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DataFunSummit

Official account of the DataFun community, dedicated to sharing big data and AI industry summit news and speaker talks, with regular downloadable resource packs.

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Recent Articles

Latest from DataFunSummit

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DataFunSummit
DataFunSummit
Jul 15, 2026 · Artificial Intelligence

From Prompt Engineering to Loop Engineering: How AI Agent Architectures Are Redefining Software Development

The 2026 AI Engineer World Expo revealed that as AI now writes code, calls tools, and self‑optimizes, engineers are shifting from writing code to designing sustainable loops, with new knowledge layers, software‑factory concepts, model routing, security controls, and open‑source advances reshaping the discipline.

AI AgentsLoop EngineeringSoftware Factory
0 likes · 22 min read
From Prompt Engineering to Loop Engineering: How AI Agent Architectures Are Redefining Software Development
DataFunSummit
DataFunSummit
Jul 15, 2026 · Artificial Intelligence

How Protocols, Constraints, Self‑Evolution, and Cost Shape Real‑World AI Agents

The live discussion reveals why stronger LLMs can hide subtle errors, why moving from single‑point chatbots to multi‑agent harnesses requires a cognitive shift, and how enterprises must enforce protocols, permissions, and structured evaluation to safely and cost‑effectively deploy AI agents at scale.

AI AgentsEnterprise AIMulti-Agent Collaboration
0 likes · 17 min read
How Protocols, Constraints, Self‑Evolution, and Cost Shape Real‑World AI Agents
DataFunSummit
DataFunSummit
Jul 14, 2026 · Artificial Intelligence

Memory‑Guided Hard Data Augmentation: Turning Model Errors into Targeted Multimodal NER Improvements

The paper proposes Memory‑Guided Hard Data Augmentation (MGHDA), a closed‑loop pipeline that diagnoses model‑specific hard instances in multimodal named entity recognition, abstracts their error patterns into a Memory Tree, and generates targeted augmentation samples, achieving consistent F1 gains across several backbones while highlighting cost and scalability trade‑offs.

AIData AugmentationLLM
0 likes · 15 min read
Memory‑Guided Hard Data Augmentation: Turning Model Errors into Targeted Multimodal NER Improvements
DataFunSummit
DataFunSummit
Jul 12, 2026 · Artificial Intelligence

Turning AI Search Agents into Your Attribution Analysis Sidekick

This article explains how JD's team built an attribution‑analysis Agent that maps analysts' investigative steps into a plan‑and‑action loop, uses parallel search with pruning, script constraints, and dynamic structured memory to make data‑driven root‑cause analysis faster, more reliable, and interactive.

AI agentAttribution AnalysisData Analytics
0 likes · 13 min read
Turning AI Search Agents into Your Attribution Analysis Sidekick
DataFunSummit
DataFunSummit
Jul 11, 2026 · Artificial Intelligence

Why Diversity Beats Data Scale: Insights from MiniMax & Fudan’s DIVE Paper

The DIVE study shows that expanding the diversity of tool pools and task structures, rather than merely increasing the amount of homogeneous training data, dramatically improves LLM agents' ability to generalize to unseen tools, as demonstrated by a 12k‑vs‑48k experiment and reinforced by a four‑stage synthesis pipeline and RL fine‑tuning.

AI AgentsDIVELLM training
0 likes · 14 min read
Why Diversity Beats Data Scale: Insights from MiniMax & Fudan’s DIVE Paper
DataFunSummit
DataFunSummit
Jul 11, 2026 · Artificial Intelligence

Agent Architecture and Practice: Building the Next‑Generation Recommendation and Search Systems

The article analyzes the technical evolution of AI‑driven recommendation and search, covering Alibaba Cloud's Agentic RAG architecture, Huawei Noah's LLM‑enhanced recommendation pipeline, and Baidu's generative ranking model GRAB, while presenting design choices, performance metrics, and real‑world deployment results.

AI AgentsAgentic RAGGenerative Ranking
0 likes · 5 min read
Agent Architecture and Practice: Building the Next‑Generation Recommendation and Search Systems
DataFunSummit
DataFunSummit
Jul 11, 2026 · Artificial Intelligence

Tencent CodeBuddy’s AI DLC Slashes Training Time and Costs with a Unified Spark‑Ray Service

The article explains how Tencent CodeBuddy’s AI DLC platform unifies Spark batch processing and Ray training to eliminate data movement, turning agent trajectories into reusable training fuel, which reduces monthly‑level training cycles to weekly, enables in‑place computation on billions of features, and cuts operational costs by 60%.

AI DLCData LakeGPU utilization
0 likes · 2 min read
Tencent CodeBuddy’s AI DLC Slashes Training Time and Costs with a Unified Spark‑Ray Service
DataFunSummit
DataFunSummit
Jul 10, 2026 · Artificial Intelligence

UI-MOPD Enables Cross‑Platform GUI Agents to Retain Skills Without Forgetting

The article analyzes why GUI agents trained on both desktop (mouse‑click) and mobile (touch) interactions suffer from behavior collapse and catastrophic forgetting, introduces the UI‑MOPD framework that assigns platform‑specific teachers through on‑policy distillation, and shows an 8B model surpassing a 235B baseline on OSWorld and MobileWorld benchmarks while preserving general GUI understanding.

Cross-platformGUI agentsUI‑MOPD
0 likes · 8 min read
UI-MOPD Enables Cross‑Platform GUI Agents to Retain Skills Without Forgetting
DataFunSummit
DataFunSummit
Jul 9, 2026 · Artificial Intelligence

Token-Level Credit Assignment Outperforms Broadcast GRPO in LLM Math Reasoning

The paper identifies the broadcast‑style credit assignment of GRPO as a bottleneck for RL‑LLM math reasoning, proposes the Outcome‑Grounded Advantage Reshaping (OAR) framework with token‑importance estimation, and demonstrates that its two variants, OAR‑P and OAR‑G, consistently improve accuracy, training efficiency, and stability across multiple math benchmarks.

Credit AssignmentGRPOLLM
0 likes · 15 min read
Token-Level Credit Assignment Outperforms Broadcast GRPO in LLM Math Reasoning