The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs

Across 107 enterprises, AI infrastructure spending is accelerating well ahead of the ability to see or steer its economics. Most organizations run their AI on a familiar base of hyperscalers and model-provider APIs, yet the next dollar is aimed at specialized compute almost none of them use today; a majority intend to switch or add …

Facial movement analysis detects deepfake videos with more than 95% accuracy

So-called deepfakes, that is, images and videos generated with the help of artificial intelligence, are becoming increasingly difficult to detect. An international research team from the University of Tokyo and the Max Planck Institute for Informatics in Saarbrücken, Germany, has developed a method that identifies manipulated videos more reliably than previous approaches—not by searching for …

Agentic orchestration: Enterprise AI organizations have a deployment problem, not a platform problem — and most are calling chatbots agents

Across 101 enterprises, agent orchestration is consolidating onto model-provider platforms — Anthropic’s Claude leads by a wide margin — chosen for the gravity of the underlying model and judged on reliable multi-step execution. But the ambition runs well ahead of the reality: most deployed “agents” are still chatbot wrappers, the control plane enterprises expect is …

Alan Turing’s biggest AI assumption may have been wrong

A new book claims AI has been built on a flawed assumption dating back to Alan Turing’s famous 1950 paper. Peter J. Denning argues that the most important parts of human intelligence, including common sense, intuition, culture, and practical know-how, cannot be encoded into computers. He believes this makes true human-level AI impossible, regardless of …

AI agents create virtual playgrounds to help robots get crucial training data

Robots walking down the street, surrounded by astounded onlookers, are an increasingly common sight. But these machines aren’t yet the do-it-all assistants you’d want working in a kitchen or factory, and a major bottleneck is data. Much like humans, robots learn best by experience. The challenge is that it’s labor-intensive and time-consuming to physically teach …