Core 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]

Investment Rating - The industry investment rating is classified as In-Line [8]. Core Insights - The report addresses the mismatch in AWS Trainium2/2.5 chip shipments attributed to unstable PCB yield rates, with an expectation of approximately 1.1 million chip shipments in 2025 [1][3]. - Supply chain checks estimate total shipments for the Trainium2/2.5 life cycle (2H24 to 1H26) at 1.9 million units, with a focus on production and consumption in 2025 [2][11]. - The report highlights a significant gap between upstream chip production and downstream consumption, suggesting improvements in yield rates may reduce this gap by 2H25 [6][11]. Upstream - Chip Output Perspective - As of late 2024, 0.3 million units of Trainium2 chips were produced, with a projected total of 1.1 million shipments in 2025, primarily packaged by TSMC (70%) and ASE (30%) [3][11]. - An additional 0.5 million Trainium2.5 chips are expected to be produced in 1H26, bringing the total life cycle shipments to 1.9 million units [3]. Midstream - PCB Perspective - Downstream checks indicate potential shipments exceeding 1.8 million units of Trainium chips, averaging around 200K per month since April [4][11]. - Key suppliers for PCB boards include Gold Circuit and King Slide, which provide essential components for Trainium computing trays [4]. Downstream - Server Rack System Perspective - Wiwynn is identified as a key supplier for server rack assembly, with revenue from AWS Trainium2 servers increasing in 1Q25, aligning with the upstream chip production estimates [5][11]. - The report notes that each server rack can accommodate 32 chips, supporting the projected consumption figures [5]. Component Suppliers - Major suppliers for Trainium2 AI ASIC servers include AVC for thermal solutions, Lite-On Tech for power supply, and Samsung for memory components [10][18]. - Other notable suppliers include King Slide for rail kits and Bizlink for interconnect solutions [10][18]. Future Projections - For Trainium3, shipments are estimated at 650K for 2026, with production managed by Alchip [12][13]. - The report anticipates that Trainium4 will enter small production by late 2027, with a rapid ramp-up expected in 2028 [14].