Core Viewpoint - The investment focus in the AI sector should shift from infrastructure to application layers, as large language models (LLMs) are rapidly commoditizing and are not the ultimate value creators [1][3][4]. Group 1: Current Market Dynamics - LLMs are being compared to the early stages of broadband network construction, where the models are essentially being "given away for free" [4]. - Major LLM developers, such as OpenAI, are in fierce competition to surpass each other on similar functionalities, akin to "creating 10 Googles" simultaneously [5]. - The real profits in the value chain will flow to application developers who can effectively utilize these tools to create actual business value [5]. Group 2: Investment Strategy - The company prefers to invest in those who leverage AI capabilities to create significant efficiency improvements and business model transformations within specific industries, rather than in the developers of the search engines themselves [6]. - There is a cautious stance towards the current market's enthusiasm for AI infrastructure, with comparisons made between Nvidia's $5 trillion valuation and Cisco's valuation during the 1999 tech boom, suggesting it reflects past achievements rather than future potential [6]. Group 3: Future Predictions - The company predicts that the U.S. will invest $500 billion in data centers over the next few years to meet "crazy" demand, but views this investment as a "small boom" with capital and attention having already "overstepped" [7].