Cerebras Systems builds wafer-scale AI chips and supercomputers designed to accelerate machine learning training and inference at scale. Founded in 2015, the company manufactures what it claims is the world's largest AI chip - 56 times larger than GPUs - that delivers the compute power of dozens of GPUs on a single device with simplified programming interfaces. The architecture eliminates the operational complexity of managing hundreds of distributed GPUs, a significant engineering burden for organizations running large-scale ML workloads.
The company's technical stack spans system architecture through application deployment: C++, Python, and Go for core development; MLIR and LLVM IR for compiler infrastructure; CSL (Cerebral Systems Language) for wafer-scale programming; and Zig for systems work. Infrastructure runs on Kubernetes and AWS, with CI/CD through GitHub Actions and Jenkins. The engineering team includes computer architects, deep learning researchers, and systems engineers working across hardware design, compiler optimization, and distributed systems.
Cerebras serves global corporations, national laboratories, and healthcare systems requiring high-throughput AI computation. Recent partnerships include OpenAI for inference deployment at scale. The company's approach targets the intersection of hardware innovation and operational simplification - reducing infrastructure complexity while pushing performance boundaries in deep learning research and production deployments.