Cybersecurity in Physical AI: Redefining Robotic Safety Beyond Functional Failures

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Published: September 19, 2026

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For decades, robot safety was evaluated through a relatively straightforward lens: Can a machine operate reliably, and what happens when a physical component fails? Engineers built safety loops, emergency stops, and redundant hardware to prevent hardware failures from causing physical harm. However, as robots transition into "Physical AI" systems—harnessing deep learning, multimodal sensors, and real-time decision-making models—this classical safety paradigm is no longer sufficient.

Today's autonomous systems do not just execute pre-programmed paths; they perceive their surroundings, interpret context via vision-language-action (VLA) models, and translate those digital thoughts into physical actions. This reliance on a complex data pipeline introduces a critical vulnerability. What happens when a robot's hardware operates perfectly, but its perception, reasoning, or communication channels are subtly manipulated by an external actor?

Beyond Functional Safety: Securing Physical AI Against Cyber-Physical Exploits

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Published: September 18, 2026

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For decades, robotics safety has been defined by functional reliability. Engineers have focused on a core engineering question: How do we prevent harm when a hardware component, sensor, or structural link fails? Standard safety frameworks like ISO 13849 have served us well by ensuring that when an actuator fails or a laser scanner gets blocked, the system enters a predictable, safe state. However, the rise of Physical Artificial Intelligence is fundamentally disrupting this paradigm.

Today's autonomous systems do not just execute static, pre-programmed trajectories. They rely on complex, multimodal neural networks, Vision-Language-Action (VLA) models, and real-time inference engines to interpret and interact with dynamic environments. This integration of deep learning with physical actuation introduces an entirely new class of vulnerabilities. The critical question for modern robotics and embedded engineers has changed: How do we keep a machine safe when its hardware functions flawlessly, but its perception, reasoning, or decision-making has been covertly manipulated?

In Memoriam: Honoring the Pioneers of Modern Wireless Networks, Cellular Infrastructure, and Hardware Design

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Published: September 17, 2026

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The modern landscape of electronics, embedded systems, and wireless communications did not appear overnight. It was constructed piece by piece, protocol by protocol, by brilliant minds working in university labs, research institutions, and early industrial facilities. Recently, the engineering community said goodbye to several giants whose seminal contributions paved the way for the technologies that IoT developers, hardware makers, and embedded engineers use every single day. From the first wireless packet network to the birth of commercial cellular networks and the languages used to design microchips, we look back at the incredible legacies left behind by these pioneers.

Imagine a world where data transmission always required a dedicated, physical cable. That paradigm shifted dramatically thanks to the work of Franklin 'Frank' Kuo, who passed away recently at the age of 91. In the late 1960s, Kuo joined the faculty of the University of Hawaii, where he collaborated with Norman Abramson to develop ALOHAnet. Going online in 1971, ALOHAnet utilized ultrahigh-frequency (UHF) radio waves to link computers across the Hawaiian islands. It was the world's first public demonstration of a wireless packet data network.