tiny-ml

Pico-type is a 1.5M-parameter byte-level multi-head classifier that predicts seven content properties from raw UTF-8 bytes in a single forward pass, designed for efficient on-device inference with minimal resources.

Qapla' is a project that demonstrates training a small transformer language model from scratch on an $8 ESP32-S3 microcontroller, showing that on-device training is feasible without a GPU or datacenter.

An open-source end-to-end machine learning platform for edge devices (MCUs) that simplifies data labeling and deployment, featuring an auto-labeler for time-series sensor data and a chatbot for data insights.

Proposes a modular reference architecture for embedded AI agent systems at the edge, decoupling on-device and cloud-augmented agents with a governance layer for safety and policy enforcement.

This paper proposes the Two-Valued Symmetric Circulant Matrix (TVSCM), a very sparse architecture that uses only two weights per layer to achieve over 80x parameter reduction on MNIST and MIT-BIH arrhythmia datasets while maintaining comparable accuracy, making it ideal for edge and tiny-ML platforms.

This article announces a working draft book 'Category Theory for Tiny ML in Rust' and a public workshop introducing a tiny ML pipeline using Rust and category theory, aimed at making machine learning structure explicit through typed transformations.