OpenAI会走向Google的商业化之路吗？

Core Viewpoint - The article discusses the commercialization path of OpenAI's LLMs (Large Language Models) and compares it to Google's advertising model, exploring potential monetization strategies and challenges in the AI landscape [4][5]. Group 1: Commercialization Strategies - OpenAI's potential monetization strategy may resemble Google's CPA (Cost per Action) model, which currently accounts for only 10% of Google's ad revenue, as opposed to the more dominant CPC (Cost per Click) model [6][8]. - The article suggests that OpenAI could leverage its large user base of nearly 900 million free users by implementing a take rate model, where it earns a commission from merchants after assisting users with transactions [5][6]. Group 2: Challenges in Monetization - The transition to a CPA model may face challenges due to the complexity of user transactions in sectors like travel and finance, where multiple interactions are often required before a purchase is made [7][8]. - The article highlights that the high token consumption associated with LLMs could lead to increased operational costs for OpenAI, especially if the conversion rate for high-value queries is low [8][9]. Group 3: Comparison with Google - Google's success is attributed to its ability to create a win-win situation for users, content creators, and the platform, primarily through its CPC model, which allows for extensive scalability and granularity in ad placements [9][10]. - The article posits that OpenAI's current product form may be limited in its commercialization potential compared to Google due to issues related to conversion rates and the granularity of monetization [8][9]. Group 4: Future AI Monetization Models - The article proposes two potential AI-native monetization models: one that utilizes the asynchronous nature of agents to price tasks based on their time value, and another that encourages advertisers to enrich their product context to improve the quality of AI-generated responses [11][12]. - A token auction mechanism is suggested, where advertisers would bid on the influence their content has on LLM outputs, shifting the payment model from clicks to content contribution [13]. Group 5: Market Performance - The article provides a performance overview of AGIX and major indices, indicating AGIX's year-to-date return of 16.11% and a return of 55.02% since 2024, showcasing its defensive advantage in a challenging market environment [15][20]. - It also notes a structural adjustment in hedge fund industry allocations, with a shift away from tech sectors, particularly AI-related themes, towards more defensive sectors like healthcare and consumer staples [18][19].