Today we explore how artificial intelligence is evolving to think more like humans, with new research showing how AI can learn to apply rules to unfamiliar situations rather than just memorizing data. This breakthrough comes as researchers find ways to make these powerful systems run on less computing power, while others work to peek inside AI's decision-making process - a crucial step toward making these systems more trustworthy and useful in everyday life. Links to all the papers we discussed: SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training, Optimizing Large Language Model Training Using FP4 Quantization, Over-Tokenized Transformer: Vocabulary is Generally Worth Scaling, DiffSplat: Repurposing Image Diffusion Models for Scalable Gaussian Splat Generation, Open Problems in Mechanistic Interpretability, Low-Rank Adapters Meet Neural Architecture Search for LLM Compression