Pure Storage
FEBRUARY 26, 2024
The Car as Code: Software Drives the Automotive Industry by Pure Storage Blog Let’s start with a bold quote: “Once, software was a part of the car. To help alleviate these automotive industry challenges, automakers are building their own, internal platforms. What Are the Biggest Disruptors in the Automotive Industry?
Pure Storage
OCTOBER 4, 2022
The in-car experience has come a long way since the early days of automotive transportation. To accelerate innovation, automotive companies have had to adopt software-driven business models to meet current and future market expectations. . Any excess capacity gets re-distributed to support ongoing development needs. .
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Pure Storage
JANUARY 19, 2022
Original equipment manufacturers (OEMs) in the automotive industry are facing a rude awakening. In this new world, automotive telemetry and in-vehicle functionality take precedence over car looks and build quality. Implications for Automotive Data Storage. The Transition from Engineering to Data.
Pure Storage
AUGUST 11, 2022
It has many potential applications in the automotive industry. . The Right Platform for Automotive AI . To help automakers realize the many promises of automotive AI, Pure and NVIDIA have created AIRI//S ™, a complete AI technology stack. This is where artificial intelligence (AI) can play a key role.
Emergency Planning
FEBRUARY 9, 2021
Civil protection, in the form of locally-based disaster response capacity, would begin to emerge in the following decade, which would end with the inauguration of the United Nations Decade for Natural Disaster Reduction. Nonetheless, there were some surprising victories in the food processing and automotive sectors.
Pure Storage
MARCH 1, 2024
and 77% (automotive and other industries) to 82% (telecom). Half of the respondents worldwide (50%) said that generative AI would require them to rethink their unstructured data capacity; 49% said generative AI would change how the business approaches the cloud operating model.
Pure Storage
JUNE 8, 2022
There are so many practical applications for this technology that it’s no surprise AI is now supporting mainstream use cases in industries from healthcare and life sciences, to semiconductor and chip manufacturing, to automotive, financial services, and beyond. Challenges of AI Implementation.
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