From the course: Generative AI and Predictive AI in the Cloud: Foundational Concepts and Scenarios
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AI and cloud automation
From the course: Generative AI and Predictive AI in the Cloud: Foundational Concepts and Scenarios
AI and cloud automation
In the previous video, we highlighted some cloud automation features for storage and compute resources. Next, we'll continue coverage of cloud automation as it pertains specifically to AI systems. So to gain an appreciation for the business value behind cloud automation, we'll be going through a list of common features relevant to AI. Automated AI model deployment, which is when we use a cloud automation tool to deploy and also configure a model, including setting up the necessary storage and compute resources. We can use cloud automation tools to also collect and filter training data, which is referred to as data ingestion and preprocessing. Tools are available to evaluate a model's performance and to help optimize the model while it's undergoing training. Part of the cloud automation infrastructure is the ability to monitor AI model performance and to issue alerts when performance falls below a threshold or when potentially bad data is detected, thereby allowing us to intervene…
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