Intro to the concept that is worth examining for developers. Intro below for common Cloud usage. Includes detail links.
Artificial Intelligence #31 - Understanding the AI cloud landscape
Published on November 23, 2021 By Ajit Jaokar in Linkedin,
Course Director: Artificial Intelligence: Cloud and Edge Implementations - University of Oxford
To provide some context, when we refer to the cloud, the discussion is often confined to Iaas – Paas – Saas – but to understand the AI cloud landscape, the flow of thought is:
Understanding the Cloud landscape
Understanding Cloud native development
Understanding MLOps and Model Ops
Understanding cloud native AI architectures for AWS, Azure, GCP
We consider the wider meaning of ModelOps as defined by Gartner
ModelOps (or AI model operationalization) is focused primarily on the governance and life cycle management of a wide range of operationalized artificial intelligence (AI) and decision models, including machine learning, knowledge graphs, rules, optimization, linguistic and agent-based models. Core capabilities include continuous integration/continuous delivery (CI/CD) integration, model development environments, champion-challenger testing, model versioning, model store and rollback. .... '
No comments:
Post a Comment