The companies building drugs — and the machines that design them Artificial intelligence in drug discovery has moved past the hype cycle and into its most critical phase: proof. After nearly a decade of investment, 2026 is shaping up to be an inflection point. The industry is now asking harder questions: Can AI actually produce

Scientists are uncovering a subtle but powerful signal hidden within the sleeping brain, one that may reveal how quickly the brain is aging and how that relates to future dementia risk. By analyzing intricate EEG patterns with machine learning, researchers identified measurable differences between biological and chronological brain age. Credit: Shutterstock A hidden signature in

Deploying a new machine learning model to production is one of the most critical stages of the ML lifecycle. Even if a model performs well on validation and test datasets, directly replacing the existing production model can be risky. Offline evaluation rarely captures the full complexity of real-world environments—data distributions may shift, user behavior can

Medical Xpress March 20, 2026 Institute of Science Tokyo A computational method called scSurv, developed by researchers at Institute of Science Tokyo, links individual cells to patient outcomes using widely available bulk RNA sequencing data. The approach uses single-cell reference datasets together with patient survival data to infer the contributions of individual cells within complex

As enterprises scramble to deploy AI, the Great AI Debate’s eighth installment reveals a widening gap between what vendors are selling and what actually works at scale. Dr. Michael Wu and Jon Reed spent this episode cutting through the hype around language models, domain expertise, and the financial reality of building sustainable AI systems; and they didn’t pull punches about

The National Highways Authority of India (NHAI) is preparing to introduce an advanced AI-powered monitoring system across nearly 40,000 km of national highways. This move is aimed at making road management more efficient and data-driven. At the core of this plan is a system called Dashcam Analytics Services (DAS), which uses Artificial Intelligence (AI) and

Summary: New research argues that the failure of AI in the workplace is rarely due to a lack of “intelligence,” but rather a lack of “cognitive alignment.” The study suggests that treating AI as a “plug-and-play” tool creates friction because humans and machines process information using fundamentally different logic. To succeed, teams must move toward

Generative AI is practically universal among British students. But a new survey reveals a major gap between how students use AI and how well universities support them. In just three years, generative AI has gone from novelty to standard practice at UK universities. According to the Higher Education Policy Institute's (HEPI) Student Generative AI Survey