Sou Hu Cai Jing·2025-11-26 07:51Core Viewpoint - The AI chip sector is undergoing significant changes, with a competitive struggle emerging between Google and Nvidia, reshaping the global AI infrastructure landscape and presenting potential investment opportunities. Group 1: Nvidia's Market Response - Nvidia issued a rare "gentle" statement on social media, expressing happiness for Google's achievements in AI and reaffirming its position as the only platform capable of running all AI models across various computing scenarios, following a more than 7% drop in its stock price, resulting in a market cap loss of several billion dollars [2] - The market's concern centers around Google's self-developed TPU chips potentially undermining Nvidia's dominance in AI computing power [2] Group 2: Google's Self-Sufficient AI Ecosystem - A leading brokerage report highlights that Google is building a fully self-sufficient AI ecosystem, from chips (TPU v7p) to models (Gemini 3.0) to applications (search + Waymo), contrasting with OpenAI's heavy reliance on external computing power [5] - This ecosystem is translating into financial returns, with TPU deployments significantly reducing inference costs and stabilizing search market share above 90%, supported by strong advertising cash flow [5] - Alphabet's stock has shown a remarkable return of nearly 82% over the past year, outperforming Nvidia's 27% increase, indicating a market shift [5] Group 3: Competitive Dynamics in AI Chips - Google's TPU has evolved from an internal workload tool to a core component of its AI strategy, with Gemini 3.0 trained entirely on TPU, achieving performance benchmarks comparable to or exceeding GPT-4 [6][7] - Nvidia emphasizes its GPUs as the only universal platform capable of running all AI models, showcasing superior adaptability in various scenarios compared to TPUs, and highlighting significant performance improvements in its new Blackwell architecture [8][9] - Nvidia is also strengthening its ecosystem through substantial investments in companies like Anthropic and a long-term collaboration with OpenAI, alongside launching DGX Cloud to enhance its "GPU as a service" capabilities [10] Group 4: Industry Impact and Future Outlook - The industry is transitioning from a single-dominant player to a dual-leader model, with Google’s TPU gaining market share while Nvidia maintains its core position [12] - In the long term, the performance gap between TPUs and GPUs is narrowing, with cost advantages likely to drive TPU adoption [12] - Google is evolving beyond a search-driven company, leveraging TPU, Gemini, and its cloud ecosystem to build a self-sufficient AI empire, while Nvidia is transitioning from merely selling graphics cards to maintaining its role as the "operating system" of the AI world [12] Group 5: Investment Opportunities in AI Chips - The adjusted AI sector presents significant value, with current valuations of tech giants being much lower than during the 2000 internet bubble, indicating that AI-driven innovation will remain a key market driver in the coming year [13] - Investors may consider focusing on ETFs related to chip technology, cloud computing, and AI applications to capitalize on these trends [14][16]