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JD Cloud Developers
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JD Cloud Developers

JD Cloud Developers (Developer of JD Technology) is a JD Technology Group platform offering technical sharing and communication for AI, cloud computing, IoT and related developers. It publishes JD product technical information, industry content, and tech event news. Embrace technology and partner with developers to envision the future.

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Recent Articles

Latest from JD Cloud Developers

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JD Cloud Developers
JD Cloud Developers
Mar 3, 2026 · Mobile Development

How to Integrate AI into Mobile Apps Without Sacrificing User Experience

This article examines the practical challenges of adding AI features to mobile clients, highlighting device fragmentation, performance trade‑offs, user pain points, and a layered approach that balances lightweight models, graceful degradation, and edge‑cloud collaboration to keep the experience smooth for the majority of users.

AI integrationAR gesturesMobile Development
0 likes · 15 min read
How to Integrate AI into Mobile Apps Without Sacrificing User Experience
JD Cloud Developers
JD Cloud Developers
Mar 2, 2026 · Artificial Intelligence

How AI Agents Are Revolutionizing Insurance: Methodology, Economics, and Technical Blueprint

This comprehensive guide explains how AI agents can be selected, designed, and deployed across the insurance supply chain, detailing their economic impact, technical architecture—including domain‑specific large models, knowledge bases, planning strategies, and reinforcement‑learning loops—and outlines future roadmaps for pricing, fulfillment, and risk‑control automation.

AI AgentArtificial IntelligenceInsurance
0 likes · 43 min read
How AI Agents Are Revolutionizing Insurance: Methodology, Economics, and Technical Blueprint
JD Cloud Developers
JD Cloud Developers
Feb 4, 2026 · Artificial Intelligence

How Deep Research Transforms LLMs into Autonomous AI Researchers

This article examines Deep Research, an AI system that adds autonomous planning and deep reasoning to large language models, enabling them to browse the web, perform long‑chain reasoning, and generate professional, citation‑rich reports for complex tasks such as industry trend analysis and technical competitive research.

AI researchAutonomous AgentsLLM
0 likes · 22 min read
How Deep Research Transforms LLMs into Autonomous AI Researchers
JD Cloud Developers
JD Cloud Developers
Jan 30, 2026 · Artificial Intelligence

Scaling Generative Recommendation: Inside JD’s 9N-LLM Multi‑Framework Training Engine

This article details JD Retail’s 9N-LLM unified training engine, which integrates TensorFlow and PyTorch across GPU and NPU hardware to tackle the massive data, model size, and reinforcement‑learning complexities of generative recommendation, offering concrete components, performance benchmarks, and future directions.

GPU/NPUPyTorchTensorFlow
0 likes · 26 min read
Scaling Generative Recommendation: Inside JD’s 9N-LLM Multi‑Framework Training Engine
JD Cloud Developers
JD Cloud Developers
Jan 16, 2026 · Information Security

How to Capture Network Packets Remotely with Wireshark and rpcapd

This guide explains why local packet captures can be impractical for real‑time analysis, then walks through installing rpcapd, configuring network requirements, launching the remote capture service, and setting up Wireshark to capture traffic from a distant machine.

Remote CaptureWinPcapWireshark
0 likes · 4 min read
How to Capture Network Packets Remotely with Wireshark and rpcapd
JD Cloud Developers
JD Cloud Developers
Jan 15, 2026 · Artificial Intelligence

Uni-Layout: Unifying Layout Generation with Human Feedback and Dynamic Alignment

Uni-Layout introduces a unified framework that combines a multimodal large language model‑based generator, a human‑like evaluator trained on the large Layout‑HF100k dataset, and a Dynamic Margin Preference Optimization (DMPO) method to align generation and evaluation, achieving state‑of‑the‑art results across diverse layout tasks.

DMPOHuman FeedbackMultimodal LLM
0 likes · 11 min read
Uni-Layout: Unifying Layout Generation with Human Feedback and Dynamic Alignment
JD Cloud Developers
JD Cloud Developers
Dec 12, 2025 · Big Data

Apache Hudi Core Concepts: Timeline, Indexes, Table Types & Queries

This article explains Apache Hudi’s core architecture, detailing the timeline mechanism, file layout, indexing strategies, the two main table types (Copy‑On‑Write and Merge‑On‑Read), and various query modes such as snapshot, time‑travel, read‑optimized and incremental queries.

Apache HudiData LakeTable Types
0 likes · 9 min read
Apache Hudi Core Concepts: Timeline, Indexes, Table Types & Queries