Best Alternatives to Muse Gadgets in 2025

This board is designed for AI at the edge, featuring a Cortex-M4F microcontroller and a suite of sensors (microphone, IMU, temperature, etc.). It supports TensorFlow Lite Micro and has a vast community, making it ideal for building AI gadgets without the complexity of Linux. Unlike Muse Gadgets, it's a ready-to-use board rather than a full toolkit, but it's highly accessible for beginners and offers robust AI capabilities.

The Raspberry Pi Pico is a low-cost microcontroller board that can run TensorFlow Lite for Microcontrollers. With its dual-core ARM Cortex-M0+ and flexible I/O, you can connect various peripherals to create AI gadgets. It's more affordable than a full Raspberry Pi setup and has extensive documentation and community support. While it lacks the integrated SDK of Muse Gadgets, it provides a solid foundation for custom AI hardware projects.

For more demanding AI applications, the Jetson Nano offers GPU acceleration and runs a full Linux environment, enabling advanced computer vision and natural language processing. It supports popular AI frameworks like TensorFlow and PyTorch. While it's pricier and more power-hungry than Muse Gadgets, it's ideal for prototypes requiring significant computational power, such as smart cameras or robotics.

The Coral Dev Board features Google's Edge TPU, a specialized ASIC for accelerating TensorFlow Lite models. It runs Linux and is designed for high-performance ML inferencing at the edge. It's a strong alternative for building AI gadgets that need fast, local processing, such as smart home devices or industrial IoT. However, it's less open-ended than Muse Gadgets and has a narrower hardware ecosystem.

Espressif's ESP32 is a popular, low-cost microcontroller with Wi-Fi and Bluetooth. Espressif provides ESP-DL, a deep learning library optimized for the ESP32, enabling AI capabilities like speech recognition and image classification. This is a direct alternative to Muse Gadgets' ESP32 support, but without Meta's specific SDK. It's highly customizable and has a large community, though you'll need to integrate components yourself.

While not a hardware kit, combining OpenAI's GPT-3 API with a Raspberry Pi allows you to build conversational AI gadgets. You can use the Pi to handle audio input/output and connect to GPT-3 for natural language processing. This approach offers state-of-the-art language understanding but requires internet connectivity and API costs. It's a flexible alternative if your focus is on voice assistants rather than full hardware control.

Mycroft is an open-source voice assistant platform that can run on Raspberry Pi and other Linux devices. The Mark II is a hardware kit for building a smart speaker with AI capabilities. It emphasizes privacy and customization, with an open-source stack. While it's more specialized for voice interactions than Muse Gadgets, it provides a complete solution for building a conversational AI device with hardware and software included.