Today's stories explore how artificial intelligence is becoming more human-like in its ability to reason, diagnose, and move. From language models that can expand their knowledge through reflection to medical AI that simulates doctor-patient conversations, and robots learning precise movements, we see technology increasingly mimicking human cognitive and physical capabilities - raising both exciting possibilities and important questions about the future of human-machine interaction. Links to all the papers we discussed: Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps, OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking, Learnings from Scaling Visual Tokenizers for Reconstruction and Generation, Exploring the Inquiry-Diagnosis Relationship with Advanced Patient Simulators, SynthLight: Portrait Relighting with Diffusion Model by Learning to Re-render Synthetic Faces, FAST: Efficient Action Tokenization for Vision-Language-Action Models