WekaIO Introduces Weka AI

Today WekaIO introduced its new storage solution framework that it states enables accelerated edge-to-core-to-cloud data pipelines, Weka AI. This new framework is underpinned by the Weka File System (WekaFS) and is composed of RAs and SDKs with partners such as NVIDIA, Mellanox, and others in the Weka Innovation Network (WIN).

Today WekaIO introduced its new storage solution framework that it states enables accelerated edge-to-core-to-cloud data pipelines, Weka AI. This new framework is underpinned by the Weka File System (WekaFS) and is composed of RAs and SDKs with partners such as NVIDIA, Mellanox, and others in the Weka Innovation Network (WIN).

Artificial Intelligence (AI) is an umbrella of different technologies that can really change the way things are done in the multiple fields. The benefits don’t come with some drawbacks. AI data pipelines are different from traditional file-based IO applications with different stages needing distinct storage IO requirements: massive bandwidth for ingest and training; mixed read/write handling for extract, transform, load (ETL); ultra-low latency for inference; and a single namespace for entire data pipeline visibility. More complications are piled on when one recognizes that AI solutions are often deployed at the edge. Up until now there was no solution that meets all of the requirements.

Weka AI is stated as solving these challenges, for performance by delivering over 73GB/s of bandwidth to a single GPU client. On top of that, the company claims it can deliver operational agility with versioning, explainability, and reproducibility and provides governance and compliance with in-line encryption and data protection. Weka AI is said to accelerate things like genomics, medical imaging, the financial services industry (FSI), and advanced driver-assistance systems (ADAS) deep learning (DL) pipelines. Finally, Weka AI is said to easily scale as well, so users from entry level to large enterprise can leverage the solution.

Availability

Weka AI bundles are immediately available.

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