Regulatory bodies have recently embarked on an intensive study of several prominent quantitative private equity firms. The focus of this research spans two critical dimensions: Firstly, it delves into the holistic operation of quantitative strategies amidst the current market dynamics. This encompasses the impact of varying market conditions on profits and drawdowns, the primary drivers of excess returns, the overall performance and adaptive strategies of quantitative firms in 2024, along with the redemption pressures on the liability side. Secondly, the study zeroes in on the utilization of AI models within quantitative strategies, particularly highlighting the challenges posed by the black box nature of AI algorithms, which includes model uninterpretability and uncontrollable risks. It further explores the typical manifestations and mitigation strategies for AI "hallucination" risks in the context of quantitative asset allocation. The ultimate objective of this research is to gain a profound understanding of the operational landscape and risks associated with quantitative private equity, thereby fortifying the foundation for effective industry supervision.