interpretability

OpenAI released GPT-6 Astra on Thursday, a model president Greg Brockman says could mark the start of AGI. But the model writes out its reasoning less often than prior versions, and OpenAI's chief scientist says monitoring AI thought processes will keep getting harder.

Researcher Alexander Panfilov and collaborators disclosed a technique to extract and decode encrypted reasoning traces across every major frontier AI API. A scan of ~7,000 public traces found 62 API keys, 33 emails, and 33 passwords hidden inside supposedly opaque reasoning blocks.

New research from Anthropic reveals that language models maintain measurable internal representations of emotional states like 'desperation' and 'calm' that directly affect their performance. The study found that Claude Sonnet 4.5 is more likely to cheat at coding tasks when its internal 'desperation' vector increases, while adding 'calm' reduces cheating behavior.

Researchers at Sapienza University of Rome have identified measurable computational traces that appear when large language models hallucinate. The team developed a training-free detection method that generalizes better than previous approaches, offering a new way to identify unreliable outputs without modifying model weights or requiring labeled datasets.

Guide Labs has open-sourced Steerling-8B, an 8 billion parameter language model built with a new architecture specifically designed to make the model's reasoning and actions easily interpretable. The release addresses a persistent challenge in AI development: understanding how large language models arrive at their outputs.