A new Governance AI study reveals that EU data protection rules are stalling AI adoption, leaving 11% of advanced LLM ...

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.

Chinese AI models are rapidly closing the gap with U.S. frontier systems. This analysis examines what their growing ...

Large language models (LLMs) are rapidly being integrated into clinical workflows, supporting tasks such as diagnosis ...

NLP and LLM teams often grow their training corpuses to improve model performance but they still do not always obtain ...

Every prompt your team sends to a language model is a potential data-exfiltration event. According to Cyberhaven's 2026 AI ...

The rapid adoption of large language model (LLM) systems across the federal government has prompted the U.S. General Services Administration (GSA) ...

Companies once measured AI by tokens burned. The real metric is whether your workflows survive when one lab pulls the model out from under you. Freedom from the Frontier.

GitHub shipped /security-review — a dedicated slash command for GitHub Copilot CLI — on Wednesday, putting AI-driven vulnerability scanning inside the terminal for the first time as an experimental ...

Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits. MeMo, a ...

Stanford University’s recent research, conducted in collaboration with Tsinghua University, has revealed a surprising shift in how we evaluate the performance of large language models (LLMs). Rather ...

Google, Microsoft and xAI will share unreleased versions of their AI models with the government to curb cybersecurity threats, the National Institute of Standards and Technology announced on Tuesday.