How Knowledge Distillation Brings AI to Industrial Edge Devices
Learn how knowledge distillation converts AI-derived behavior into compact decision rules that configurable mixed-signal hardware can execute at the industrial edge.
Learn how knowledge distillation converts AI-derived behavior into compact decision rules that configurable mixed-signal hardware can execute at the industrial edge.
As mechanical fallback disappears, automotive safety depends on precise position data. Learn how inductive position sensing enables functional safety, cyber resilience, and trust in x-by-wire systems.
Learn how the Renesas modular IO-Link platform helps sensor and actuator manufacturers lower development costs, reduce risk, and accelerate time to market.
Discover how a low-voltage Renesas REXGaN® transistor can improve efficiency and thermal performance in 48V to 12V converters, enabling higher switching frequencies and smaller passive components.
Explore how functional safety and intelligent video monitoring are enabling safer, more sophisticated HUD and AR-HUD experiences.
Use case for upgrading a next-generation electrocardiograph to the Renesas RZ/G2L with Qt, replacing an aging existing platform. The result was improved CPU performance and GPU acceleration, while providing a clear upgrade path to the AI-enabled RZ/G3E.
RZ/G3L and RZ/G3SE MPUs enable scalable HMI and IoT edge designs with common hardware and software assets and optimized performance.
Learn how system-level design, digital tools, and ecosystem collaboration are helping engineers tackle humanoid robotics complexity in the physical AI era.
Renesas' 2025 Business & Sustainability Report details progress toward carbon neutrality, resource conservation, and responsible business practices.
Renesas is expanding analog innovation through configurable technologies, digital design tools, and system-level expertise to help engineers build smarter, more integrated systems across industries.