在每日经济新闻App举办的掘金大赛中，第81期比赛将于1月5日开始，多位选手报名，准备开始冲锋。对于年初的行情，参赛高手怎么看呢？今日， 他们对此做了一些分享。 大赛为模拟炒股，模拟资金50万元。报名时间为2026年1月1日到1月16日，比赛时间为2026年1月5日到1月16日。每期比赛结束，正收益就获现金奖 励！报名就拿福利！冲刺月度积分王大奖！ 每经记者｜吴永久 每经编辑｜闫峰峰 元旦节期间，中国资产大爆发，在周五，恒生指数涨2.76%，恒生科技指数涨4%，纳斯达克中国金龙指数大涨4.38%。2026年A股能否迎来"开门 红"？高手看好哪些主线？ 每期比赛的税前现金奖励为：第1名奖励688元，第2~4名奖励188元/人，第5~10名奖励88元/人，其余正收益选手均分500元正收益奖。月度积分王的 税前现金奖励为：第1名奖励888元，第2~4名奖励288元/人，第5~10名奖励188元/人，第11~30名奖励68元/人，第31~100名奖励18元/人。 目前，大盘震荡蓄势，为便于参赛选手提高交易胜率，只要成功报名掘金大赛，就能获得每日经济新闻App私人订制的"火线快评"6个交易日的免费 阅读权限。此外，每期 ...

Core Insights - The primary value of Google's TPU lies not only in its speed but also in its profit margins, allowing the company to bypass the "Nvidia tax" and significantly reduce computing costs [1][17][18] - Google's TPU v7 is positioned as a formidable competitor in the AI chip market, showcasing substantial advancements in performance and efficiency compared to Nvidia's offerings [5][14][20] Background and Development - The inception of TPU was driven by a critical need for enhanced computational capacity to support Google's services, leading to the decision to develop a custom ASIC chip tailored for TensorFlow [6][7][8] - The rapid development cycle of TPU, from concept to deployment in just 15 months, highlights Google's commitment to innovation in AI technology [8] Architectural Advantages - TPU's architecture is designed for efficiency, utilizing a "Systolic Array" that minimizes data movement and overcomes the "von Neumann bottleneck," resulting in superior energy efficiency compared to traditional GPUs [10][11][12] - The TPU v7 demonstrates a significant leap in performance metrics, achieving a BF16 computing power of 4,614 TFLOPS, a tenfold increase from its predecessor [15] Competitive Landscape - The TPU v7's specifications, including a single-chip HBM capacity of 192GB and a memory bandwidth of 7,370 GB/s, position it competitively against Nvidia's Blackwell series [16] - Google's strategic control over TPU design allows it to escape the high costs associated with Nvidia's GPUs, restoring higher profit margins for cloud services [17][18] Market Implications - As AI workloads shift from training to inference, the importance of Nvidia's CUDA may diminish, potentially benefiting Google's TPU ecosystem [19] - Analysts suggest that Google's dominance in large-scale computing and the performance of TPU v7 could redefine the competitive dynamics in the AI chip market, positioning Google as a key player capable of controlling its own destiny [20]