AI/ML Resources

What AI Systems Taught Us About the Limits of Chaos Engineering

AI-driven infrastructure is non-deterministic. Chaos testing ensures systems maintain intended behavior under stress, improving reliability and safety.

April 22, 2026

by Sayali Patil

· 9,389 Views · 6 Likes

Designing a “People You May Know” System With Graph Neural Networks

This article explains a practical design for a LinkedIn-style “People You May Know” system, focusing on real-world tradeoffs, graph embeddings, and low-latency serving.

April 22, 2026

by Deepu Komati

· 2,609 Views · 2 Likes

AWS Bedrock: The Future of Enterprise AI

Amazon Bedrock simplifies enterprise AI with multi-model access, built-in security, RAG, and scalable, no-infrastructure deployment.

April 21, 2026

by Subrahmanyam Katta

· 5,234 Views · 2 Likes

Demystifying Intelligent Integration: AI and ML in Hybrid Clouds

AI and ML are transforming hybrid clouds with edge intelligence, federated learning, and explainable, scalable integration.

April 21, 2026

by Abhijit Roy

· 3,523 Views

SPACE Framework in the AI Era: Why Developer Productivity Metrics Need a Rethink Right Now

AI coding tools boost commit metrics, but hide deeper issues. Learn how the SPACE framework reveals real developer productivity beyond traditional DevOps metrics.

April 21, 2026

by Sreejith Velappan

· 3,368 Views

Solving the AI Accountability Gap: The Fact-Based Labeling (FBL) Framework

The Fact-Based Labeling framework replaces ‘black-box’ flags with machine-extracted facts that trigger structured human questionnaires for consistent content governance.

April 21, 2026

by Prachi Priyam

· 2,029 Views

Architecting AI-Native Cloud Platforms: Signals to Insights to Actions

AI-native platforms embed intelligence into cloud infrastructure, allowing systems to sense events, generate insights with AI, and trigger automated actions in real time.

April 21, 2026

by Harvendra Singh

· 2,295 Views

Quality Assurance in AI-Driven Business Evolution

QA is evolving for AI-driven business, focusing on data quality, model validation, and risk management to ensure reliable, trustworthy, well-governed systems.

April 20, 2026

by Parimal Kumar

· 4,029 Views

Hidden Cyber Threat AI Is Preparing That Some Companies Aren't Thinking About

The rapid and unpredictable progression of AI capabilities suggests that their advancement may soon rival the immense power of the human brain.

April 20, 2026

by Francis Ejiofor

· 2,700 Views

Securing AI Agents: Agent Logging, Visibility, and Data Protection

AI agents create a logging paradox: too little visibility is dangerous, too much creates data leaks. Here's how to design telemetry that solves both.

April 20, 2026

by Alvin Lee

CORE

· 3,078 Views · 1 Like

Why Every Defense Against Prompt Injection Gets Broken — And What to Build Instead

Twelve LLM prompt injection defenses were tested, and all bypassed. Stop relying on perimeter filters. Strip model privileges and design for containment instead.

April 20, 2026

by Dinesh Elumalai

CORE

· 4,240 Views · 1 Like

Gemini Agent vs Microsoft Copilot vs ChatGPT Operator: How They Compare

AI is shifting from chat to action. Learn how Agentic AI, Copilots, and Operators differ in architecture, capability, and autonomy.

April 20, 2026

by Jubin Soni, FBCS

CORE

· 1,981 Views

Context Lakes: The Infrastructure Layer AI Agents Need That Doesn't Exist Yet

No composition of feature stores, vector DBs, and stream processors can guarantee Decision Coherence. Here's the correctness gap in multi-agent systems.

April 17, 2026

by Angela Zhao

· 2,778 Views

Training a Neural Network Model With Java and TensorFlow

Learn how to train a neural network model using the TensorFlow platform with Java and using a pre-trained model in a proper Spring Boot application.

April 17, 2026

by George Pod

· 3,387 Views · 1 Like

AI-Powered Dev Workflows: How SWEs Are Shipping Faster in 2026

Boost your velocity with AI-orchestrated workflows. Learn best practices for prompt engineering, automated reviews, and secure code generation.

April 17, 2026

by Jubin Soni, FBCS

CORE

· 3,056 Views · 1 Like

Beyond Fail-Safe: Designing Fail-Operational State Machines for Physical AI

When encountering a fault, physical AI cannot return error codes or reset. It must be fail-operational to safely degrade functionality and maintain physical control.

April 16, 2026

by Nishant Bhanot

· 3,068 Views · 1 Like

How To Build A White-label AI Chatbot: Here's the Complete Process

Steps to build a fully white-label AI chatbot using RAG-based conversational AI, STT/TTS, and a low-code JavaScript widget.

April 16, 2026

by Alexander Samuel

· 2,915 Views

Stop Burning Money on AI Inference: A Cloud-Agnostic Guide to Serverless Cost Optimization

Most teams waste money on AI inference. Five cloud-agnostic tactics—model routing, prompt trimming, response caching, smart batching, GPU offloading—can cut costs 40‑80%.

April 16, 2026

by Rajesh Kumar Pandey

· 3,086 Views · 1 Like