Core Insights - The article discusses the increasing demand for smaller chips due to the need for more transistors and higher processing power, particularly in the context of large-scale language models [1][2] - It highlights the challenges in semiconductor manufacturing, particularly the limitations in increasing transistor density and the difficulties in wiring connections between transistors [4][6] - The article compares different chip architectures, specifically the WSE-3 and Nvidia H100, emphasizing the trade-offs in performance, memory capacity, and cost-effectiveness [9][10] Group 1: Chip Architecture and Performance - The trend towards using smaller chips is driven by the desire to increase the number of transistors within a limited area, with current limits around 800 square millimeters for manufacturing [2][3] - The WSE-3 chip, while having a larger size and more on-chip memory, faces challenges in storing all necessary weights for large language models, leading to a complex external memory configuration [10][8] - The performance comparison shows that WSE-3 has a memory capacity 880 times greater than H100, but only achieves 20 times the performance, indicating a complex balance between cost and value [10][8] Group 2: Cost and Value Considerations - The article discusses the cost implications of using chiplets versus monolithic designs, noting that chiplets can potentially reduce manufacturing costs while allowing for greater flexibility in product design [15][16] - It emphasizes the importance of evaluating the value derived from using chiplets, as the benefits must outweigh the additional costs associated with their implementation [24][26] - The article also mentions that the value of chiplets can vary significantly between companies, depending on their specific manufacturing processes and technologies [26]