专访丨讯兔科技创始人李罗丹：金融AI正从“助理时代”向“师徒时代”演进

Core Insights - Financial AI is evolving from an "assistant era" to a "mentor-mentee era," where AI will increasingly embody the implicit knowledge of experienced professionals [1][4][10] - The goal is for AI systems like Alpha to develop capabilities akin to a fund manager's assistant by around 2027, transforming into a new financial infrastructure [1][9][13] Group 1: Evolution of Financial AI - The transition from "assistant" to "mentor" signifies a shift from handling explicit knowledge to understanding implicit knowledge, which is crucial in investment research [4][5] - Implicit knowledge involves the know-how and nuances that are difficult to articulate and typically shared through long-term interactions [5][6] - AI's development will focus on deepening interactions, allowing it to learn and adapt to individual preferences and thought processes [10][11] Group 2: Current Capabilities and Future Directions - Currently, Alpha is at a "mid-level researcher" stage, with aspirations to reach "junior researcher" status by early 2025 and "senior researcher" by 2026 [9][10] - The most significant challenge in evolving to a fund manager's assistant is achieving memory and adaptability to individual fund managers' needs [10][12] - Future interactions will shift from simple Q&A to a more integrated workspace where AI can proactively provide insights and manage tasks [11][12] Group 3: Data Security and Personalization - The uniqueness of each AI "mentee" ensures that the knowledge and data remain private and tailored to individual users, enhancing data security [6][10] - Trust and data compliance are essential for establishing a true mentor-mentee relationship, as personalized data must remain accessible only to the owner [6][10] Group 4: Market Dynamics and Infrastructure - The financial industry is undergoing significant changes, necessitating new infrastructure that can handle the demands of AI and 24/7 trading environments [13][14] - Companies are increasingly viewing AI as integral to their business rather than just a tool, leading to a shift in resource allocation towards AI capabilities [15][16] - The competitive landscape will see a divide between companies focused on interaction and those providing data and capabilities, emphasizing the need for strong partnerships [16][17]