Edge AI: Real Solutions for Real World Problems
summary
Claims that a full, deployable Edge AI stack exists: silicon, tools and support that hit real constraints rather than benchmark numbers. Microchip Edge AI solutions pair microcontrollers, microprocessors and FPGAs that run GOPS-class inference without fans or high power with toolchains like ONNX, Yocto, MPLAB ML and Edge Impulse and offer supply longevity, security and partner services. Demonstrated use cases include predictive maintenance with multimodal sensors and on-device audio anomaly and keyword spotting, implemented in low‑power compact hardware that meets runtime and lifecycle requirements.
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chapters (9)
- 0:00Edge AI solutions
- 1:05Microchip’s Edge AI role
- 2:50Why AI at the edge matters
- 4:58Predictive maintenance with AI
- 6:22Audio AI applications and challenges
- 8:49Edge AI use cases beyond vision
- 10:35Hardware for Edge AI
- 12:19Microchip’s Edge AI toolkit
- 13:50Closing & Q&A
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