Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025)

NeurIPS 2025 papers challenge AI assumptions. Key takeaways: LLMs converge, attention needs improvement, RL scales with depth, diffusion models generalize, and RL enhances reasoning performance, not capacity. AI progress is now systems-limited, not model-size limited.