The post discusses the advancements and economic implications of DeepSeek's R1-Zero and R1 AI systems, emphasizing the removal of human bottlenecks in AI training and the potential for generating high-quality data through reasoning systems. The conversation reflects skepticism about the novelty and quality of generated data, particularly outside of math and code domains. It addresses the dual focus on inference and computation costs, predicting a shift towards more inference-centric AI models and custom app development powered by LLMs. Key points include: - The potential for reasoning systems to generate training data. - Economic implications of moving towards inference solutions. - The necessity of human interaction in real-world discoveries still paramount. - Predictions about the future of LLMs in custom software development and app creation.