Cerebras

What is Cerebras?

Cerebras Systems is a pioneering AI hardware and cloud company that revolutionizes deep learning compute limits. Its flagship innovation is the Wafer-Scale Engine (WSE), the largest computer chip ever built, which powers the CS-3 system to deliver unprecedented speed and scalability. By integrating massive amounts of memory and compute cores on a single continuous silicon wafer, Cerebras effectively eliminates the communication bottlenecks common in traditional GPU clusters. The company enables researchers and enterprise developers to train massive large language models in a fraction of the time and cost. Furthermore, Cerebras offers cloud API services that deliver ultra-fast AI inference speeds, significantly outperforming conventional hardware setups.

How to use Cerebras?

Users can leverage Cerebras technology either by procuring their physical CS-3 AI supercomputers for on-premise data centers or by utilizing the Cerebras Cloud infrastructure. Developers can sign up for the Cerebras Inference platform to access incredibly fast LLM inference via a standard API, integrating it seamlessly into custom applications. Additionally, AI researchers can access Cerebras's open-source large language models via platforms like Hugging Face to run, fine-tune, or deploy highly optimized models tailored to their specific enterprise use cases.

Cerebras's Core Features

• Wafer-Scale Engine (WSE-3): Features the world's largest AI chip with 4 trillion transistors for immense computational density.

• CS-3 System: Provides a purpose-built AI supercomputer delivering massive cluster-scale performance within a single machine.

• Ultra-Fast Inference API: Offers an easy-to-use cloud API platform for running open-source generative AI models at record speeds.

• Cluster-Scale Linearity: Allows seamless scaling of complex AI workloads across multiple systems without tedious distributed programming.

• Open Source Contributions: Develops and releases highly efficient open-source LLMs like BTLM-3B to the global AI community.

• Unprecedented Memory Bandwidth: Integrates massive on-chip SRAM to completely eliminate the data movement bottlenecks of traditional chips.

• Framework Compatibility: Supports standard machine learning frameworks like PyTorch natively, simplifying software deployment.

Cerebras's Use Cases

• #1

  Training massive Large Language Models (LLMs) with billions or trillions of parameters efficiently.

• #2

  Running real-time, ultra-low latency inference for consumer-facing generative AI applications.

• #3

  Accelerating deep learning research in scientific computing and healthcare diagnostics.

• #4

  Building specialized on-premise AI supercomputers for strict enterprise data security.

• #5

  Integrating high-speed generative AI capabilities into commercial software via direct API access.