Data engineering is the process that makes it usable. It involves moving, cleaning, and organizing. This creates the foundation for BI and analytics. The goal is to replace guesswork with facts. That ...

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

Understand the critical differences between edge gateways and historians to make informed decisions about collecting, ...

1. Risk: AI Monoculture (Shared Blind Spots). This is the most critical and overlooked systemic vulnerability. Building your ...

Discusses Counter-Drone Solutions and Industry Trends at Drone Conference December 10, 2025 4:30 AM ESTCompany ...

The business world used to operate in silos—local shops served local customers, and global corporations dominated international markets. But that line has blurred. Today, a bakery in Singapore can ...

Materials informatics combines data analytics and engineering design, streamlining material development and enhancing ...

A key lesson was to measure what matters. From the outset, we defined clear success metrics—latency reduction, resource ...

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

This article examines how cameras are deployed in robotics and how GMSL can enable scalable, performance-driven robotic ...

Fears about AI data centers’ water use have exploded. Experts say the reality is far more complicated than people think.