If you are interested in running machine learning on embedded devices but are unsure how to get started, Google’s TensorFlow Lite team member Pete Warden will introduce how to build and run your own TinyML applications. This will include an overview of the different boards, software frameworks, and tutorials available to help you get started … Read more
Introduction: This issue is the AI Briefing for 20210219, bringing you 8 news articles. The first wave after the Spring Festival is here, spring has come, and work resumes! New year, new atmosphere, and I hope everyone pays more attention to the community, where more exciting content awaits you! This article has a total of … Read more
Explore Smart Manufacturing Community IoT Enhancement Solutions: Insights on TinyML and MES Theme of This Session: IoT Enhancement Solutions: TinyML and MES Insights Event Time: May 13 (Thursday) 19:00 – 20:30 Event Location: Youli Cafe (Building 21, Zijing Apartment, 2nd Floor, near Zhilan Garden) Event Content The Ministry of Industry and Information Technology’s “13th Five-Year … Read more
Introduction Check out Why FPGA/ADC Communication Prefers GPMC Interface in Industrial Applications? to learn about TinyML~ Today, I will introduce several open-source projects related to TinyML. TinyML Cookbook https://github.com/PacktPublishing/TinyML-Cookbook Overview This book is about TinyML, a rapidly evolving field that lies at the unique intersection of machine learning and embedded systems, enabling AI to be … 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
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
Edge Computing Applications We know that the concept of edge computing resonates with cloud computing centers. Especially after the widespread application of the concepts of 5G and the Internet of Things in the business scenarios of Industrial Internet, the number of connected smart terminals and the data that needs to be processed are increasing, leading … Read more
According to a report from Electronic Enthusiasts (by Li Wanwan), with the explosive growth of IoT devices, massive data will accumulate at the edge, and edge AI is entering a booming development phase. Gartner predicts that by 2023, more than 50% of large enterprises will deploy at least six edge computing applications for IoT or … Read more