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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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DataFunSummit
DataFunSummit
Apr 18, 2026 · Industry Insights

Why Palantir’s Ontology Beats Traditional Data Models – Insights from Industry Leaders

A closed‑door forum gathered experts from academia and leading Chinese tech firms to dissect Palantir’s ontology‑driven approach, comparing it with conventional data modeling, exploring AI integration, and highlighting the managerial and technical challenges that determine its success in enterprise environments.

Industry InsightsPalantirdata governance
0 likes · 27 min read
Why Palantir’s Ontology Beats Traditional Data Models – Insights from Industry Leaders
DataFunSummit
DataFunSummit
Apr 17, 2026 · Artificial Intelligence

Why RAG Projects Fail: Real‑World Pitfalls and Proven Solutions

This article dissects the hype‑versus‑reality gap of Retrieval‑Augmented Generation in enterprises, exposing low recall, hallucinations, and cost overruns, then offers a systematic diagnosis, hybrid search, reranking, security controls, and advanced GraphRAG and Agentic RAG strategies to achieve reliable production deployments.

Best PracticesLLMRAG
0 likes · 17 min read
Why RAG Projects Fail: Real‑World Pitfalls and Proven Solutions
DataFunSummit
DataFunSummit
Apr 17, 2026 · Artificial Intelligence

From Manual Agents to Self‑Improving AI: My OpenClaw vs Hermes Experiment

A senior Google Cloud AI product manager shares a hands‑on study comparing OpenClaw and the open‑source Hermes agent, revealing how a disciplined prompt‑engineering feedback loop can turn static agents into self‑improving systems while highlighting ownership, back‑tracking, and practical deployment considerations.

AI AgentsHermesOpenClaw
0 likes · 7 min read
From Manual Agents to Self‑Improving AI: My OpenClaw vs Hermes Experiment
DataFunSummit
DataFunSummit
Apr 16, 2026 · Industry Insights

Why Palantir’s Ontology Is Redefining Enterprise AI Platforms

Palantir’s explosive Q4 revenue growth, its unique Ontology‑based operating model, high‑profile enterprise case studies, deep AI integration, and the resulting lock‑in challenges together illustrate how the company is reshaping the boundaries of enterprise software and why its success goes far beyond a simple AI hype.

Palantirmarket analysisontology
0 likes · 9 min read
Why Palantir’s Ontology Is Redefining Enterprise AI Platforms
DataFunSummit
DataFunSummit
Apr 15, 2026 · Industry Insights

Why Traditional Data Platforms Fail and How Ontology Drives Triple‑Digit ROI

The article analyzes costly data‑platform failures—such as a $40 million payroll system in San Francisco schools and a collapsed Healthcare.gov launch—identifies the root cause as ineffective data middle platforms, and demonstrates how Palantir’s ontology‑based three‑layer architecture (semantic, dynamics, decision) can turn data into actionable insights, delivering triple‑digit ROI for enterprises like BP, Novartis, and General Mills.

Big DataData PlatformIndustry Insights
0 likes · 5 min read
Why Traditional Data Platforms Fail and How Ontology Drives Triple‑Digit ROI
DataFunSummit
DataFunSummit
Apr 15, 2026 · Artificial Intelligence

How Relax Powers Scalable Multi‑Modal RL Training with Full Asynchrony

Relax, an open‑source RL training engine built on Megatron‑LM and SGLang, tackles data heterogeneity, system fragility, and role coupling by using a service‑oriented fault‑tolerant architecture, asynchronous pipelines, and multimodal‑native support, achieving up to 76% end‑to‑end speedup over veRL.

AI infrastructureDistributed SystemsMultimodal
0 likes · 11 min read
How Relax Powers Scalable Multi‑Modal RL Training with Full Asynchrony
DataFunSummit
DataFunSummit
Apr 13, 2026 · Industry Insights

How Kuaishou’s Life Services Data Center Boosted Warehouse Efficiency with AI Agents

In a rapidly growing data‑driven environment, Kuaishou’s Life Services Data Center tackled exploding demand and limited manpower by replacing traditional siloed data‑warehouse practices with AI‑driven intelligent review, DQC, and chatbot solutions, achieving up to 11.34% productivity gains and dramatically improving data quality.

AIData WarehouseKnowledge Base
0 likes · 16 min read
How Kuaishou’s Life Services Data Center Boosted Warehouse Efficiency with AI Agents
DataFunSummit
DataFunSummit
Apr 10, 2026 · Artificial Intelligence

How Can AI Agents Truly Remember? A Deep Dive into Long‑Term Memory Engineering

This article examines the shortcomings of current AI assistants, outlines the ideal of long‑term memory engineering, reviews mainstream industry solutions such as hard‑context models and Retrieval‑Augmented Generation, proposes a four‑layer memory loop architecture, and looks ahead to online learning and collective intelligence for future agents.

AIAgentFoundation Model
0 likes · 15 min read
How Can AI Agents Truly Remember? A Deep Dive into Long‑Term Memory Engineering