With the rapid adoption of AI-enabled services into production applications, it’s important that organizations are able to secure the AI/ML components coming into their software supply chain. The good news is that even if you don’t have a tool specifically for scanning models themselves, you can still apply the same DevSecOps best practices to securing …
With Gartner estimating that over 90% of newly created business software applications will contain ML models or services by 2027, it is evident that the open source ML revolution is well underway. By adopting the right MLOps processes and leveraging the lessons learned from the DevOps revolution, organizations can navigate the open source and proprietary …
Today, we’re excited to announce a new integration with Amazon SageMaker! SageMaker helps companies build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. By leveraging JFrog Artifactory and Amazon SageMaker together, ML models can be delivered alongside all other software development components in a modern …
TL;DR: JFrog’s ML Model Management capabilities, which help bridge the gap between AI/ML model development and DevSecOps, are now Generally Available and come with a new approach to versioning models that benefit Data Scientists and DevOps Engineers alike. Model versioning can be a frustrating process with many considerations when taking models from Data Science to …
The Wake-Up Call The rapid rise of artificial intelligence, more specifically, generative AI systems such as OpenAI’s ChatGPT, has simultaneously spurred intense development and concern over the past year. On the 30th of October, President Joe Biden signed an Executive Order that urges new federal standards for AI development, safety, security, and trustworthiness that also …
