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Data Thinking Notes
Data Thinking Notes
Jun 4, 2025 · Artificial Intelligence

How DeepSeek AI Model is Revolutionizing China’s State Enterprises – Over 100 Deployment Cases

The DeepSeek large language model has been extensively deployed across more than 100 central and local Chinese state‑owned enterprises, spanning sectors such as energy, manufacturing, transportation, finance, telecommunications, construction, and public services, driving intelligent transformation through applications like smart scheduling, risk assessment, intelligent customer service, and AI‑enhanced office automation.

AI deploymentDeepSeekindustrial AI
0 likes · 38 min read
How DeepSeek AI Model is Revolutionizing China’s State Enterprises – Over 100 Deployment Cases
DataFunSummit
DataFunSummit
Dec 26, 2024 · Artificial Intelligence

Applying Artificial Intelligence in Automotive Manufacturing: Concepts, Use Cases, and Implementation Insights

This article explores how artificial intelligence concepts translate into practical applications within automotive manufacturing, covering AI fundamentals, its role across vehicle production workshops, data‑algorithm‑compute triad, model lifecycle management, and strategies for decomposing large scenarios into actionable small‑scale AI solutions.

AIAutomotive Manufacturingcomputer vision
0 likes · 22 min read
Applying Artificial Intelligence in Automotive Manufacturing: Concepts, Use Cases, and Implementation Insights
DataFunSummit
DataFunSummit
Aug 23, 2024 · Artificial Intelligence

Applying Large Language Models to Automotive Industrialization: Practices and Experiences

This presentation outlines the development of ChatGPT, the underlying principles of large language models, and how they empower new industrialization in automotive manufacturing, detailing practical implementations, agent architectures, data and model closed loops, and case studies such as intelligent inspection and G8D agents.

AutomotiveChatGPTData Loop
0 likes · 13 min read
Applying Large Language Models to Automotive Industrialization: Practices and Experiences
DataFunTalk
DataFunTalk
Apr 11, 2024 · Artificial Intelligence

Ant Group’s Time Series AI Practices: AntFlux Engine and Real‑World Applications

Ant Group shares its time‑series AI practice, detailing the AntFlux intelligent engine, the evolution of statistical and deep learning models, large‑scale time‑series platforms, and real‑world applications across finance, cloud, and green computing, illustrating challenges, innovations, and future directions.

AntFluxTime Series AIforecasting
0 likes · 19 min read
Ant Group’s Time Series AI Practices: AntFlux Engine and Real‑World Applications
DataFunTalk
DataFunTalk
Feb 29, 2024 · Artificial Intelligence

Applying Large Language Models to Automotive Industrialization: Practices and Insights

This presentation outlines the development of ChatGPT, the underlying principles of large language models, and how they empower new industrialization in the automotive sector, detailing practical implementations, agent architectures, data and model closed‑loops, and case studies such as intelligent quality inspection and G8D agents.

AI agentsChatGPTindustrial AI
0 likes · 14 min read
Applying Large Language Models to Automotive Industrialization: Practices and Insights
DataFunSummit
DataFunSummit
Jan 23, 2024 · Artificial Intelligence

Meta-Learning and Cross-Domain Recommendation: Industrial Practices at Tencent TRS

This article presents Tencent TRS's industrial practice of applying meta‑learning and cross‑domain recommendation to address personalization challenges, detailing problem definitions, solution architectures, algorithmic choices such as MAML, deployment strategies, and the cost‑effective outcomes achieved across multiple scenarios.

Cross-DomainMAMLRecommendation systems
0 likes · 16 min read
Meta-Learning and Cross-Domain Recommendation: Industrial Practices at Tencent TRS
DataFunSummit
DataFunSummit
Jan 13, 2024 · Artificial Intelligence

Large Model Applications in Automotive Industrialization: Practices, Architecture, and Case Studies

This presentation explores the development of ChatGPT, the underlying principles of large language models, their role in enabling new industrialization, detailed NIO automotive AI platform architecture, data‑model‑agent closed‑loops, intelligent inspection solutions, and practical case studies such as G8D Agents, providing a comprehensive view of large‑model deployment in the automotive sector.

AI agentsAutomotivedata loops
0 likes · 13 min read
Large Model Applications in Automotive Industrialization: Practices, Architecture, and Case Studies
DataFunSummit
DataFunSummit
Sep 24, 2023 · Artificial Intelligence

Decision Optimization Algorithms for Port Terminal Scheduling: Case Study, Challenges, and Solutions

This article presents a comprehensive overview of decision optimization algorithms applied to port terminal equipment coordination, detailing a real-world case study, the iECS architecture, implementation challenges across data, computation, and operations, and discusses future trends and best practices for industry deployment.

AI algorithmsdecision optimizationindustrial AI
0 likes · 19 min read
Decision Optimization Algorithms for Port Terminal Scheduling: Case Study, Challenges, and Solutions
AntTech
AntTech
Sep 7, 2023 · Artificial Intelligence

Ant Group Open-sources Ant Graph Learning (AGL), the First General Industrial Graph Learning System

Ant Group announced the open-source release of Ant Graph Learning (AGL), a pioneering industrial‑grade graph learning platform that supports trillion‑scale graph data, offers ready‑to‑use algorithms, and aims to lower the barrier for large‑scale graph AI applications across industries.

Ant Groupgraph learningindustrial AI
0 likes · 4 min read
Ant Group Open-sources Ant Graph Learning (AGL), the First General Industrial Graph Learning System
DataFunTalk
DataFunTalk
Jul 6, 2023 · Artificial Intelligence

Industrial Practice of Meta‑Learning and Cross‑Domain Recommendation in Tencent TRS

This article presents Tencent TRS's industrial deployment of meta‑learning and cross‑domain recommendation, detailing problem definitions, solution architectures, challenges of industrialization, and practical implementations that achieve personalized modeling and cost‑effective multi‑scene recommendation across various online services.

Cross-DomainMAMLRecommendation systems
0 likes · 18 min read
Industrial Practice of Meta‑Learning and Cross‑Domain Recommendation in Tencent TRS
DataFunSummit
DataFunSummit
Mar 5, 2023 · Artificial Intelligence

Data‑Driven Decision Optimization: Challenges and Advances in Offline Reinforcement Learning

This article reviews the practical challenges of applying data‑driven decision optimization in real‑world systems, explains the fundamentals of offline reinforcement learning, discusses recent algorithmic innovations such as policy‑constraint methods and the DOGE framework, and presents industrial case studies including power‑plant control and mixed offline‑online RL approaches.

Offline Reinforcement Learningdata-driven decisionindustrial AI
0 likes · 27 min read
Data‑Driven Decision Optimization: Challenges and Advances in Offline Reinforcement Learning
AntTech
AntTech
Sep 28, 2022 · Artificial Intelligence

Advancing Trustworthy AI to Industrial-Scale Applications: Insights from Ant Group

The article outlines Ant Group's comprehensive approach to promoting trustworthy AI in large‑scale industrial settings, detailing the four core pillars of robustness, explainability, privacy protection, and fairness, and describing practical methodologies, open platforms, and ecosystem collaborations that drive responsible AI deployment.

AI safetyexplainabilityfairness
0 likes · 13 min read
Advancing Trustworthy AI to Industrial-Scale Applications: Insights from Ant Group
DataFunTalk
DataFunTalk
Apr 30, 2022 · Artificial Intelligence

Insights into BIDMach: An Unusual Machine Learning Framework and Thoughts on Building Industrial‑Grade ML Systems

The article introduces BIDMach, a compact Scala‑based machine‑learning framework built with JNI‑driven CUDA/MKL, explains its three‑layer architecture, and discusses broader considerations for designing usable, high‑performance, and extensible industrial AI frameworks, emphasizing co‑design, algorithm‑framework co‑evolution, and ecosystem factors.

BIDMachCo-designMachine Learning
0 likes · 8 min read
Insights into BIDMach: An Unusual Machine Learning Framework and Thoughts on Building Industrial‑Grade ML Systems
Baidu Geek Talk
Baidu Geek Talk
Mar 14, 2022 · Artificial Intelligence

Zero-Threshold AI Development: Empowering SMEs with Intelligent Transformation

The article explains how China’s policy‑driven push for specialized, innovative SMEs is being accelerated by Baidu’s zero‑threshold AI platform EasyDL, which lets small firms like AiBao Flower Accessories and Shanghai ZheYuan Technology build high‑accuracy inspection systems without deep technical expertise, lowering costs and boosting industrial intelligence.

AI transformationEasyDLPaddlePaddle
0 likes · 9 min read
Zero-Threshold AI Development: Empowering SMEs with Intelligent Transformation
Baidu Geek Talk
Baidu Geek Talk
Mar 9, 2022 · Artificial Intelligence

Communication Tower Recognition Using PaddlePaddle: An Industrial AI Practice

The article describes an industrial AI system that uses PaddlePaddle’s PP‑PicoDet model, enhanced with COCO pre‑training and quantization, to accurately recognize communication towers in diverse outdoor conditions, achieving 94.5% mAP at 78 ms inference and supporting edge deployment via PaddleLite and ONNX.

PP-PicoDetPaddlePaddlecommunication tower
0 likes · 6 min read
Communication Tower Recognition Using PaddlePaddle: An Industrial AI Practice
Baidu Geek Talk
Baidu Geek Talk
Mar 7, 2022 · Artificial Intelligence

Industrial AI Applications: Energy Prediction, Quality Inspection, and Safety Management

The article outlines how Paddle EasyDL’s industrial AI courses teach companies to use predictive analytics for energy optimization, machine‑vision for bearing quality inspection, and continuous AI‑driven safety monitoring, reducing manual effort, cutting costs, and supporting digital transformation toward smarter, greener manufacturing.

Machine Visioncarbon reductiondigital-transformation
0 likes · 6 min read
Industrial AI Applications: Energy Prediction, Quality Inspection, and Safety Management
DataFunTalk
DataFunTalk
Nov 19, 2021 · Artificial Intelligence

Industrial Intelligence: Current Status, Talent, Challenges, and AI Application in Manufacturing

This article examines industrial intelligence from the perspectives of flow and fusion, detailing its current state, talent needs, pain points, AI development processes, edge‑cloud architecture, and key characteristics such as timeliness, reliability, explainability, and applicability in manufacturing.

AI WorkflowTalentdata science
0 likes · 22 min read
Industrial Intelligence: Current Status, Talent, Challenges, and AI Application in Manufacturing
DataFunSummit
DataFunSummit
Nov 16, 2021 · Artificial Intelligence

Industrial Intelligence: Current Status, Talent Requirements, Challenges, and AI Application Process

This article examines the state of industrial AI, discussing data and model challenges, the multidisciplinary talent needed, the DIKW framework, typical AI workflows, edge‑cloud architecture, real‑time processing tools, time‑series storage, service design patterns, and practical recommendations for deploying AI in manufacturing.

DIKWMachine Learningdata science
0 likes · 24 min read
Industrial Intelligence: Current Status, Talent Requirements, Challenges, and AI Application Process
DataFunTalk
DataFunTalk
Jun 2, 2021 · Artificial Intelligence

Industrial-Scale Graph Learning for JD Advertising: 9N GRAPH End‑to‑End Solution and BVSHG Model

This article introduces JD.com's 9N GRAPH industrialization framework for large‑scale graph algorithms in advertising, covering the challenges of e‑commerce recommendation, the end‑to‑end solution architecture, the BVSHG multi‑behavior heterogeneous GNN model, training pipelines, and observed business impact.

BVSHGGraph Neural NetworksJD.com
0 likes · 17 min read
Industrial-Scale Graph Learning for JD Advertising: 9N GRAPH End‑to‑End Solution and BVSHG Model
DataFunTalk
DataFunTalk
Dec 17, 2020 · Artificial Intelligence

Context‑Aware Re‑ranking in Industrial Recommendation Systems: Design and Practice of a List Retrieval System

The article presents a comprehensive study of re‑ranking in large‑scale industrial recommendation pipelines, identifies four key challenges—context awareness, permutation specificity, computational complexity, and business constraints—and proposes a two‑stage List Retrieval System that combines fast sequence search and a generative re‑ranking network with a deep context‑wise model, achieving significant online gains across multiple Taobao feed scenarios.

Recommendation systemscontext-awaredeep learning
0 likes · 28 min read
Context‑Aware Re‑ranking in Industrial Recommendation Systems: Design and Practice of a List Retrieval System