@PitDuran This discussion highlights questions about adding AI features—like voice commands, image recognition, or anomaly detection—to embedded/IoT projects and choosing between on-device and cloud AI. It reflects the real challenges developers face when balancing performance, power, and usability in smart devices. For teams tackling such embedded AI integration, ai application development services https://artjoker.net/services/ai-app-development/ can offer expertise in designing custom workflows, tools, and models that fit both edge and cloud use cases, helping turn complex ideas into reliable solutions.

M5Paper quirks can definitely slow you down. Curious what steps you’ve tried so far and if any improvements helped.

@seahope Interesting post! Leveraging HF models like Realistic Vision with the AX8850 module sounds like a solid step toward faster, more efficient on-device AI workflows.