Agile AI Platform Architecture with the Agile Cloud Manager
Part 0 of 10: Agenda
The entire transcript of this video is given below the video so that you can read and consume it at your own pace. We recommend that you both read and watch to make it easier to more completely grasp the material.
Artificial Intelligence can become a lot easier to implement at the enterprise level when you use a free tool called Agile Cloud Manager.
You can find this video and many others at the AgileCloudInstitute.io web site.
This video will explain ten specific aspects of enterprise A.I. platform architecture, which are summarized as follows.
- First, we will explain the common obstacles that most companies experience when trying to implement A.I. at the enterprise level. And we will summarize the primary ways that Agile Cloud Manager addresses those obstacles.
- Second, we will give a high-level summary of the many different kinds of use cases for artificial intelligence, and we will illustrate how A.I. models interact with the many types of use cases that an enterprise might require.
- Third, we will explain how A.I. models break down and degrade over time. The temporary relevance of A.I. models create a unique set of requirements for the architecture of an enterprise-level A.I. platform.
- Fourth, we will give a high-level view of the enterprise A.I. system development life cycle. You will see that many different projects need to be defined in order to address the unique requirements of artificial intelligence.
- Fifth, we will explain how you can speed up the progress of each project if you begin each A.I. project with a set of software-defined templates. These templates can enable artificial intelligence to become feasible at the enterprise level because the templates can eliminate redundant work.
- Sixth, we will illustrate how the continuous experimentation and training required for A.I. models can be integrated into an enterprise-level A.I. platform.
- Seventh, we will review and summarize the essential components of a software-defined enterprise A.I. platform that we explained in the first six slides.
Then we will describe two working examples of software-defined enterprise A.I. management platforms that you can download from the AgileCloudInstitute.io web site to use as a starter to seed your projects. (The examples are labeled as data lake house appliances, and each example includes AI project management.)
- Slide eight explains an Azure example.
- Slide nine explains an A.W.S. example.
- Tenth, and finally, we will describe next steps that you can take to begin enterprise-level management of A.I. to transform your organization.
Next: Proceed to Part 1: Problem Definition And How Agile Cloud Manager Solves The Problem
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