梁文锋旗下幻方量化去年收益率56.6%，位列百亿级量化基金业绩榜第二

Group 1: Company Performance - The average return of Huansheng Quantitative for 2025 is projected to be 56.55%, ranking second among quantitative private equity firms in China with over 10 billion yuan in management scale, only behind Lingjun Investment at 73.51% [1][4] - Huansheng Quantitative has a management scale exceeding 70 billion yuan, with an average return of 85.15% over the past three years and 114.35% over the past five years [1][4] - The strong performance of Huansheng Quantitative has provided substantial research and development funding for DeepSeek, a company under the leadership of Liang Wenfeng [1][4] Group 2: Company Background and AI Development - Huansheng Quantitative, founded by Liang Wenfeng in 2008 while studying at Zhejiang University, is one of the most well-known quantitative private equity giants in China, with a focus on mathematics, computation, research, and AI [1][4] - The company broke the 10 billion yuan management scale in 2019 and surpassed 100 billion yuan in 2021 [1][4] - Huansheng Quantitative has been investing in AI since 2016, with its first stock position generated by deep learning algorithms going live in October 2016, and by the end of 2017, nearly all quantitative strategies were using AI models [1][4] Group 3: DeepSeek and AI Innovations - In April 2023, Huansheng Quantitative announced the establishment of an independent research organization, DeepSeek, to explore the essence of AGI, focusing on serving the common interests of humanity through AI technology [2][5] - DeepSeek's R1 model, released in January 2025, gained significant media attention and is noted for its industry-leading capabilities and cost advantages, with training costs an order of magnitude lower than competitors [2][6] - DeepSeek is set to release its next flagship AI model, DeepSeek V4, in February, which is expected to have strong programming capabilities and significantly impact the current AI competitive landscape [2][6] Group 4: Research Contributions - On January 12, DeepSeek published a new paper titled "Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models," co-authored with Peking University, featuring Liang Wenfeng as a co-author [3][6] - DeepSeek also open-sourced a related memory module named Engram on the same day [3][6]