Cerebras Systems and Cirrascale Cloud Services Introduce Cerebras AI Model Studio to Train GPT-Class Models with 8x Faster Time to Accuracy

With Predictable Fixed Pricing, Faster Time to Solution, and Unprecedented Flexibility and Ease of Use, Customers Can Train GPU-Impossible Sequence Lengths and Keep Trained Weights

Cerebras Systems, the pioneer in accelerating artificial intelligence (AI) compute, and Cirrascale Cloud Services, a provider of deep learning infrastructure solutions for autonomous vehicle, NLP, and computer vision workflows,  announced the availability of the Cerebras AI Model Studio. Hosted on the Cerebras Cloud @ Cirrascale, this new offering enables customers to train generative Transformer (GPT)-class models, including GPT-J, GPT-3 and GPT-NeoX, on industry-leading Cerebras Wafer-Scale Clusters, including the newly announced Andromeda AI supercomputer.

AI News: An Investment Into Artificial Intelligence as Daktela Buys Coworkers.ai

“The new Cerebras AI Model Studio expands our partnership with Cirrascale and further democratizes AI by providing customers with access to multi-billion parameter NLP models on our powerful CS-2 clusters, with predictable, competitive model-as-a-service pricing”

Traditional cloud providers struggle with large language models as they are unable to guarantee latency between large numbers of GPUs. Variable latency produces complex and time-consuming challenges in distributing a large AI model amongst GPUs and large swings in time to train. The Cerebras AI Model Studio overcomes these challenges. Set up is quick and easy; clusters of dedicated CS-2s guarantee deterministic latency; and because the clusters rely solely on data parallelization, there is zero distributed compute work required.

Training Large Language Models (LLMs) is challenging and expensive — multi-billion parameter models require months to train on clusters of GPUs and a team of engineers experienced in distributed programming and hybrid data-model parallelism. It is a multi-million dollar investment that many organizations simply cannot afford.

The Cerebras AI Model Studio offers users the ability to train GPT-class models at half the cost of traditional cloud providers and requires only a few lines of code to get going. Users can choose from state-of-the-art GPT-class models, ranging from 1.3 billion parameters up to 175 billion parameters, and complete training with 8x faster time to accuracy than on an A100.

Latest AI/NLP Technology Insights: ProcessUnity Acquires AI/NLP Technology from ISMS Solutions

“The new Cerebras AI Model Studio expands our partnership with Cirrascale and further democratizes AI by providing customers with access to multi-billion parameter NLP models on our powerful CS-2 clusters, with predictable, competitive model-as-a-service pricing,” said Andrew Feldman, CEO and co-founder of Cerebras Systems. “Our mission at Cerebras is to broaden access to deep learning and rapidly accelerate the performance of AI workloads. The Cerebras AI Model Studio makes this easy and dead simple – just load your dataset and run a script.”

The Cerebras AI Model Studio offers users cloud access to the Cerebras Wafer-Scale Cluster, which enables GPU-impossible work with first-of-its-kind near-perfect linear scale performance. Users can access up to a 16-node Cerebras Wafer-Scale Cluster and train models using longer sequence lengths of up to 50,000 tokens – a capability only available to Cerebras users – opening up new opportunities for exciting research.

“We are really excited to offer our enterprise, research and academic customers easy, affordable access to the leading CS-2 accelerator to train GPT-class models in less than one day,” said PJ Go, CEO, Cirrascale Cloud Services. “We’ve made the process extremely simple – eliminating the need for dev-ops and distributed programming – with push-button model scaling, from 1 to 20 billion parameters.”

With every component optimized for AI work, the Cerebras Cloud @ Cirrascale delivers more compute performance at less space and less power than any other solution. Depending on workload, from AI to HPC, it delivers hundreds or thousands of times more performance than legacy alternatives, but uses only a fraction of the space and power. Cerebras Cloud is designed to enable fast, flexible training and low-latency datacenter inference, thanks to greater compute density, faster memory, and higher bandwidth interconnect than any other datacenter AI solution.

Latest Aithority Insights : Got It AI Announces AutoFlows, a Breakthrough Autonomous Conversational AI

 [To share your insights with us, please write to sghosh@martechseries.com]