According to a report from Electronic Enthusiasts (by Li Wanwan), previously, edge AI mainly involved uploading large amounts of data to the cloud for processing and analysis. In contrast, edge AI shifts the focus of data processing to local devices, leveraging the advantages of edge computing for real-time feedback and intelligent decision-making. This approach can … Read more
Edge refers to the edge of a network, relative to data centers or cloud computing, meaning the edge of a network (e.g., the Internet). Compared to large models (e.g., ChatGPT), Edge AI can run on edge devices, and even on small sensors. The development of Edge AI benefits from the continuous enhancement of computing power … Read more
Source | Zhongzi Network Introduction The field of the Internet of Things (IoT) is filled with acronyms, from LPWAN to MQTT to the acronym IoT itself. There are many branches in the application fields of IoT, one of which is IIoT, representing the Industrial Internet of Things. 01 IoT vs Industrial IoT The Internet of … Read more
This article surveys the differences in various anomaly detection methods and their applicability to the security protection of the Industrial Internet of Things (IIoT). It analyzes papers published from 2000 to 2021 on network anomaly detection, summarizes the security threats faced by IIoT, and categorizes 9 types of network anomaly detection methods and their characteristics. … Read more
Click Blue Text Reply 「1」 to receive six industry gift packages (Big Data, Cloud Computing, Artificial Intelligence, Blockchain…) ——– Author / Song Pengfei · Editor / Jenny Robin Source / Broadband Capital The Japanese Ministry of Internal Affairs and Communications recently released a popular short film “Connecting the World After 5G”. In just over three … Read more
Edge computing has become an important trend in the Internet of Things .The Gartner Group identified edge computing as one of the major technology trends of 2019. Companies implementing IoT solutions are seeing the real benefits of processing data closer to the “things” at the edge before it is sent to the cloud. A recent … Read more
ZEHPYR-7B is one of the next-generation large language models (LLMs) that has gained significant popularity in the AI community. The model was created by Hugging Face and is essentially a fine-tuned version of Mistral-7B trained on public datasets, optimized through knowledge distillation techniques. This model has achieved incredible results, surpassing many larger models across various … Read more
Source: Deephub Imba This article is about 4000 words long, and it is recommended to read in 6 minutes. In this article, we will explain the basic concepts of LoRA itself and then introduce some variants that improve the functionality of LoRA in different ways. LoRA can be said to be a major breakthrough for … Read more
Excerpt from lightning.ai Author: Sebastian Raschka Compiled by Machine Heart Editor: Chen Ping The author states: Among various effective LLM fine-tuning methods, LoRA remains his top choice. LoRA (Low-Rank Adaptation) is a popular technique for fine-tuning LLMs (Large Language Models) that was first proposed by researchers from Microsoft in the paper “LORA: LOW-RANK ADAPTATION OF … Read more
©PaperWeekly Original · Author | Su Jianlin Unit | Dark Side of the Moon Research Direction | NLP, Neural Networks LoRA (Low-Rank Adaptation) is one of the parameter-efficient fine-tuning methods for current LLMs. Previously, we briefly discussed it in “LoRA from a Gradient Perspective: Introduction, Analysis, Speculation, and Promotion”. In this article, we will learn … Read more