Researchers made AI agents better by turning academic papers into working code — no retraining required

ScholarEvolve uses published research to improve AI agents, raising Qwen's AppWorld task completion from 69% to 81.4% without retraining the model.
InfoQ

AWS Introduces Strands Decider 2B and Strands Box for AI Agent Development

AWS has introduced two open-source projects for AI agent development: Strands Decider 2B, a small model designed to make ...

Nobel Prize in Chemistry, Soai Reaction and the Frank Model: Let's take a peek at the mechanism where a 'slight bias' is amplified to 100% using Python! [Sna…

On October 7, 2026, the Royal Swedish Academy of Sciences announced that the 2026 Nobel Prize in Chemistry would be awarded ...
InfoQ

Android Bench 2 Adds Support for Long-Horizon Tasks, Agentic Evaluation, and Continuous Scoring

Google has released Android Bench 2.0, a major update to its benchmark framework for evaluating AI models and agents on Android development tasks. The update introduces long-horizon tasks (LHTs), ...
Ars Technica

Covert uploads and megalomania: OpenAI details new “misaligned” agent incidents

For a while now, the issue of “AI alignment” (i.e., how well an AI model’s actions line up with the intentions of its creator and/or user) has been a core concern and topic of discussion among AI ...