VAST’s scalable, secure central data foundation is already powering one of the world’s largest AI clouds, a multi-hundred petabyte AI lake at Core42

Cerebras Systems, the pioneer in accelerating generative AI, today announced that it has selected VAST Data, the AI data platform company, to help deliver advanced data solutions that will accelerate the training and accuracy of generative AI workloads. By leveraging the scalable and secure multi-tenant VAST Data Platform, Cerebras scales capacity and performance of its leading CS-2 AI supercomputers, including the recently announced Condor Galaxy, the world’s largest AI supercomputer network built in partnership with G42 Cloud, now part of Core42.

“The data requirements for training generative AI workloads continues to increase at an exponential and unprecedented pace,” said Andrew Feldman, CEO and co-founder of Cerebras Systems. “The VAST Data team have industry-leading expertise in managing exabytes of data from edge to cloud, and helping evolve that data into information. With VAST’s enhanced data capabilities, we enable optimal utilization of Condor Galaxy, built in strategic partnership with G42, and our other AI supercomputers. This will allow users to build and train the next wave of cutting-edge foundational models, while greatly reducing training times and accelerating time-to-insight.”

Training large models requires massive amounts of AI compute, huge datasets, and specialized AI expertise. Cerebras and Core42 recently introduced Condor Galaxy, a network of nine interconnected AI supercomputers that will provide 36 exaFLOPs of AI compute, which delivers on all three elements and was used to train Jais, the world’s highest quality Arabic Large Language Model. By collaborating with VAST Data, the Condor Galaxy supercomputing network furthers its leadership in the high-performance storage and enhanced data management of vast and diverse datasets. The VAST Data Platform provides scalable, secure, and efficient access to the massive amount of data required for training workloads conducted on Condor Galaxy.

“Our strategic partnerships with Cerebras and VAST Data deliver on our mission to deploy AI-optimized cloud infrastructure that addresses the most pressing needs of global organizations and uses data-intensive AI computing to solve real-world challenges,” said Talal Alkaissi, EVP & Chief Product and Global Partnerships Officer of Core42, a G42 company. “We are thrilled to be delivering meaningful results, including the newly announced clinical LLM, Med42, a leading 70 billion parameter open-access model launched by M42 and trained on Condor Galaxy 1, with its curated medical dataset stored and secured by VAST.”

“As AI model training continues to grow and expand, so too does the need for more memory in each GPU, and Cerebras is delivering a new approach to solve this problem,” said Jeff Denworth, co-founder at VAST Data. “Through our joint collaboration with Core42, the VAST Data Platform is helping organizations reimagine the future of data-intensive AI training and inference with infrastructure that was designed for these high-performance demanding workloads, and the simplicity and zero trust, multi-layer security that modern enterprises require. Together, we’re excited to provide the data foundation for a global network of next-generation AI supercomputers.”

For more information, please visit https://www.cerebras.net/condor-galaxy-1.

About Cerebras Systems

Cerebras Systems is a team of pioneering computer architects, computer scientists, deep learning researchers, and engineers of all types. We have come together to build a new class of computer system, designed for the singular purpose of accelerating generative AI work. Our flagship product, the CS-2 system, powered by the world’s largest and fastest AI processor, makes training large models simple and easy, by avoiding the complexity of distributed computing. Cerebras solutions are available in the cloud, through the Cerebras AI Model Studio or on premises. For further information, visit https://www.cerebras.net.

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