Articles from WebProNews

After more than two years of breathless investment and sky-high expectations, enterprise generative AI is running headlong into a wall of practical limitations. Companies have poured billions into large language models, prompt engineering teams, and AI-powered prototypes, yet the gap between dazzling demos and reliable production systems remains stubbornly wide. A growing chorus of technologists and enterprise leaders is now asking an uncomfortable question: Is the current approach to generative AI fundamentally broken for business use?

Richard Blumenthal, the former Democratic senator from Connecticut who spent years as one of Washington’s most vocal critics of Big Tech, has turned his attention to what he describes as a critical national security vulnerability: the alleged facilitation of Iranian transactions through Binance, the world’s largest cryptocurrency exchange. The inquiry, first reported by The New York Times, marks a new chapter in the ongoing tension between cryptocurrency platforms and U.S.

For the better part of three years, Nvidia has been the undisputed kingmaker of the artificial intelligence boom, its data center GPUs powering the massive compute infrastructure behind ChatGPT, Gemini, and virtually every large language model of consequence. But now, the company led by Jensen Huang is making a calculated move back toward a market it once dominated and then largely ceded to competitors: the consumer PC.

A team of researchers has demonstrated a technique that can detect whether a smartphone has been tampered with — without ever touching the device, and from distances of over a mile. The method, which relies on analyzing the unique radio frequency emissions of a phone’s hardware, represents a significant advance in the ongoing battle against supply chain attacks and firmware-level compromises that have bedeviled governments and enterprises for years.