LEAD: Breaking the No-Recovery Bottleneck in Long-Horizon Reasoning

Long-horizon execution in Large Language Models (LLMs) remains unstable even when high-level strategies are provided. Evaluating on controlled algorithmic puzzles, we demonstrate that while decomposition is essential for stability, extreme decomposition creates a “no-recovery bottleneck”. We show that this bottleneck becomes critical due to highly non-uniform error distribution, where consistent errors on a few “hard” …

ML 21458 1

Introducing Claude Opus 5 on AWS: Anthropic’s most capable Opus model

Today, we announce the availability of Claude Opus 5 on Amazon Bedrock and Claude Platform on AWS. Claude Opus 5 is Anthropic’s most advanced Opus model and the first in the fifth generation. It is a meaningful step forward, providing improvements across the workflows that teams run in production such as agentic coding, knowledge work, …