Machine Learning

Classic! Five AI-Themed Papers from Top Management Journals M&SOM

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Classic! Five AI-Themed Papers from Top Management Journals M&SOM

This issue focuses on five AI-themed papers from Manufacturing & Service Operations Management, revealing the multidimensional roles and dynamic challenges of AI technology in operational decision-making, service optimization, and ethical governance. A Framework for Decision Science Integration of Human-Machine Collaboration The integration of Machine Learning (ML) and Behavioral Science (BSci) provides complementary solutions to operational … Read more

Cutting-Edge Technology: Edge Computing Applications of ABB PLC for Intelligent On-Site Decision Making

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Cutting-Edge Technology: Edge Computing Applications of ABB PLC for Intelligent On-Site Decision Making

In the wave of Industry 4.0, the intelligence of equipment has become a key factor in the upgrade of the manufacturing industry. Today, let’s discuss the application of ABB PLC in the field of edge computing and see how to enable production lines to have the ability to “think autonomously”. What is Edge Computing? Think … Read more

Is C Language Being Phased Out?

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Is C Language Being Phased Out?

Source丨Reprinted with permission from OSC Open Source Community (ID: oschina2013) Author丨 Bai Kaishui Researchers from Carnegie Mellon University have launched an open-source automatic code generation model called PolyCoder, which has 27 billion parameters and is based on the GPT-2 architecture. It was trained on 249GB of code spanning 12 programming languages on a single machine. … Read more

Multi-Agent AI Systems: The Future of Intelligent Transformation in Enterprises

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Multi-Agent AI Systems: The Future of Intelligent Transformation in Enterprises

In today’s digital age, artificial intelligence (AI) is no longer just a tool; it is evolving into an intelligent workforce composed of numerous AI agents capable of autonomous planning, reasoning, and task execution. The rise of Multi-Agent Systems (MAS) is fundamentally changing the way businesses operate by enabling specialized AI agents to collaborate seamlessly, tackling … Read more

A Brief Overview of Meta’s Multi-Token Attention

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A Brief Overview of Meta's Multi-Token Attention

A Brief Overview of Meta’s Multi-Token Attention Meta’s new attention mechanism, MTA (Multi-Token Attention), enhances the model’s ability to perceive the locations of key information by incorporating convolution, allowing the model to attend to more information across tokens and attention heads during the attention computation phase. Traditional multi-head attention can split multiple heads to focus … Read more

Learn to Assemble Circuit Boards in 20 Minutes! Open Source SERL Framework Achieves 100% Success Rate with Three Times the Speed of Humans

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Learn to Assemble Circuit Boards in 20 Minutes! Open Source SERL Framework Achieves 100% Success Rate with Three Times the Speed of Humans

Machine Heart ColumnMachine Heart Editorial Team Now, robots have learned to perform precision control tasks in factories. In recent years, significant progress has been made in the field of robotic reinforcement learning technologies, such as quadrupedal walking, grasping, and dexterous manipulation. However, most of these advancements remain limited to laboratory demonstrations. The widespread application of … Read more

A Discussion on Embedded AI Technology | The Role of Feature Space on the Edge

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A Discussion on Embedded AI Technology | The Role of Feature Space on the Edge

Author: Andrew Su Yong As an AI technology expert at a globally renowned semiconductor company, I often receive inquiries from clients about machine learning algorithms when introducing Renesas’s AI hardware and AI tools, such as convolutional neural networks, K-means algorithms, or other algorithms. However, the reality is that during the process of building AI solutions, … Read more

TinyML Breakthrough: Deploying 1KB Models with MicroTVM on LoRa

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TinyML Breakthrough: Deploying 1KB Models with MicroTVM on LoRa

Hey, recently I’ve been tinkering with something fun — running machine learning on those tiny IoT devices! Seeing the number “1KB”, many people shake their heads: how is that possible? Indeed, a high-definition photo takes several MB, so where’s the magic that allows AI to fit into such a tiny space? Actually, TinyML is such … Read more

Using TinyML on Arduino IDE: The DeepC Framework Perfectly Adapts to Arduino

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Using TinyML on Arduino IDE: The DeepC Framework Perfectly Adapts to Arduino

In recent years, artificial intelligence technology has developed rapidly, but its powerful computing capabilities often rely on cloud servers. This poses a significant challenge for resource-constrained embedded devices. However, the rise of TinyML (Tiny Machine Learning) technology brings new hope: enabling resource-limited microcontrollers to run deep learning models! This article will take you into the … Read more

Why Multi-Agent Systems Fail? Two Interesting Experimental Conclusions on R1 Class Reasoning Model Training and Inference

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Why Multi-Agent Systems Fail? Two Interesting Experimental Conclusions on R1 Class Reasoning Model Training and Inference

Today is March 27, 2025, Thursday, Beijing, clear weather. Today, we continue to discuss the R1 reasoning model and the topic of multi-agents. There are three interesting experimental reports. They are: Enhancing LLM Reasoning by Scaling Multi-round Test-time Thinking (Think Twice), Length of Training Data is More Important than Difficulty for Training Reasoning Models, and … Read more