Faster Edge AI, Fewer Headaches
If you’ve ever shipped a model that flew in the cloud and crawled on a device, this conversation is a relief valve. We bring on Andreas from Embedl to unpack why edge AI breaks in the real world—unsupported ops, fragile conversion chains, misleading TOPS—and how to fix the loop with a unified, device-first workflow that gets you from trained model to trustworthy, on-device numbers in minutes.
We start with the realities teams face across automotive, drones, and robotics: tight latency budgets on tiny chips, firmware that lags new ops, and the pain of picking hardware without reliable…
The skinny
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