英伟达市值一个月内蒸发5万亿元

Core Viewpoint - The AI chip market is experiencing significant shifts, with Google accelerating the commercialization of its self-developed AI chip, TPU, which may disrupt NVIDIA's dominance in the GPU market [2][6][10] Group 1: Google's Strategy - Google is pushing its TPU chip towards external clients, with Meta considering deploying TPU in its data centers as early as 2027, potentially involving contracts worth billions [6] - The move aligns with Google's long-term strategy of "soft and hard integration" and aims to reduce costs associated with large model training [6] - Google's latest TPU versions, including TPU v7 and Gemini 3, are designed to enhance its technological capabilities in the era of large models [6] Group 2: NVIDIA's Response - NVIDIA has responded to the competitive threat by emphasizing its leadership in the GPU market and the unique advantages of its products, claiming to be the only platform capable of running all AI models [4][7] - Despite the rise of TPU, NVIDIA maintains that its GPUs remain irreplaceable due to their versatility and compatibility across various AI applications [7] - NVIDIA's stock has been volatile in response to Google's advancements, indicating market concerns about its future share and profitability in AI infrastructure [10] Group 3: Industry Trends - The trend of major tech companies developing their own AI chips is growing, with AWS and Microsoft also advancing their proprietary chip technologies [9] - The industry is shifting from a GPU-centric model to a heterogeneous architecture involving multiple suppliers, as companies seek to diversify their computing resources [9] - The collaboration between companies like Anthropic with both NVIDIA and Google highlights a preference for a multi-route procurement strategy, indicating a move away from reliance on a single chip architecture [9]