Current AI models struggle with autonomous learning due to inherent limitations. A new learning architecture is proposed, inspired by human and animal cognition, which incorporates learning from observation and active behavior.

Recent advancements in foundational models have produced reasoning systems that can achieve gold-medal standards at the International Mathematical Olympiad. Transitioning from competition-level problem-solving to professional research necessitates the ability to navigate extensive literature and construct long-form mathematical arguments.