Scalability posts

Deploying computer vision models in production is a complex endeavor that requires a holistic approach that inlcude data, models, infrastructure, and processes. By addressing the challenges of data acquisition, model selection, infrastructure, CI/CD, monitoring, and ethical considerations, organizations can successfully deploy computer vision models at scale.

Discover the benefits of implementing MLOps at the Edge for faster data processing, improved security, and reduced latency. Learn how to overcome the challenges of deploying machine learning models in Edge devices.

Federated Data Spaces refer to the idea of multiple linked data spaces, allowing data to be shared between different organizations, domains or even countries, exerting a multiplier effect of new use cases and innovation in the Industry.

EDGE's new capabilities for deploying machine learning and MLOps: the new flagship deployment model.