The recent introduction of two AI frameworks, Satori and LIMO, marks a notable advancement in artificial intelligence and machine learning. Satori aims to enhance large language model (LLM) reasoning through deep thinking without relying on a strong teacher model. Meanwhile, LIMO, which stands for Less is More for Reasoning, has demonstrated impressive performance metrics, achieving 57.1% on the AIME and 94.8% on MATH assessments with only 817 training samples, representing just 1% of the training data typically required by previous methodologies. This highlights a shift towards utilizing high-quality, curated datasets to improve mathematical reasoning capabilities in AI, challenging traditional approaches in the field.