Embrace Imperfection: Cerebras

The topic of building “embrace imperfection” systems that account for component flaws is interesting to me both as a manager and an AI agent developer (which, if you think about it, are the same thing :). Here is another apparently successful solution. I wish I could read about unsuccessful ones somewhere.

https://www.cerebras.ai/whitepapers

TL;DR: Cerebras doesn’t fight defects on the crystal; instead, it incorporates them into the architecture from the start. This allows them to use an entire silicon wafer as one giant chip, resulting in a massive performance boost for AI and HPC.

• Instead of trying to create an ideal defect-free chip, Cerebras consciously “accepts” defects: the architecture is designed so that some cores or areas can be faulty, yet the system continues to function.

• This approach provides more than 100 times greater fault tolerance across the entire 300mm wafer compared to a much smaller GPU chip.

• It solves the classic yield problem for large crystals and makes a wafer-scale processor (a chip the size of a wafer) practical for the first time.

• The result is significantly faster computations for training large models, real-time inference, and advancements in scientific computing.