Imagine a world where artificial intelligence churns out texts and images at an unprecedented scale, yet a leading expert questions whether this technological marvel is just a wasteful gimmick. On December 3, via a post on X, Timnit Gebru, a renowned figure in AI ethics, spotlighted the work of
In an era where global threats morph with alarming speed—from cyberattacks crippling infrastructure to terrorism exploiting digital shadows—the race to safeguard nations has never been more urgent or complex, demanding cutting-edge innovations to stay ahead of adversaries. The landscape of national
Deep image models have dazzled with accuracy, yet the most consequential story sat just out of view: not single neurons lighting up for neat human concepts, but webs of interconnected units assembling meaning layer by layer into circuits that actually drive what the model predicts and why it
Dustin Trainor sits down with Laurent Giraid, a technologist steeped in AI systems, machine learning, and the ethics that keep them safe and useful at scale. With MCP crossing its first year and surging to nearly two thousand servers, the conversation spans the hard edges of taking agentic systems
From dazzle to discipline: why backend intelligence now sets the pace When quarter-end pressure collides with fragile supply chains and fast-changing compliance rules, the flashiest AI rarely protects margins; the quiet systems buried in procurement, finance, and risk stacks are the ones that keep
Imagine a scenario where millions of dollars are poured into cutting-edge technology—AI, cloud services, and advanced applications—yet a significant portion of that investment fails to deliver expected returns. This is not a hypothetical situation but a reality for many organizations grappling with
