Iterative launches MLEM to bridge the gap between ML engineers and DevOps teams by using the git-based approach that developers are already familiar with.

Conclusion Treating ML models as artifacts within the larger software supply chain transforms the traditional approach of separating DevOps and MLOps into a unified, cohesive process.

AI/ML Model Deployments with Security and Compliance Guardrails: Opsera ensures that model training and deployment using Databricks infrastructure meets security and quality guardrails and thresholds ...

AI and machine learning (ML) technologies are revolutionizing the deployment and optimization of wireless sensor networks (WSNs).