In recent years Artificial Intelligence and Machine Learning have become the hottest topics, promising significant improvements across a range of industries. Following the trend, many companies made significant steps in areas of AI/ML. The typical approach is to take one or more business cases and seek to apply AI/ML technologies of different readiness levels to solve them.
AI DevOps is the seamless integration across multiple designs and delivery phases to rapidly deliver into production highly trusted AI/ML models, with continuous monitoring, automated assessments and refinements. It is built by cross functional teams that have all the necessary skills and expertise. It adopts core DevOps practices, such as continuous integration and deployment. It extends them to address the additional challenges of AI/ML – managing not just code but data and models to enable rapid iterative development, simplify maintenance, and enable re-use.
In this whitepaper, we will cover the key challenges to AI/ML industrialization and how the use of AI DevOps can streamline AI/ML development and deliver successful projects at scale. Download to know more.