EdgeAi

Introduction “Edge AI on Microcontrollers: Thriving Without GPUs” 🚨 The AI industry is abuzz with recent news: The U.S. has imposed a ban on exporting high-performance GPUs from NVIDIA and AMD to countries like China, Russia, and Iran. For years, GPUs have been the backbone of AI development, enabling massive computations for training and deploying […]

Let’s start with an example of predictive maintenance in motor control. Imagine this scenario: if a motor’s output current, temperature, or vibration levels deviate by ±10-20%, a threshold-based system flags an issue. Problem solved, right? Not so fast. While thresholds are straightforward, they fall short in handling the real-world complexity of motor systems. AI/ML models

What if the tiniest chips in your devices could run AI models powerful enough to provide real-time insights, smarter automation, and predictive capabilities—all while keeping the cloud out of the picture? 🧠✨ That’s the promise of Tiny AI paired with the right microcontroller unit (MCU). In this article, we’ll dive into the best pairings of

Imagine this: Your smartwatch doesn’t just count steps—it understands your daily habits, predicts health risks, and communicates seamlessly—all while consuming minimal power. Sounds futuristic? This is the power of Tiny AI, a groundbreaking innovation enabling powerful intelligence on the smallest devices. In this article, we showcase the best Tiny AI models optimized for edge devices,

Tags: #EdgeAI #EmbeddedSystems #Cybersecurity #MCUs #IoT #SmartDevices #AutomotiveAI #ConnectedTech Introduction: Edge AI Meets Embedded Systems Embedded systems are evolving rapidly, driven by the integration of Edge AI is a game-changing technology enabling devices to process data locally for real-time insights, enhanced security, and superior performance. “AI Models run on our embedded devices.” Edge AI’s going