Smarter Infrastructure for AI
AI workloads require GPUs, specialized processors that process massive amounts of data from structured and unstructured sources. Maximize GPU efficiency and ROI with high-performance, architecturally optimized solutions.
AI is transforming organizations everywhere. But data doesn’t analyze itself, and legacy systems often can’t support the massive AI data pipelines required for machine learning and deep learning. Pure Storage brings a massively parallel platform, capable of delivering ultra-fast, all-flash performance, to billions of objects and files.
Data is stuck in 20th-century infrastructure and sprawling silos, but it’s also the lifeblood of AI. From data capture to neural network training, Pure FlashBlade//S is built from the ground up to deliver a unified scale-out storage platform that consolidates and accelerates your data pipeline.
AI pilots often start on existing compute infrastructure or in the cloud. As data scales to production levels, performance and reliability become critical, legacy infrastructure can’t keep up, and cloud infrastructure can become very expensive. Scale AI to production levels with systems that are optimized for AI and lower total cost of ownership.
In a breakout year for AI, Pure Storage has been recognized by AI Breakthrough Awards as the Best AI Solution for Big Data.
“The computing speed of analyzing medical data has been greatly increased after introducing AIRI.”
“We needed fast and reliable storage for AI projects, and FlashBlade was an optimal choice for us. Since adopting FlashBlade, we are able to use data more efficiently and significantly reduce the cost of managing infrastructure.”
for Distributed File Systems and Object Storage
FlashArray and FlashBlade provide a robust and scalable storage solution for Meta’s RSC.
Artificial intelligence (AI) is a branch of computer science concerned with creating self-learning systems that can perform tasks that normally require human intelligence. From self-driving cars to predicting the future, AI is revolutionizing the ways in which we can use data to shape our world.
AI can power your data analytics pipeline in a number of ways—from processing unstructured data like streaming video feeds to powering advanced predictive analytics tools. AI algorithms can give your analytics capabilities the boost you need to remain competitive.
AI and big data have a symbiotic relationship where both are generally better together. The bigger and higher quality the training data set, the smarter the AI will become. On the flipside, big data analytics pipelines can leverage AI to efficiently process large quantities of unstructured data spread across multiple siloed environments.
The difference between AI, machine learning (ML), and deep learning (DL) lies in the scope of specificity:
AI deals broadly with building computer systems that can learn on their own.
ML is a subset of AI that deals with algorithms that can self-learn from training data.
DL is a subset of ML that deals with neural networks—specifically those that have more than one “hidden” layer between the input and output layers of the network.
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Pure Storage, Inc.
2555 Augustine Dr.
Santa Clara, CA 95054
800-379-7873 (general info)
