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Thinking Machines AI shares its mission to build AI that extends human will and judgment, emphasizing local knowledge, customization, and distributed AI. They outline technical directions including strong multimodal models, tools for customization, interfaces, and research.
PaperMentor is a human-centered multi-agent writing assistant that integrates an expert skill library with specialized agents to provide actionable inline comments on Overleaf, outperforming GPT-5.2 in usability and relevance for AI research papers.
The BEAMS Initiative presents a benchmark suite for evaluating AI tools in modeling and simulation, focusing on human-centered and responsible AI practices. Tests reveal variability across LLM-based engines, with better performance in qualitative tasks than causal reasoning.
The author reflects on their decade-long journey as an Android developer, emphasizing the value of human connections over the pressure to adopt AI, and argues for prioritizing personal growth and community.
This paper proposes Human-Centered Learning Mechanics (HCLM), a dynamical and information-theoretic framework for studying open and controlled learning systems. It formalizes entropy regularization through effective information force, derives convergence and generalization results, and provides a conditional interpretation of scaling-law behavior.