Search Results for "personal"

...Even though it’s running on minimal hardware, MimiClaw maintains local memory that persists across power cycles, enabling context continuity over time without relying on cloud services. Its architecture emphasizes privacy, low power, and portability, ideal for personal or hobbyist use cases where privacy and local control matter.

zclaw is a highly compact personal AI assistant framework designed to run on constrained embedded hardware such as the ESP32. The project focuses on delivering core assistant capabilities within an extremely small footprint, demonstrating how AI-driven automation can operate on microcontrollers. It includes support for GPIO control, scheduled tasks, memory handling, and other embedded automation features that enable real-world device interaction.

LLMFarm is a framework designed to simplify the deployment, management, and utilization of large language models in local or self-hosted environments, focusing on accessibility and efficient resource usage. It enables users to run LLMs on personal hardware or private infrastructure, reducing dependency on external APIs and improving data privacy. The system typically provides a user-friendly interface for loading models, configuring inference parameters, and interacting with them through chat or task-based workflows. It emphasizes modularity, allowing users to integrate different models, backends, or tools depending on their needs and hardware capabilities. ...

MERP is a modular low cost robot platform designed as a research tool or for personal use. It allows real world testing of algorithms developed in simulation for trajectory planning, obstacle avoidance, human robot interaction, among others.

Voice interface to drive your operating system

Computer Vision Software designed for AttyTheWalker, a made from scratch hexapod robot. Entirely developed in C language for GNU/Linux platforms it's the best way to move the robot using a personal computer with RS-232 serial communication.

Personal research achievements from the authors presented here in the form of symbolic Algebra and non-numerical analysis algorithms implemented in C/C++, Java, and/or Pascal. As part of a more wide, simple, powerful and robust CAS enviroment under development, new code will be continuously added up to this repository. The authors give their welcome and encouragement to everyone interested in bring some kind of collaboration.