Cloud Analytics Drives Airplanes-as-a-Service Business

On-demand flying through an app sounds like something for only the rich and famous, yet the use of cloud analytics is making flexible flying a reality at start-up airline, KinectAir.  On April 7, 2021, The CTO of KinectAir, Ben Howard, will join the SNIA Cloud Storage Technologies Initiative (CSTI) for a fascinating discussion on first-hand experiences of leveraging cloud analytics methods to bring new business models to life that are competitive and profitable.

And since start-up companies may not have legacy data and analytics to consider, we’ll also explore what established businesses using traditional analytics methods can learn from this use case. Join us on April 7th for our live webcast “Adapting Cloud Analytics for Practical Business Use” for views from both start-up and established companies on how to revisit the analytics decision process with a discussion on:

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Video Analytics Q&A

There is a new wave of cognitive services based on video and image analytics, leveraging the latest in machine learning and deep learning. In a recent SNIA Cloud Storage Technologies Initiative (CSTI) webcast “How Video Analytics is Changing the Way We Store Video,” we looked at some of the benefits and factors driving this adoption, as well as explored compelling projects and required components for a successful video-based cognitive service. This included some great work being done in the open source community.

In the course of the presentation, there were several discussion points and questions that arose. Our SNIA presenters, Glyn Bowden from HPE and Kevin Cone from Intel provide the answers. 

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A New Wave of Video Analytics

Adoption of cognitive services based on video and image analytics is on the rise. It’s an intriguing topic that the SNIA Cloud Storage Technologies Initiative will dive into on December 2, 2020 at our live webcast, “How Video Analytics is Changing the Way We Store Video.” In this webcast, we will look at some of the benefits and factors driving this adoption, as well as explore compelling projects and required components for a successful video-based cognitive service. This includes some great work in the open source community to provide methods and frameworks, some standards that are being worked on to unify the ecosystem and allow interoperability with models and architectures. Finally, we’ll cover the data required to train such models, the data source and how it needs to be treated.

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