Espressif Systems has introduced the ESP-Claw framework, designed to enable ESP32 devices to function as local AI agents. The framework allows hardware to interact with Large Language Models (LLMs) to make decisions and execute actions locally without requiring constant cloud connectivity. It supports natural language conversation for defining device behavior through chat coding and utilizes Lua scripts for deterministic execution.
Key features include:
- Local event bus driving millisecond-latency responses via Lua rules.
- MCP Server and Client capabilities for hardware exposure and external service calling.
- On-chip private memory for long-term context retention without data leaving the device.
- Support for various messaging platforms including Telegram, WeChat, and Feishu.
- Compatibility with LLMs such as OpenAI, Qwen, and ChatGPT.
- Current support for ESP32-S3 with upcoming support for ESP32-P4.
Key features include:
- Local event bus driving millisecond-latency responses via Lua rules.
- MCP Server and Client capabilities for hardware exposure and external service calling.
- On-chip private memory for long-term context retention without data leaving the device.
- Support for various messaging platforms including Telegram, WeChat, and Feishu.
- Compatibility with LLMs such as OpenAI, Qwen, and ChatGPT.
- Current support for ESP32-S3 with upcoming support for ESP32-P4.
M5Stack has launched the AI-88502 LLM Accelerator M.2 Kit, based on the LLM-8850 M.2 card with a 24 TOPS Axera AX8850 SoC, offering an alternative to the Raspberry Pi AI HAT+ 2 for LLM and AI vision workloads.
Arduino has released the Nesso N1, a compact IoT controller built around the ESP32-C6 RISC-V microcontroller, featuring Wi-Fi 6, Thread, LoRa, a touch display, and multiple sensors for rapid prototyping and portable embedded applications.
M5Stack LLM-8850 card is an M.2 M-Key AI acceleration module powered by an Axera AX8850 SoC delivering 24 TOPS of performance, compatible with devices like Raspberry Pi 5 and Rockchip RK3588 SBCs. It features 8GB RAM, 32Mbit SPI NOR flash, and supports H.265/H.264 8Kp30 video encoding/60fps decoding.
A web-based flasher for various devices, including M5Stack, LilyGO, CYD, and custom boards. It provides instructions for entering download mode and selecting firmware for flashing.
An overview of the M5Stack Cardputer, a compact, card-sized portable computer with an ESP32-S3 chip, keyboard, screen, and various peripherals. It's aimed at engineers, developers, and IoT enthusiasts, with support for Python, Arduino, and even a Forth interpreter.
A user is asking about the compatibility of different modules (GPS, GPIO, I2C, 'Port C' UART) with the Cardputer, specifically whether modules using 'Port C' can be used.
A curated list of resources for the M5Stack Cardputer, a $30 credit-card sized mini computer based on the ESP32-S3. Includes specs, pre-installed apps, community apps, and resources.
The Cardputer v1.1 is a high-performance card computer for engineers featuring the StampS3A microcontroller, 56-key keyboard, 1.14-inch TFT screen, and various connectivity options for prototyping, industrial control, and IoT projects.
The M5Stack Cardputer v1.1 is a high-performance card computer featuring a StampS3A microcontroller, 56-key keyboard, 1.14-inch TFT screen, and various interfaces for expansion and control. It's ideal for rapid prototyping, industrial control, and IoT projects.
