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SwiftStack Announces World’s First Multi-Cloud AI/ML Data Management Solution

by Jon Seals | March 12, 2019 | Uncategorized | 0 comments

Autonomous vehicle companies now spanning large-scale Artificial Intelligence/Machine Learning data pipelines from edge-to-core-to-cloud

SAN FRANCISCO – SwiftStack, the leader in multi-cloud data storage and management, today announced a new customer-proven edge-to-core-to-cloud solution that supports large-scale Artificial Intelligence/Machine and Deep Learning (AI/ML/DL) workflows. SwiftStack has recently deployed the new solution stack in two autonomous vehicle use cases.

SwiftStack’s AI/ML solution delivers massive storage parallelism and throughput, needed for ingest, training and inferencing; a scale-out global namespace for access to data whether on-premises or in one or more clouds; data services such as tagging, search, and metadata management to support AI/ML workflows; and Kubernetes and TensorFlow support. Additionally the solution extends to public clouds to take advantage of cloud-bursting and economies of scale, while data is secured on-premises.

“Infrastructure challenges are the primary inhibitor for broader adoption of AI/ML workflows,” said Amita Potnis, Research Director at IDC’s Infrastructure Systems, Platforms and Technologies Group. “SwiftStack’s multi-cloud data management solution is the first of its kind in the industry and effectively handles storage I/O challenges faced by edge-to-core-to-cloud, large-scale AI/ML data pipelines.”

The solution includes an integration of SwiftStack with Valohai’s deep learning platform-as-a-service to provide machine orchestration, version control, and AI/ML pipeline management.

“With this integration users can quickly adopt an AI/ML platform, easily use multi-cloud workflows and frameworks, and scale to petabytes of storage and hundreds of gigabytes of bandwidth,” said Eero Laaksonen, CEO of Valohai. “This gives them the ability to create a deep learning infrastructure, even at an enormous scale, in a fraction of the time.”

https://www.swiftstack.com/solutions/ai-ml

About SwiftStack

SwiftStack, founded in 2011 by some of the earliest pioneers in cloud computing, is a leading cloud storage provider for organizations that require universal access to petabytes of unstructured data in a single namespace. Its software is popular in industries like media and entertainment, global service providers, life sciences, and web-based business; and for functions like AI/ML, analytics, scientific research, active archive, and managing data across multiple clouds. SwiftStack is utilized by industry leaders including eBay, Pac-12 Networks, Verizon, and the HudsonAlpha Institute for Biotechnology. The company is headquartered in San Francisco and received B-series funding from OpenView Partners, Storm Ventures, UMC Capital, and Mayfield Fund. For more information visit www.swiftstack.com or follow the company on Twitter and LinkedIn.

Valohai is a Deep Learning Management Platform that automates machine orchestration, version control and pipeline coordination for data science teams. Scale models to hundreds of CPUs or GPUs at the click of a button. Create an audit trail and reproduce any previous run with built-in version control for input data, hyperparameters, training algorithms and environments. Manage the entire ML pipeline with automatic coordination from feature extraction and training to inference. Valohai was founded in 2016 by a team of engineers with backgrounds in various software development companies and has offices in Turku, Helsinki and San Francisco, US. Read more on Valohai website www.valohai.com

About GPL Technologies. Founded in Los Angeles, California in 2003, GPL draws on over a decade of expertise as trusted technology advisers, adding value for our customers by offering personalized methods of improving IT efficiency, streamlining complex systems and environments, and reducing the costs associated with acquiring and maintaining IT systems with innovative managed services and financial solutions. For further information, visit http://www.gpltech.com/

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