This article is from Arduino Project Hub Author: Arduino “having11” Guy Prerequisites Like humans, plants can also get sick; for instance, the leaves of a plant may turn yellow or develop spots due to fungi or other pathogens. Thus, by harnessing the power of machine learning, we can scan the colors and then use them … Read more
Posted by: ArduinoTEAM — May 26th, 2020 Running Machine Learning (ML) on microcontrollers is one of the most exciting developments in recent years, allowing small battery-powered devices to detect complex movements, recognize sounds, or find anomalies in sensor data. To make it accessible for every embedded developer to build and deploy these models, we have … Read more
TinyML is a type of machine learning characterized by shrinking deep learning networks for use in micro hardware, primarily applied in smart devices. Ultra-low power embedded devices are “invading” our world, further promoting the proliferation of AI-driven IoT devices with the help of new embedded machine learning frameworks. FPGA has been applied across various fields … Read more
Today,the data processing architecture exhibits a “split” characteristic. The focus has shifted to “cloud” computing, which boasts massive scale and computational power, while “edge” computing places the processing right at the “front line”, connecting electronic devices with the real world. In the cloud, the volume of data stored is enormous, and processing must be queued … Read more
This article is contributed by the community, Author Wang Yucheng, ML & IoT Google Developers Expert, Chief Engineer of the Smart Lock Research Institute at Wenzhou University.Learn more: https://blog.csdn.net/wfing Introduction to TinyML 1. Overview Pete Warden and Daniel Situnayake co-authored a book introducing how to run ML on Arduino and ultra-low-power microcontrollers, TinyML: Machine Learning … Read more
Many innovations in today’s edge technology began with consumer electronics and mobile devices. The smartphones, tablets, cameras, smart speakers, drones, and other devices we use in our daily lives are actually various forms of AI edge devices. These devices are embedded with many different operating systems and optimizations for specific chips to enable them to … Read more
1. Introduction Voice recognition technology (Automatic Speech Recognition) is a technology that converts human speech into text. For example, voice assistants like “Hey, Siri” and “Hi Alexa” are applications of voice recognition technology. Through voice assistants, users can directly control home appliances such as air conditioners, TVs, curtains, and lights using their voice, making device … Read more
LLM (Large Language Model) Definition: Large Language Models are AI models designed to understand and generate natural language text. They are typically based on deep learning techniques and trained on vast amounts of text data. Examples: GPT-3, GPT-4 (provided by OpenAI) BERT (provided by Google) T5 (provided by Google) Application Scenarios: Text generation Translation Sentiment … Read more
The rapid development of the Internet of Things (IoT) in the past two years is evident to industry professionals. However, as development accelerates, the difficulty of developing new devices also increases significantly. How can we achieve the best development experience while maintaining security and low power consumption, and reduce time-to-market? To excel in a task, … Read more
1. Introduction The booming development and wide application of chatbots In the e-commerce customer service sector, chatbots respond to customer inquiries at any time, quickly answer product questions, handle after-sales issues, improve customer service efficiency, and reduce labor costs; on social platforms, they can chat with users, play games, and enhance interactive fun; in smart … Read more