Cerebras' technical achievement is clear.

It turned an entire wafer into a single chip, routed around defects, and placed 44GB of SRAM right next to the compute engines. It is a direct attempt to solve the memory bottleneck that GPUs have faced for years, but through a fundamentally different architecture.

However, there have not been many articles that deeply analyze the practical limits of this structure in real deployment environments.

In this article, I break down the physical ceiling of 44GB SRAM, the bandwidth bottleneck that appears once MemoryX is used, the edge defect and yield challenges of wafer scale manufacturing, and the flexibility limits of a fixed hardware architecture.

This is not simply a summary of IPO materials.

It combines my own technical understanding with perspectives I have heard from people in Silicon Valley, with the goal of helping readers understand Cerebras in a more three dimensional way from both a technology and investment perspective.

At the end, I also share my own investment view.