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

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 ...

The progression of glaucoma was accurately predicted by machine learning models based on structural, functional and vascular biomarkers, including those from OCT angiography, according to data ...

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

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

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

AI models using ultrasound imaging demonstrate superior diagnostic performance for ovarian cancer compared to sonographers, with higher sensitivity and specificity. The study emphasizes the need for ...

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 ...

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 ...