Tag：AI - lyan · CodeFun

OpenClaw Agent Technical Deep Dive

lyan 2026-02-21

This document outlines the architecture and implementation of a production-ready OpenClaw agent system deployed on edge hardware. Over a four-day sprint, a complete system was engineered, moving from concept to a stable, running instance. The project involved significant hardware and software integration, including a dual-model LLM strategy for cost and latency optimization, multimodal input via OpenAI Whisper, and asynchronous communication channels. This post-mortem serves as a technical deep-dive for engineers and architects working on similar agent-based systems.

AI Jetson OpenClaw Agent

Build a Fashion-MNIST CNN with PyTorch

lyan 2021-07-10

This document details the process of developing and optimizing a Convolutional Neural Network (CNN) for the Fashion-MNIST dataset using PyTorch. Building upon the foundational work of "Let's Build a Fashion-MNIST CNN, PyTorch Style" ^[1], this project introduces significant enhancements, including a redesigned CNN architecture, a systematic hyperparameter tuning process, and comprehensive testing and visualization. The optimized model achieves a training accuracy of 99.02% and a test accuracy of 91.01%, a substantial improvement over baseline models. This report outlines the methodology, model architecture, optimization techniques, and data analysis that led to these results.

OpenClaw Agent Technical Deep Dive

Build a Fashion-MNIST CNN with PyTorch

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