Nvidia(US:NVDA) 是说芯语·2026-01-15 23:37Core Insights - Etched, an AI chip company founded by Harvard dropouts, has raised nearly $500 million in a new funding round, achieving a valuation of $5 billion and total funding close to $1 billion [1][12] - The company aims to optimize the cost-performance ratio of AI computing, specifically focusing on running Transformer models more efficiently rather than competing directly with Nvidia's general-purpose GPUs [1][4] Market Context - Nvidia dominates the GPU market, with projected data center sales exceeding $500 billion by the end of 2026 [3] - Etched's analysis indicates that computational density has only improved by about 15% over the past few years, highlighting a need for more efficient solutions [3] Product Overview - Etched has developed a custom chip named Sohu, designed specifically for Transformer architecture, claiming it to be the "fastest AI chip ever" [3][10] - Under specific testing conditions, Sohu can process over 500,000 tokens per second when running the Llama 70B model, outperforming Nvidia's Blackwell GB200 GPU by an order of magnitude [3][4] Competitive Advantage - A server composed of eight Sohu chips can replace 160 H100 GPUs, offering a more economical, efficient, and environmentally friendly option for enterprises requiring specialized chips [5] - Sohu's design focuses on reducing energy consumption while achieving higher efficiency in running Transformer models, distinguishing it from general-purpose GPUs [5][10] Financial Implications - The cost of training AI models exceeds $1 billion, with inference applications potentially surpassing $10 billion; even a 1% performance improvement can justify a custom chip project costing between $50 million to $100 million [5][7] Future Prospects - Etched's chip is manufactured using TSMC's 4nm process and is integrated with HBM memory and server hardware to support production capabilities [10] - The company has plans to expand its technology beyond text generation to include image and video generation, as well as protein folding simulations [16] Industry Landscape - Other companies, such as Meta and Amazon, are also developing specialized AI chips, but Etched's approach focuses solely on Transformer models, avoiding unnecessary hardware components and software overhead [10][17] - The success of Etched hinges on the continued relevance of Transformer models in the AI landscape; a shift away from this architecture could necessitate a reevaluation of their strategy [18]