Core Insights - The article discusses the launch of Broadcom's new Jericho4 network chip, which addresses the challenges faced by cloud computing companies in optimizing the efficiency of existing small data centers amid the ongoing expansion of AI data center scale [1][2] - The Jericho4 chip enhances data transmission speed and capacity, enabling the interconnection of dispersed small data centers to create large distributed systems that support AI model development and operation [1] Group 1 - Broadcom's Jericho4 chip can connect over one million processors, with data processing capacity improved by approximately four times compared to previous models [1] - The chip plays a critical role in the AI hardware ecosystem, facilitating data routing and switching functions within GPU clusters, which is increasingly important as AI computing power demands grow [1] - The power consumption issue of large GPU clusters has become a technical bottleneck, with individual facilities struggling to support power demands exceeding 300 megawatts, while distributed architectures can alleviate this pressure [1] Group 2 - Companies are migrating data centers to urban areas to reduce data interaction latency, making the integration of multiple small data centers more feasible in space-constrained environments [2] - The Jericho4 chip's significant advantage lies in its cross-regional interconnectivity, supporting transmission distances of over 100 kilometers, unlike the Tomahawk series, which typically covers communication within a single data center [2] - Jericho4 chips have begun shipping to early customers, with full product integration and deployment expected to be completed within nine months, reflecting the industry's trend towards a "distributed + near-user" transformation in data centers during the AI era [2]