworks like Quarkus to build cutting-edge applications in 2025.

May 21, 2025

by Daniel Oh

CORE

· 5,795 Views · 4 Likes

Securing the Future: Best Practices for Privacy and Data Governance in LLMOps

This article covers strategies for safeguarding sensitive data, enforcing compliance, and embedding responsible AI principles throughout the model lifecycle.

May 21, 2025

by Rajarshi Tarafdar

· 4,211 Views · 1 Like

Kullback–Leibler Divergence: Theory, Applications, and Implications

Kullback–Leibler divergence (KL divergence) is a statistical measure that quantifies how one probability distribution differs from a second reference distribution.

Updated May 20, 2025

by Shailendra Prajapati

· 3,093 Views

Building Reliable LLM-Powered Microservices With Kubernetes on AWS

This article explores how to design, build, and deploy reliable, scalable LLM-powered microservices using Kubernetes on AWS, covering best practices for infrastructure.

May 20, 2025

by Rajarshi Tarafdar

· 6,023 Views · 2 Likes

Building an AI/ML Data Lake With Apache Iceberg

Learn how Apache Iceberg powers AI/ML data lakes with time travel and schema flexibility, shown via a full Python-based feature store implementation.

May 20, 2025

by Anant Kumar

· 4,372 Views · 1 Like

Secrets Sprawl and AI: Why Your Non-Human Identities Need Attention Before You Deploy That LLM

Your RAG implementation can expose secrets in some unexpected ways. Secure your LLM deployments and scrub knowledge bases to prevent your secrets from leaking.

May 20, 2025

by Dwayne McDaniel

· 3,406 Views · 2 Likes

Operational Principles, Architecture, Benefits, and Limitations of Artificial Intelligence Large Language Models

Large Language Models (LLMs) are advanced AI systems that generate human-like text by learning from extensive datasets and employing deep learning neural networks.

May 19, 2025

by Venkata Suresh Babu Chilluri

· 3,387 Views · 1 Like

Navigating the LLM Landscape: A Comparative Analysis of Leading Large Language Models

Here is an in-depth analysis comparing top LLMs, including OpenAI and its exciting contenders like LangChain, Anthropic, Cohere, Google, and more.

Updated May 19, 2025

by Jorge Torres

· 3,974 Views · 2 Likes

AI-Driven Test Automation Techniques for Multimodal Systems

Learn how AI-powered test automation improves reliability and efficiency in multimodal AI systems by addressing complex testing challenges effectively.

May 19, 2025

by Gaurav Sharma

· 3,554 Views · 5 Likes

The Smart Way to Talk to Your Database: Why Hybrid API + NL2SQL Wins

Discover why the future of database interaction — it's a smart hybrid of solid backend architecture and AI-powered NL2SQL assistance.

May 19, 2025

by Dmitry Narizhnykh

CORE

· 7,430 Views · 3 Likes

Integrating Model Context Protocol (MCP) With Microsoft Copilot Studio AI Agents

Model Context Protocol (MCP) integrates seamlessly with Copilot Studio, enabling AI agents to access real-time data and interoperate.

May 19, 2025

by Aravind Nuthalapati

CORE

· 24,344 Views · 1 Like

The Full-Stack Developer's Blind Spot: Why Data Cleansing Shouldn't Be an Afterthought

Full-stack developers often focus on clean code but neglect clean data, leading to performance issues, security vulnerabilities, and frustrated users.

May 16, 2025

by Farah Kim

· 3,818 Views · 2 Likes

How Can Developers Drive Innovation by Combining IoT and AI?

Discover how developers can drive innovation by combining IoT and AI to create transformative solutions and unlock new opportunities across industries.

May 16, 2025

by Harris Anderson

· 4,059 Views · 2 Likes

AI-Driven Root Cause Analysis in SRE: Enhancing Incident Resolution

This article examines how AI is transforming root cause analysis (RCA) in Site Reliability Engineering by automating incident resolution and improving system reliability.

May 16, 2025

by Nikhil Kapoor

· 4,768 Views · 5 Likes

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