AI Adoption posts

Deploying machine learning models across multiple locations is becoming critical for scaling AI. Whether you're building infrastructure or serving diverse clients, this guide covers key strategies, challenges, and best practices for successful multi-site model deployment.

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.

AI flexibility algorithm based on consumption and production patterns to minimise congestion and overvoltage events

Everything you need to know about edge computer vision

Artificial Intelligence in Industry: Main applications and its progress towards the Edge

The role of TinyML in embedded systems that is revolutionizing the AI industry.