Let’s be honest — for a long time, AMD wasn’t the first name that came up in conversations about AI hardware. Powerful? Sure. Affordable? Often. But in the high-stakes race for training massive models and deploying them at scale? NVIDIA had the stage. That’s why this week’s reveal hit differently.
Over the past few years, edge computing has quietly moved from theory to frontline reality. It’s in factories, ports, trucks, remote retail branches, city infrastructure — often in places without stable power, climate control, or even a human nearby. And while early proof-of-concept demos looked clean and promising, scaling secure,
Let’s face it: relying on a single cloud provider in today’s world feels… risky. Outages happen. Costs spike. Regions go down without warning. That’s why more and more enterprise teams are leaning into multi-cloud setups. But here’s the catch — stitching together networks across different clouds isn’t as simple as
The job market for network pros is picking up again. That’s the good news. But before you dust off your resume and start listing every router you’ve ever touched — take a breath. Things have changed. A few years ago, knowing your way around OSPF, stacking switches, maybe a CCNP
