Driving Competitive Advantage through Oracle Cloud, Edge Computing and AI

Driving Competitive Advantage through Oracle Cloud, Edge Computing and AI

I have been experimenting with #ChatGPT and #Google #BARD #AI

I asked BARD to summarize our recently released white paper which is a great story of collaboration between 英特尔 甲骨文 德勤 as well as Falkonry I think BARD did a decent job to summarize the white paper. Here is the unedited version of the summary.

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The white paper discusses how Intel and Oracle are working together to provide a cloud-native, open, and secure platform for AI and ML workloads. The paper covers the following topics:

  • The challenges of AI and ML workloads
  • The need for a cloud-native, open, and secure platform
  • How Intel and Oracle are working together to meet these needs
  • The benefits of using Intel and Oracle's platform

The paper concludes by stating that Intel and Oracle's platform is the ideal solution for organizations that are looking to deploy AI and ML workloads at scale.

Here is a more detailed summary of the paper:

  • The challenges of AI and ML workloads

AI and ML workloads are becoming increasingly complex and demanding. This is due to the growing amount of data that is being generated, the need for faster processing speeds, and the need for more sophisticated algorithms.

  • The need for a cloud-native, open, and secure platform

In order to address the challenges of AI and ML workloads, organizations need a cloud-native, open, and secure platform. This platform should be able to scale to meet the needs of large-scale deployments, it should be able to support a variety of different workloads, and it should be secure enough to protect sensitive data.

  • How Intel and Oracle are working together to meet these needs

Intel and Oracle are working together to provide a cloud-native, open, and secure platform for AI and ML workloads. This platform is based on Intel's hardware and Oracle's cloud infrastructure. It provides a number of features that make it ideal for AI and ML workloads, including:

* Scalability: The platform can scale to meet the needs of large-scale deployments.
* Performance: The platform can provide the performance that is required for AI and ML workloads.
* Security: The platform is secure enough to protect sensitive data.
* Openness: The platform is open, which allows organizations to choose the tools and technologies that best meet their needs.        

  • The benefits of using Intel and Oracle's platform

There are a number of benefits to using Intel and Oracle's platform for AI and ML workloads. These benefits include:

* Improved performance: The platform can provide the performance that is required for AI and ML workloads.
* Reduced costs: The platform can help organizations to reduce the costs of AI and ML workloads.
* Increased agility: The platform can help organizations to increase their agility and to respond more quickly to changes in the market.
* Improved security: The platform can help organizations to improve the security of their AI and ML workloads.        

Overall, Intel and Oracle's platform is a powerful and versatile solution for organizations that are looking to deploy AI and ML workloads at scale. It offers a number of features that make it ideal for these workloads, and it provides a number of benefits, including improved performance, reduced costs, increased agility, and improved security.

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What do you think of the summarization done by BARD? Also watch the video, that goes with the White Paper. Jake Hall Mark Saltzman Nikunj Mehta

Terri Cobb??Brian Campbell?Mark Bagley?Ashley Smith?Matt Sheerin?Ryan Givhan?Doug Bourgeois?Thomas Henry?

Nikunj Mehta

AI-Driven Decision Intelligence Expert | Protecting & Optimizing operations | 30+ international patents

1 年

Shyam - great to see the publication of this white paper. As a leader in Edge AI, we are constantly pushing the limits of all the elements referred here - processing, usefulness of insights and economics - so that it can provide desired benefits in various kinds of situations. I thought the summarization was a little long but it also didn’t miss much that is important.

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