AI News Archive - Browse Page 25 of 160

Why does this matter now? Because 2026 marks a shift from sheer size to purpose. Large language models are being judged on safety, controllability...

Generative AI and autonomous agents are turning identity theft into a near‑industrial operation.

Why do groups of AI agents sometimes act like hidden teams? When multiple models interact, they can develop internal ties that aren’t obvious from...

Flow matching builds data by stepping through a learned velocity field, and each integration step—measured as number of function evaluations...

Chain‑of‑thought (CoT) prompting and reasoning‑tuned models such as DeepSeek‑R1 are often praised for “thinking” their way past shallow heuristics.

Why does long‑context inference still choke on memory? In large language models the key‑value cache expands linearly with each processed token,...

Anthropic says the stories we tell about AI can shape how the systems behave. During pre‑release testing of Claude Opus 4, engineers observed the...

Why does this matter? As of May 10, 2026, Hermes Agent—an open‑source model from Nous Research—has claimed the top spot on OpenRouter’s global daily...

Reading the raw transcript reveals a troubling pattern: two sections trace back to a single ambiguous sentence, one line was invented outright, and...

Palisade Research has put AI agents through a practical test that reads like a cyber‑war scenario.

Training a family of large language models has always been a cost‑heavy exercise.

Claude Mythos Preview has slipped past the measuring stick that METR, the AI‑risk outfit, has relied on for years.

Why does this matter? As AI systems grow more capable, the gap between what they can do and what humans can verify widens.

Artificial intelligence is reshaping everything, and it’s doing so with a brand‑new vocabulary.

British mathematician Timothy Gowers, a Fields Medalist who holds the Combinatorics Chair at the Collège de France and a fellowship at Trinity...

Why does this matter for anyone crossing into large‑language‑model work? Because the jump from computer‑vision pipelines to LLM engineering isn’t...

Memory isn’t a luxury for an AI agent; it’s a prerequisite for anything beyond a single prompt.

Anthropic just announced a $30 billion revenue run rate – an 80‑fold jump from its baseline.

Voice agents have long been costly to run and tricky to orchestrate. The problem isn’t the models’ ability to converse; it’s the context ceilings...

Employers are slipping “emotion AI” into the daily grind, and the technology is moving faster than the rules can keep up.