AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a ...

This year’s winner of Best use of machine learning/AI, ActiveViam stood out for delivering a practical, production-ready ...

From SOCs to smart cameras, AI-driven systems are transforming security from a reactive to a predictive approach. This ...

Adam M. Root argues businesses must anchor ML in customer problems, not technology. He details a strategy using ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

For decades, soil management has relied on sparse field sampling and averaged recommendations. While effective in relatively uniform landscapes, this approach breaks down in real-world fields where ...

Automation experts from Beckhoff, DigiKey and Siemens Digital Industries explain how AI enhances motion control across applications in welding, automotive manufacturing and ...

Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...

The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...