Group 1 - The core theme of the event is how big data analysis drives AI optimization and innovation, emphasizing the importance of interpreting complexity rather than just the quantity of data [2] - Z generation possesses a unique ability to extract valuable signals from noise in a data-saturated environment, which is crucial for both humans and AI systems [3] - Retaining "dirty data" can sometimes be more valuable than overly cleaned data, especially in fields like fraud detection where atypical behaviors are key indicators [3] Group 2 - Cross-domain data fusion is essential for AI optimization, allowing for a more comprehensive understanding of market dynamics beyond traditional financial metrics [4] - The shift from "big data samples" to "small data samples" highlights the importance of "meta-learning," enabling AI to adapt quickly with fewer data points [4][5] - This transition offers advantages such as enhanced privacy protection and improved response speed, allowing AI to remain efficient in rapidly changing environments [6]