1️⃣ Introduction: Understanding CodeBERT in One Sentence Translating “The injection molding machine is broken” into “First replace the thermocouple, then set the PID” using an AI large model. Dimension 2025 Industrial Practice Parameter Count 125 M (LoRA fine-tuning is sufficient) Corpus +500,000 enterprise work orders Typical ROI Halved downtime 2️⃣ Functional Architecture: 2-1 Functional Matrix … Read more
✅ Author’s Profile: A Matlab simulation developer passionate about research, skilled in data processing, modeling simulation, program design, obtaining complete code, reproducing papers, and scientific simulation. 🍎 Previous reviews, follow the personal homepage:Matlab Research Studio 🍊 Personal motto: Investigate to gain knowledge, complete Matlab code and simulation consultation available via private message. 🔥 Content Introduction … Read more
Click the blue text to follow us Introduction: With the development of artificial intelligence technology, AI Agents have gradually become the primary means for humans to interact with large models. AI Agents can perform tasks, solve problems, and provide personalized services. Their key components include planning, memory, and tool use, making interactions more efficient and … Read more
▲ Click the blue text aboveto follow our public account, and reply with“Feilian Cloud” to obtain【Data Download Method】 An AI Agent refers to an intelligent entity capable of proactive thinking and action, working in a human-like manner. It utilizes large models to “understand” user needs, actively “plan” to achieve goals, employs various “tools” to complete … Read more
This article is reprinted from the public account: AI Algorithm Chips and Systems. This article is for academic/technical sharing only. If there is any infringement, please contact us to delete the article. 01 Abstract This article provides an in-depth analysis of the neural processing unit (NPU) integrated into Intel’s Meteor Lake mobile processor. The NPU, … Read more
Genetic algorithm optimization for flexible job shop scheduling based on MATLAB. First, determine the types of workpieces and the number of machines, along with the time required for each workpiece and process sequence corresponding to the machines. This addresses two main issues in the scheduling process: which workpiece to schedule and which machine to assign. … Read more
Hello everyone, today I would like to introduce an article published by our research group in the journal Coordination Chemistry Reviews titled “Cross-responsive fluorescence sensor arrays combined with machine learning for dietherapeutic phytochemicals recognition in food-medicine homology“. This article systematically summarizes the latest advancements and challenges in the rapid identification of dietherapeutic phytochemicals (Dietherapeutic phytochemicals,DTP) … Read more
In recent years, advancements in robotics have accelerated the development of intelligent manufacturing systems. Among these, object recognition based on visual perception plays a crucial role. However, due to the optical transparency of liquids and the similarity in their tactile properties, the identification and classification of liquids in containers remain a field that has not … Read more
Sharing Cutting-Edge Research on TinyML 01 Definition TinyML, or “Tiny Machine Learning,” refers to the technology, tools, and methodologies for running machine learning applications on ultra-low-power microcontrollers (MCUs) and other small computing devices. The core of TinyML is to compress and optimize trained machine learning models to fit the limited memory (typically KB-level SRAM, MB-level … Read more
Abstract This article provides an in-depth analysis of the neural processing unit (NPU) integrated into Intel’s Meteor Lake mobile processor. Codenamed “NPU 3720,” this NPU is based on Movidius technology acquired by Intel and is designed to handle machine learning workloads with higher energy efficiency. The article discusses its high-level architecture, neural compute engine design, … Read more