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Show HN: A language model that lives in a boot sector

Hacker News Top ↗ · 10h ago Cached

bootgpt 是一个完全容纳在 510 字节 MBR 中的神经网络运行时,加载下一扇区的 11.5KB int8 量化字符级模型,在 386 的 16 位实模式下无操作系统运行,用于在开机时生成虚构的 Linux 启动日志。

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#tiny-ml

pico-type: A 1.5M-Parameter Byte-Level Multi-Head Content Classifier

arXiv cs.LG ↗ · 2026-08-18 Cached

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.

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#tiny-ml

An SLM trained on $8 ESP32-S3

Hacker News Top ↗ · 2026-08-05 Cached

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.

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#tiny-ml

Recent project I worked on: End to End Edge ML platform [D]

Reddit r/MachineLearning ↗ · 2026-07-27

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.

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#tiny-ml

Toward a Modular Architecture for Embedded AI Agent Systems at the Edge

arXiv cs.AI ↗ · 2026-06-03 Cached

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.

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#tiny-ml

Two-Valued Symmetric Circulant Matrices: Applications in Deep Learning

arXiv cs.LG ↗ · 2026-05-19 Cached

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.

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#tiny-ml

Building ML framework with Rust and Category Theory

Hacker News Top ↗ · 2026-05-14 Cached

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.

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