As artificial intelligence reaches new milestones in reasoning and video understanding, researchers are pushing the boundaries of what machines can comprehend - from solving complex math problems to understanding the physics of everyday situations. These developments signal a shift from AI that simply processes information to systems that can truly reason about the world, though the struggle with Olympic-level math problems reveals there's still a distinctly human edge in complex problem-solving. Links to all the papers we discussed: Video-R1: Reinforcing Video Reasoning in MLLMs, UI-R1: Enhancing Action Prediction of GUI Agents by Reinforcement Learning, Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Models, VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness, Large Language Model Agent: A Survey on Methodology, Applications and Challenges, LeX-Art: Rethinking Text Generation via Scalable High-Quality Data Synthesis