Resources
AI & Machine Learning using MAIXDUINO
This tutorial shows how to use micropython and Maixduino to build AI and Machine learning projects. The tutorial covers in-depth on how to set things up and use simple ML models for face detection, object detection, etc. Must read if you are building projects using the Maixduino board
MAX78000FTHR Evaluation Kit
The MAX78000 Feather development board comes with a ton of features, including an ARM Coretex M4 processor with Risc-V coprocessor, Convolutional Neural Network Accelerator, CMOS VGA Image Sensor, Stereo Audio CODEC, Digital Microphone and On-Board DAPLink debugger
Arduino UNO R4 WiFi
The Arduino Uno R4 WiFi combines a powerful 32-bit processor with ESP32 for Wi-Fi and Bluetooth capabilities. The board also supports the Arduino Cloud Platform enabling you to build IoT projects very easily. Its on-board LED matrix and Qwiic connector simplify prototyping, making it perfect for beginners and experts alike.
SIPEED MAXDUINO IoT Kit
The MaixDuino IoT Kit from Seeed Technologies comes with an on-board microphone, camera, and a TFT display allowing you to build quick AI and IoT projects. The board also supports Arduino IDE and Maixpy so you can write code in both C++ and micropython.
What is Edge AI?
The article discusses “Edge AI,” a new trend combining machine learning with IoT. It highlights the evolution of AI, the rise of machine learning, and deep learning, and the impact of AI on business. Edge AI runs algorithms on local devices, reducing network traffic and enabling efficient data processing.
How to use Arduino IoT Cloud?
Learn to develop, deploy, and monitor connected Arduino projects with the Arduino IoT Cloud. Sign in to your Arduino account, link your device, install the Arduino Create Agent, configure your board, and create a “thing” to manage your IoT projects and variables.
Cat.AI – Built with MAX78000FTHR
Tomorrow Lab collaborates Cornel Pizara from Analog Devices to create a product using the MAX78000— a new breed of AI Micro built to enable neural networks to execute at ultra-low power. For this one, the team decided to help out some furry friends.