Today's tech landscape reveals growing tensions between AI advancement and safety, as researchers grapple with security vulnerabilities in retrieval systems and potential biases in AI evaluation methods. Meanwhile, a breakthrough in human animation technology offers a glimpse of more natural human-AI interaction, though questions remain about maintaining trust and safety as these systems become more sophisticated. Links to all the papers we discussed: The Differences Between Direct Alignment Algorithms are a Blur, OmniHuman-1: Rethinking the Scaling-Up of One-Stage Conditioned Human Animation Models, Process Reinforcement through Implicit Rewards, SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model, AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Understanding, Preference Leakage: A Contamination Problem in LLM-as-a-judge