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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 25, 2026 · Cloud Native

Evolution of Agent Infrastructure: Engineering Insights from Tencent Cloud Agent Runtime

The article analyzes how agents transition from demo to production, revealing that beyond model capabilities, stability, elasticity, security, and governance become critical, and explains the engineering challenges and solutions—including session management, state persistence, scheduling mismatches, sandbox isolation, and open‑source strategies—that underpin Tencent Cloud's Agent Runtime.

Agent RuntimeCloud NativeKubernetes
0 likes · 26 min read
Evolution of Agent Infrastructure: Engineering Insights from Tencent Cloud Agent Runtime
DataFunSummit
DataFunSummit
Jul 25, 2026 · Artificial Intelligence

The Hidden Flaws of AI‑Driven “Lights‑Off” Software Factories

While AI‑powered coding agents promise a lights‑off software factory where developers never read code, this article reveals the growing maintainability nightmare, benchmark shortcomings, and why current large‑language models still fail to produce good design, urging a return to planning and human oversight.

AI codingSoftware Factoryagentic development
0 likes · 13 min read
The Hidden Flaws of AI‑Driven “Lights‑Off” Software Factories
DataFunSummit
DataFunSummit
Jul 24, 2026 · Artificial Intelligence

Why Harness Engineering Fails: Hidden Defects of AI‑Powered Code Factories

The article analyzes the rise of “lights‑off” software factories that rely on AI agents to generate, review, and fix code, exposing their maintainability nightmare, the inability of current models to learn good design, the limits of existing benchmarks, and proposes a pragmatic four‑step workflow that re‑introduces human planning and oversight.

AI codingSoftware Factoryagentic development
0 likes · 12 min read
Why Harness Engineering Fails: Hidden Defects of AI‑Powered Code Factories
DataFunSummit
DataFunSummit
Jul 24, 2026 · Industry Insights

Why High-Quality Data Is the New Bottleneck in Large Model Competition

In a four‑hour investor briefing, DeepSeek founder Liang Wenfeng explains that the real competitive edge for large language models now lies in the ability to continuously produce high‑quality training signals, a capability limited by time rather than capital.

AI industryDeepSeekHigh-Quality Data
0 likes · 10 min read
Why High-Quality Data Is the New Bottleneck in Large Model Competition
DataFunSummit
DataFunSummit
Jul 23, 2026 · Artificial Intelligence

How Agentic Architectures Power Next‑Gen Recommendation and Search Systems

The article reviews cutting‑edge AI search and recommendation techniques—including Alibaba Cloud's Agentic RAG, Huawei Noah's LLM‑enhanced recommendation evolution, and Baidu's generative ranking model GRAB—detailing their architectures, multi‑modal retrieval strategies, performance gains, and real‑world deployment insights.

AI SearchAgentic RAGAlibaba Cloud
0 likes · 6 min read
How Agentic Architectures Power Next‑Gen Recommendation and Search Systems
DataFunSummit
DataFunSummit
Jul 22, 2026 · Artificial Intelligence

Why Knowledge Bases Alone Can’t Empower AI Agents: The Need for Actionable Experience

Large language models may know a great deal, yet they still stumble on concrete tasks because knowledge must be transformed into actionable, context‑aware skills; this article analyses how skill representation, model‑specific cognition, and continuous practice reshape knowledge engineering for self‑evolving AI agents.

AI AgentsExperience LearningKnowledge Engineering
0 likes · 16 min read
Why Knowledge Bases Alone Can’t Empower AI Agents: The Need for Actionable Experience
DataFunSummit
DataFunSummit
Jul 22, 2026 · Artificial Intelligence

Designing Next‑Generation Recommendation and Search Systems with Agentic Architectures

The article analyzes how agentic architectures, large language models, and generative ranking techniques are applied to overcome high‑concurrency, multimodal, and multi‑hop challenges in modern recommendation and search systems, showcasing concrete designs, performance gains, and real‑world deployments from Alibaba Cloud, Huawei Noah, and Baidu.

AI SearchAgentic RAGGenerative Ranking
0 likes · 5 min read
Designing Next‑Generation Recommendation and Search Systems with Agentic Architectures
DataFunSummit
DataFunSummit
Jul 22, 2026 · Big Data

How Tencent Redefines Data Architecture for the Agent Era

With agents moving from Q&A to execution, traditional architectures expose three critical flaws—data stored in lakes, models in the cloud, and split scheduling—forcing petabyte‑scale data movement; Tencent Cloud’s big data AI DLC resolves this by running Spark and Ray side‑by‑side on the same lake, enabling closed‑loop processing and automatic trajectory capture.

AIAgentBig Data
0 likes · 2 min read
How Tencent Redefines Data Architecture for the Agent Era
DataFunSummit
DataFunSummit
Jul 21, 2026 · Industry Insights

When Models Get Cheaper, Who’s Making Money?

The article argues that as large‑language‑model costs plunge, profit shifts from model providers to companies that prepare, govern, and route data for AI, citing Databricks’ $3 billion raise, Anthropic’s data‑engineered accuracy jump, and the emerging European compliance market.

AIAI GovernanceBusiness Models
0 likes · 12 min read
When Models Get Cheaper, Who’s Making Money?
DataFunSummit
DataFunSummit
Jul 21, 2026 · Industry Insights

Why Enterprises Still Hesitate to Deploy Production‑Ready AI Agents Despite Palantir’s New Stack

The article analyzes Palantir’s Agent Stack—Orchestrator, observability, optimization, and Ontology—explaining how moving AI agents from chat interfaces to long‑running production tasks raises challenges of state management, fault handling, permission control, and trust, shifting the focus from model capability to enterprise‑grade infrastructure.

AI AgentsEnterprise AIOntology
0 likes · 14 min read
Why Enterprises Still Hesitate to Deploy Production‑Ready AI Agents Despite Palantir’s New Stack