WEKA & Stability AI aim to maximise cloud benefits for AI
WEKA and Stability AI recently announced a partnership to pioneer a new AI solution that aims to train multiple AI models in the cloud.
WEKA’s Data Platform Converged Mode for Cloud solution is aiming to enhance Stability AI’s ability to train multiple AI models, including its popular Stable Diffusion model, and extend efficiency, cost and sustainability benefits to its customers. Both companies are aiming to maximise cloud benefits for AI model training.
Both companies have consistently considered AI within the context of businesses and data and this partnership only seeks to strengthen the AI adoption of their customers.
Supporting AI models and improving use cases
WEKA in particular has shed plenty of light on infrastructure challenges that impact AI adoption, having revealed in a survey that 32% of respondents cited data management as a technological inhibitor to AI and machine learning deployments.
WEKA has been working to develop a unique way to dramatically improve things for its cloud-first generative AI customers. The WEKA Data Platform’s Converged Mode solution is the first scale-out storage on deep learning capable instances available to users running workloads in the cloud. It uses ephemeral local storage and memory in cloud AI instances to reduce costs and create performance improvements for large-scale generative AI resources compared to traditional data architectures.
Stability AI seeks to use existing cloud resources more efficiently. The company began working with WEKA to develop a ‘converged cloud’ approach with the WEKA data platform and recently concluded a successful trial of the solution. It works to provide a single, high-performing set of resources to support the application and data platform simultaneously.
As a result, there is more optimal training of Stability AI’s models and better utility for its research teams.
“Simple and affordable to run AI model training and inference in the public cloud”
“As the only independent, open, and multimodal generative AI company, we understand the limitations of running converged workloads on-premises,” said Tom Mason, CTO at Stability AI.
“WEKA gives our customers more options by enabling training on converged mode in the public cloud. Our hope is that this partnership will increase our hardware utilisation and scale to thousands of instances and essentially, do more with less, more sustainably.”
Once deployed, Stability AI is aiming to be able to extend the benefit of performance gains and significant cloud cost-savings from WEKA’s data platform. The company is working to do this whilst simultaneously lowering carbon emissions and energy consumption. The company expects to use the WEKA solution to underpin its forthcoming sustainability initiatives as its deployment matures and grows.
“The WEKA Data Platform can increase GPU-stack storage efficiency by 10-50x, driving a significant cost advantage for generative AI companies by helping to maximise resources they’ve already paid for,” said WEKA co-founder and CEO Liran Zvibel.
“At the same time, WEKA makes it simple and affordable to run AI model training and inference in the public cloud, helping to shrink their data infrastructure and energy and carbon footprint, delivering a double-bottom line benefit for customers that want to harness the power of AI without compromising their corporate sustainability goals.”
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