Search Results: MLOps

Verbit's architecture team eliminated ML algorithm integration headaches by abstracting research code into Temporal workflows. This approach enables automatic production updates without rewrites, ML engineers, or cross-team bottlenecks—delivering resilience and scale for free.

A new open-source Python project called DemandCast is enabling precise hourly electricity demand forecasting worldwide. Developed by the Open Energy Transition team, the platform combines public demand data, weather patterns, and machine learning to support critical energy planning, especially in data-scarce regions.

Traditional AI pipelines reliant on static database snapshots fail to capture the dynamic reality of business operations. A new approach advocates integrating Event Sourcing with AI/ML, enabling systems that continuously learn from real-time domain events, offering unprecedented traceability, adaptability, and alignment with actual processes.

New analysis reveals why 80% of AI projects fail during the treacherous deployment phase between prototype and production—and how MLOps and infrastructure shifts are turning the tide. Discover the technical make-or-break factors determining real-world AI success.