应用很散 一揽子？

Core Viewpoint - The global AI landscape is shifting from training to inference, with software applications beginning to emerge prominently. The number of notable models released in 2024 has decreased compared to 2023, indicating a potential slowdown in model development despite increasing model parameters and performance improvements driven by new technologies [1][2]. Group 1: Model Development and Performance - The number of notable AI models released in 2024 is 40, down 34.43% from 61 in 2023, with OpenAI, Google, and Alibaba leading in contributions [1]. - The performance of AI models is expected to improve significantly with increased reasoning time, as evidenced by a study showing a 6%-11% accuracy improvement in medical diagnosis with extended reasoning time [1]. - The use of tokens has surged, with Google processing tokens increasing 50 times monthly and Microsoft Azure AI Foundry increasing by 5 times [2][3]. Group 2: Revenue and Market Trends - Revenue from foundational AI models is growing rapidly, with OpenAI generating $3.7 billion, Anthropic $2 billion, and Perplexity $120 million [3]. - The adoption rate of AI tools among developers has risen from 44% to 63% between 2023 and 2024, indicating a growing reliance on AI technologies [2][3]. - The U.S. market is seeing significant growth in various AI applications across sectors such as military, education, and healthcare, while the domestic market is still in the product development phase [3]. Group 3: Investment Insights - The performance of AI-related ETFs has shown volatility, with the chip ETF down 15% from its peak, but there is potential for recovery as AI applications expand [5]. - The data ETF has also experienced a decline of around 20% from its high, suggesting a market correction and potential for future growth as demand for AI solutions increases [9]. - The current allocation of public funds in technology sectors is relatively low, indicating potential for growth as the market stabilizes [4].