JFrog has launched JFrog ML, an MLOps solution that blends best practices from devops into the machine learning workflow. By integrating devsecops processes, it allows development teams and data scientists to deploy and manage AI applications securely and efficiently. Announced on March 4, this tool arises from JFrog's QWAK.ai acquisition and aims to simplify the complex nature of ML model development. With features like seamless promotion from experimentation to production, JFrog ML uses the JFrog Artifactory for model management and supports integration with leading AI technologies such as Hugging Face and Amazon SageMaker.
JFrog's ML solution introduces a structured approach to MLOps, aimed at integrating machine learning workflows with devsecops processes for enhanced enterprise-ready AI development.
By leveraging their Artifactory repository and integrating with platforms like Hugging Face and Nvidia, JFrog ML offers a comprehensive solution for managing the machine learning lifecycle.
Collection
[
|
...
]