• ai

MCP vs. RAG: How AI Agents & LLMs Connect to Data

• 01 Apr, 2026

MCP vs. RAG: Como Agentes de IA e LLMs se conectam aos seus dados Você já sentiu que sua IA, apesar de poderosa, parece "travada" em uma bolha? Você tenta integrar dados específicos ou automatizar um

• ai

LLM Compression Explained: Build Faster, Efficient AI Models

• 31 Mar, 2026

LLM Compression Explained: Build Faster, Efficient AI Models Have you ever felt that while the future of AI is breathtaking, the sheer cost and sluggishness of running massive models are holding you

• ai

The Power of AI Agents and Agentic AI Explained

• 30 Mar, 2026

The Power of AI Agents and Agentic AI Explained Have you ever felt like you’re drowning in manual tasks, even though we’re supposedly living in the "AI era"? It’s frustrating to watch your to-do list

• ai

What Is an AI Stack? LLMs, RAG, & AI Hardware

• 26 Mar, 2026

Decoding the AI Stack: From Mystery to Mastery Ever feel like the world of AI is moving so fast that you’re just trying to keep your head above water? You hear terms like LLMs, RAG, and Vector Databa

• segurança

Every API Authentication Method Explained (Don’t Choose the Wrong One)

• 25 Mar, 2026

Você já passou horas desenvolvendo uma API incrível, só para travar completamente na hora de decidir como protegê-la? É um dilema comum. Se você escolhe um método simples demais, como o Basic Auth, p

• ai

What is Human In The Loop with AI? How HITL Shapes AI Systems

• 23 Mar, 2026

Have you ever felt like using Artificial Intelligence is a bit like shouting into a "black box"? You type in a command, cross your fingers, and just hope the result makes sense. The problem is that l

• ai

9 AI Concepts Explained in 7 minutes: AI Agents, RAGs, Tokenization, RLHF, Diffusion, LoRA...

• 18 Mar, 2026

Technical Brief: Core Generative AI Architectures and Implementation 1. Technical Overview This documentation provides a high-level technical synthesis of the foundational concepts driving modern

• ai

MCP vs API: Simplifying AI Agent Integration with External Data

• 11 Mar, 2026

1. Technical Overview The Model Context Protocol (MCP) is an open-standard communication protocol designed to replace the fragmented landscape of custom API integrations for Large Language Models (L

• ai

Spec-Driven Development: AI Assisted Coding Explained

• 10 Mar, 2026

Have you ever felt like you’re just "vibe coding"? You throw a prompt at an AI, cross your fingers, and hope the output actually fits your project. It feels more like a game of trial and error than a

• ai

Why AI Agents Need A Human in the Loop Now

• 10 Mar, 2026

Can AI agents succeed without humans? Anna Gutowska explains the importance of Human-in-the-Loop (HITL) systems for safe and ethical AI decision-making. Learn how HITL balances automation, compliance,

• mco

A2A vs MCP: AI Agent Communication Explained

• 10 Mar, 2026

Sobre o vídeo: Ready to become a certified watsonx AI Assistant Engineer v1 - Professional? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/BdpXdV Learn more about A

• podman

Podman pull images behind a corporate proxy

• 26 Nov, 2025

Today, I set out to pull an image from Docker Hub on a RHEL 9 system using Podman. This step was part of my journey to install Watson Code Assistant for Z. While Podman is a great alternative to Docker on RHEL, the process had its quirks—especially when working with enterprise environments and specialized tools like Watson Code Assistant. In this post, I’ll share what worked, what didn’t, and some tips to make the setup smoother for anyone tackling the same challenge. I can simulate the error using podman pull: podman pull docker.io/library/orientdb:3.2.28 Trying to pull docker.io/library/orientdb:3.2.28... WARN0000 Failed, retrying in 1s ... (1/3). Error: initializing source docker://or