Core Insights - Dr. Yang Likun, a prominent figure in the AI field, is leaving Meta to start his own company, marking a significant turning point for both Meta and the AI industry [2] - Yang Likun is known for his groundbreaking work in convolutional neural networks, particularly the LeNet architecture, which revolutionized computer vision [2][4] - Meta is undergoing a strategic shift in its AI approach, facing internal disagreements and challenges in keeping pace with competitors like OpenAI and Google [5][6] Background of Yang Likun - Born on July 8, 1960, in France, Yang Likun developed an early interest in electronics, later earning an electrical engineering diploma in 1983 [3] - He completed his PhD in computer science in 1987, focusing on early forms of neural network training using backpropagation [3][4] - His work at AT&T's Bell Labs led to the development of convolutional neural networks, significantly impacting image processing and recognition [4] Meta's Strategic Changes - Meta is restructuring its AI strategy, investing $14.3 billion in Scale AI and appointing CEO Wang Tao to lead a new department [5] - The restructuring reflects deeper strategic divides within Meta, as Yang Likun has expressed skepticism about large language models, which the company is prioritizing [5][6] - The departure of Yang Likun highlights ongoing challenges within Meta's AI division, including a recent reduction of approximately 600 positions [6] Industry Implications - Yang Likun's new venture will focus on "world models," which aim to understand environments through video and spatial data rather than just text [5] - The AI industry is experiencing intense competition, with differing opinions on the path to achieving artificial general intelligence (AGI) [6]

Market Performance - The Sci-Tech 50 Index decreased by 1.48% over the last five trading days, while the ChiNext Index fell by 3.79%. In contrast, the large-cap value stocks rose by 1.03%, and the large-cap growth stocks declined by 0.67%. The Shanghai 50 Index increased by 1.13%, and the small-cap index represented by the CSI 2000 dropped by 0.15%. The sectors of non-ferrous metals and steel performed well, while media and communication lagged behind [1]. Risk Premium and Valuation Levels - As of October 10, 2025, the risk premium, calculated as the inverse of the static PE of the CSI All Share Index minus the yield of ten-year government bonds, stood at 2.84%. The two-standard-deviation boundary is 4.76%. The valuation levels indicate that the CSI All Share Index's PETTM is at the 80th percentile, with the Shanghai 50 and CSI 300 both at 71%. The ChiNext Index is close to the 50th percentile, while the CSI 500 and CSI 1000 are at 63% and 61%, respectively. The ChiNext Index's valuation is relatively at the historical median level [1]. ETF Fund Flows - In the last five trading days, ETF inflows amounted to 68.6 billion yuan, and the margin trading balance increased by approximately 15.3 billion yuan. The average daily trading volume across the two markets was 233.17 billion yuan [2]. Industry Focus - The latest thematic allocation focuses on semiconductor materials, chips, and information technology. This includes specific indices such as the CSI Semiconductor Industry Index, the Shanghai Stock Exchange Sci-Tech Board Semiconductor Materials Equipment Theme Index, the CSI Semiconductor Materials Equipment Index, the Shanghai Stock Exchange Sci-Tech Board Chip Index, and the Shanghai Stock Exchange Sci-Tech Board New Generation Information Technology Index [2][3]. Long-term Market Sentiment - The report includes observations on the proportion of stocks above the 200-day long-term moving average, indicating market sentiment trends [13]. Financing Balance - The report tracks the financing balance, which is a critical indicator of market liquidity and investor sentiment [16]. Individual Stock Performance - There is a statistical distribution of individual stocks based on their year-to-date performance across different return intervals, providing insights into stock performance trends [18]. Oversold Indices - The report highlights indices that are currently considered oversold, which may present potential investment opportunities [20].

Market Performance - The Sci-Tech 50 Index decreased by 5.42% over the last five trading days, while the ChiNext Index increased by 2.35%. The large-cap value index fell by 1.25%, and the large-cap growth index rose by 1.68%. The SSE 50 Index dropped by 1.15%, and the small-cap index represented by the CSI 2000 fell by 2.41%. The power equipment and comprehensive sectors performed well, while the defense, military, and computer sectors lagged behind [1]. Risk Premium Analysis - The risk premium, calculated as the inverse of the static PE of the CSI All Share Index minus the yield of ten-year government bonds, indicates that the implied returns of equity and bond assets are at historically high levels. This metric reached 4.17% on April 26, 2022, and 4.08% on October 28, 2022, leading to a rapid market rebound. As of January 19, 2024, the indicator was at 4.11%, marking the fifth occurrence since 2016 of exceeding 4%. As of September 5, 2025, the indicator stands at 2.99%, with the two-standard-deviation boundary at 4.76% [1]. Valuation Levels - As of September 5, 2025, the CSI All Share Index's TTM PE is at the 76th percentile. The SSE 50 and CSI 300 are at 71% and 69%, respectively, while the ChiNext Index is close to 47%. The CSI 500 and CSI 1000 are at 59% and 55%, respectively, indicating that the ChiNext Index's valuation is relatively at the historical median level [2]. Long-term Market Trends - The technical analysis of the Deep 100 Index suggests a cyclical pattern of bear markets every three years, followed by bull markets. Historical declines have ranged from 40% to 45%. The current adjustment, which began in the first quarter of 2021, appears to have sufficient time and space for a potential upward cycle [2]. Fund Flow and Trading Activity - In the last five trading days, ETF inflows totaled 29.7 billion yuan, and the margin trading balance increased by approximately 35.8 billion yuan. The average daily trading volume across both markets was 25,676 billion yuan [2]. AI and Neural Network Analysis - A convolutional neural network (CNN) has been utilized to model price and volume data, mapping learned features to industry themes. The latest focus areas include communication and artificial intelligence, covering sub-indices such as communication equipment, AI industry, and 5G [8]. Indexes of Interest - The following indices are highlighted as of September 5, 2025: - CSI All Share Communication Equipment Index - CSI Artificial Intelligence Industry Index - CSI Communication Equipment Theme Index - ChiNext Artificial Intelligence Index - CSI 5G Communication Theme Index [3][9].