Core Insights - The article discusses the evolution of AI from a "scaling law" approach to an "era of experience," emphasizing the need for AI to learn from real user interactions rather than just relying on large datasets [1][5][6] - Macaron AI, founded by Chen Kaijie, aims to create a "Personal Agent" that understands users' needs and emotions, moving beyond traditional chatbots [1][2] Group 1: Transition from Scaling Law to Experience Era - The AI industry is shifting from relying solely on increasing parameters and data to focusing on learning from real user experiences [1][6] - The "Chinchilla Law" indicates that as model parameters increase, the required data also increases, but the available data is limited, leading to a bottleneck in model intelligence [4][6] - The future competitiveness of intelligent systems will depend on their ability to learn continuously from real experiences rather than just pre-trained data [6][7] Group 2: Reinforcement Learning and Real Feedback - Reinforcement learning (RL) is central to this new approach, where real interactions provide high-quality data that includes causal relationships [2][7] - The success of AI code assistant Cursor illustrates how analyzing user feedback on code suggestions can enhance model performance [2][8] - A robust "Reward Model" evaluates user satisfaction and guides the AI in improving its responses, making the learning process more effective [9][10] Group 3: Macaron AI's Unique Features - Macaron AI has created over 100,000 personalized "mini-apps" for various life scenarios, focusing on being a private and dedicated assistant [3][11] - The memory system of Macaron AI is integrated into the model, allowing it to learn and adapt based on user feedback rather than relying on traditional keyword searches [2][11] - The use of Ant Group's open-source Text Diffusion technology enhances the model's ability to generate and modify content quickly, contributing to a better user experience [12] Group 4: Future of Personal Agents - The vision for personal agents includes the ability to manage various aspects of daily life, such as scheduling, travel, and shopping, potentially replacing many existing applications [16] - The integration of small applications and memory functions is seen as a long-term goal, aiming for a seamless user experience [15]