Cerebras is a functional institution in semiconductor design that solved the problem of making a chip as large as an entire standard silicon wafer used in chipmaking.
Their chip achieves incredible speeds and low latency due to its size and independence of external networking.
Taken to the a potential extreme, notions of "Physical Foundation Models" -- where models are more-or-less hardcoded into a physical substrate -- could also upend how we think about AI & computing.
@SamoBurja Watch folks like @LoganGWright1, @TianYuWang2020, @peterlmcmahon to see how this space develops
https://arxiv.org/abs/2604.27911
Cerebras is seeking hardware solutions to its chips' limitations. If it succeeds, its chips would perhaps rival Nvidia's.
The company is a case study in how new AI methods are incentivizing a Cambrian explosion in semiconductor shapes and sizes, reversing the industry's logic.
At the same time, the chip's geometry makes it difficult to scale up due to the lack of external networking capacity.
So far the chip's ideal use case is fast, near-instantaneous inference of large language models, though with limitations on context length and model density.
@Travis_Sch @cerebras @GroqInc keeping a close eye on @TensordyneInc as well!
@SamoBurja @bismarckanlys GN! Sweet dreams.