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 the dominance of NVIDIA's GPUs in the computing power market [1][3]. Group 1: Google's TPU Development - Google has been developing TPU since 2013, primarily for internal AI workloads and Google Cloud services, but is now pushing for external commercialization, with potential contracts worth billions [3]. - Meta is considering deploying Google's TPU in its data centers starting in 2027, with the possibility of renting TPU capacity through Google Cloud as early as next year [3]. - Google's TPU strategy aligns with its long-term "soft-hard integration" approach, aiming to reduce energy consumption and control costs amid rising training costs for large models [3]. Group 2: NVIDIA's Market Position - NVIDIA currently holds over 90% of the AI chip market share and emphasizes its "one generation ahead" and "all-scenario advantages" in response to competition from Google's TPU [3][4]. - Despite the potential entry of TPU into large-scale data centers, NVIDIA maintains that GPUs will not be replaced in the short term, as both TPU and NVIDIA GPUs are experiencing growing demand [1][4]. Group 3: Industry Trends - The industry is moving towards a heterogeneous deployment of ASICs and GPUs, rather than a single architecture dominating the market [2][5]. - Major tech companies, including AWS and Microsoft, are also developing their own AI chips, indicating a broader trend of companies seeking to control their computing power [5][6]. - The collaboration between Anthropic and both NVIDIA and Google highlights a shift towards a diversified supply chain for AI computing power, as companies are reluctant to rely solely on one chip architecture [6]. Group 4: Market Reactions - Following news of Google's TPU commercialization, NVIDIA's stock experienced significant fluctuations, reflecting market reassessment of GPU's future share and profitability in AI infrastructure [7]. - The AI infrastructure industry is transitioning from hardware competition to system-level competition, influenced by changes in software frameworks, model systems, and energy efficiency [7].