As embedded and IoT systems grow more connected and critical, their security risks extend well beyond traditional software ...

As organizations scale from co-pilots to fully autonomous digital colleagues, the challenge is building smarter operating ...

The study advances a broader argument about the future of responsible AI. It contends that ethical AI cannot be achieved ...

Multispectral Intelligent Vision System with Embedded Low-Power Neural Computing is now nearing completion.

Test vendors use AI and machine learning to handle massive data volumes from complex electronics and detect hard-to-find ...

Left-shifting DFT, scalable tests from manufacturing to the field, enabling system-level tests for in-field debug.

Fraud detection is defined by a structural imbalance that has long challenged data-driven systems. Fraudulent transactions typically account for a fraction of a percent of total transaction volume, ...

Bioprocessing data is often scattered across electronic laboratory notebooks (ELNs), laboratory information management systems (LIMS), instruments, spreadsheets, and legacy systems that don’t talk to ...

As AI and robotics transform healthcare, the challenge is shifting from developing new tools to delivering measurable value ...

From PSIM’s rise and fall to the emergence of integration alliances, connected intelligence, and agentic AI, the physical ...

AI, automation, green fuel, robotics and digital corridors all scaled together in 2025, reshaping global air cargo into a ...

Thanks to their agility and resilience, software-defined radios can provide a capable first line of defense against threats ...