AI/ML Resources

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

· 2,759 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

· 16,147 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

· 5,729 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

· 4,047 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

· 3,051 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

· 5,986 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

· 4,287 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

· 3,385 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

· 3,328 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

· 3,938 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

· 3,433 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

· 7,389 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

· 24,281 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

· 3,765 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

· 4,013 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

· 4,720 Views · 5 Likes

Developers Beware: Slopsquatting and Vibe Coding Can Increase Risk of AI-Powered Attacks

Slopsquatting and vibe coding are fueling a new wave of AI-driven cyberattacks, exposing developers to hidden risks through fake, hallucinated packages.

May 14, 2025

by Aminu Abdullahi

· 4,654 Views · 2 Likes

Unlocking AI Coding Assistants: Generate Unit Tests

This blog post instructs on creating qualitative unit tests for a Spring Boot application using an AI coding assistant and its capabilities and limitations.

May 14, 2025

by Gunter Rotsaert

CORE

· 4,143 Views · 2 Likes

Beyond Code Coverage: A Risk-Driven Revolution in Software Testing With Machine Learning

Machine learning-driven, risk-based testing targets critical risks, automates test selection, and improves software reliability.

May 14, 2025

by Gopinath Kathiresan

· 3,974 Views · 2 Likes

Intro to RAG: Foundations of Retrieval Augmented Generation, Part 1

Retrieval-augmented generation (RAG) retrieves relevant information from external sources to improve the accuracy and reliability of responses, making it a powerful tool.

May 14, 2025

by Jennifer Reif

CORE

· 3,441 Views · 3 Likes

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