Objective In Indonesia, the second most natural disaster-prone country in the world, the tobacco industry exploits such crises via corporate social responsibility. The objective of this study was to ...

Utilize AI to analyze application runtime data (e.g., rendering time, communication latency), obtain optimization suggestions (such as reducing component re-rendering, reusing hardware connections), ...

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 Komprise data management survey shows that 74% have 5PB or more of stored data and 85% of participants expect to spend ...

More than ever, building and maintaining trust, the bedrock of every business, succeeds or fails based on how data is handled ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results.

Google recently published a guide outlining eight essential design patterns for multi-agent systems, ranging from sequential ...

A practical guide to the four strategies of agentic adaptation, from "plug-and-play" components to full model retraining.

Compare and discover the best workload management tools like ClickUp and Teamwork.com for balancing team capacity and tracking utilization.

Data management is the process businesses use to gather, store, access and secure data from various platforms. Managing this information properly helps organizations utilize data analytics to gain ...

From traditional fuses to eFuses, understanding the advantages, limitations, and use cases of each technology helps engineers ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...