We've been working on something slightly ridiculous. A language model for MCUs.
After V1, Atome LM v2 (SuperESP) turns an ESP32 into a tiny AI appliance capable of running:
• Voice commands
• Motion recognition
• Machine anomaly detection
• Air-quality classification
• Energy disaggregation
• Occupancy sensing
• Water leak detection
• Predictive maintenance
• Wearable activity recognition
• Agriculture monitoring
• Sound events
• Tiny custom classifiers
All offline.
No Linux.
No accelerator.
No WiFi required.
Everything was tested on a physical ESP32-WROOM-32.
Current numbers:
• ~27 KB runtime state
• ~265 KB free heap remaining
• Bit-for-bit reproducible decisions
• Ed25519 signed models
• Tamper-evident inference logs
• CSV → Train → Flash workflow
Before anyone asks:
No, this is not ChatGPT on an ESP32.
No, it's not magic.
The idea is simple:
Collect your sensor data.
Export CSV.
Train.
Flash.
Deploy.
[link] [comments]