Whether you want to build a multi-lingual chatbot or predict DNA sequences, our team of AI scientists and engineers will work with you and your data to build state-of-the-art models leveraging the latest AI techniques.
With 900,000 cores and 44 GB of on-chip memory, the CS-3 completely redefines the performance envelope of HPC systems. From Monte Carlo Particle Transport to Seismic Processing, the CS-3 routinely outperforms entire supercomputing installations.
The Cerebras platform has trained a huge assortment of models from multi-lingual LLMs to healthcare chatbots. We help customers train their own foundation models or fine-tune open source models like Llama 2. Best of all, the majority of our work is open source.
“Mayo Clinic selected Cerebras as its first generative AI collaborator for its large-scale, domain-specific AI expertise to accelerate breakthrough insights for the benefit of patients.”
Matthew Callstrom, MD, PhD
Medical Director for Strategy, Chair - Department of Radiology
"The Cerebras CS-2 is a critical component that allows GSK to train language models using biological datasets at a scale and size previously unattainable. These foundational models form the basis of many of our AI systems and play a vital role in the discovery of transformational medicines."
Kim Branson
SVP Global Head of AI and ML, GlaxoSmithKline
"Training which historically took over 2 weeks to run on a large cluster of GPUs was accomplished in just over 2 days — 52hrs to be exact — on a single CS-1. This could allow us to iterate more frequently and get much more accurate answers, orders of magnitude faster."
Nick Brown
Head of AI & Data Science, AstraZeneca
"Working with the Cerebras ML team we were able to train a new state-of-the-art large language model that outperforms models twice its size in a matter of weeks. Their AI expertise is second to none."
OpenTensor
The OpenTensor Foundation
"Cerebras allowed us to reduce the experiment turnaround time on our cancer prediction models by 300x, ultimately enabling us to explore questions that previously would have taken years, in mere months."
Dr. Rick Stevens
Associate Laboratory Director of Computing, Environment and Life Sciences, Argonne National Laboratory