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DataFunSummit
DataFunSummit
May 19, 2026 · Databases

Building an AI‑Ready, Multi‑Modal Database Foundation for the Digital Intelligence Era

The talk outlines the AI era’s three major challenges for large language models and data (stability, 3V, resource limits), presents YashanDB’s original theory breakthroughs—including resource‑constrained computing, shared‑cluster performance and adaptive transaction scheduling—details a multi‑modal fusion architecture, introduces the KSA trustworthy knowledge‑engineering framework, and showcases real‑world deployments in smart‑city and energy domains.

AI-Ready Data PlatformEnergy IndustryKnowledge Engineering
0 likes · 16 min read
Building an AI‑Ready, Multi‑Modal Database Foundation for the Digital Intelligence Era
dbaplus Community
dbaplus Community
May 14, 2026 · Big Data

Building a ‘One‑Sentence Bank’: Big Data and AI Fusion for Small Banks

The article outlines the evolution of big data in banking, compares management models for heterogeneous data, describes the shift from data engineering to knowledge engineering, introduces LLMOps for high‑quality knowledge bases, and details how integrating AI and data can enable a “one‑sentence bank” that answers queries and executes tasks.

Artificial IntelligenceBankingBig Data
0 likes · 22 min read
Building a ‘One‑Sentence Bank’: Big Data and AI Fusion for Small Banks
DataFunSummit
DataFunSummit
Apr 22, 2026 · Artificial Intelligence

From Flawed RAG to Production‑Ready: Deep Dive into Scaling Retrieval‑Augmented Generation

This expert roundtable dissects why RAG often fails in production—low recall, hallucinations, cost overruns—and walks through concrete diagnostics, hybrid search designs, knowledge‑engineering tricks, GraphRAG and Agentic RAG advances, plus practical deployment, security, and cost‑optimization guidelines.

AI deploymentAgentic RAGHybrid Search
0 likes · 20 min read
From Flawed RAG to Production‑Ready: Deep Dive into Scaling Retrieval‑Augmented Generation
phodal
phodal
Apr 8, 2026 · R&D Management

How to Turn a Decade of Writing into a Reusable AI Skill

The author explains how, after ten years of writing, they analyzed their own articles, extracted evolving stylistic patterns, and engineered a modular, reusable writing skill—/phodal-writer/—that can be repeatedly loaded by AI to produce consistently structured, paced, and judgment‑rich content.

AI writingContent GenerationKnowledge Engineering
0 likes · 14 min read
How to Turn a Decade of Writing into a Reusable AI Skill
AI Architecture Hub
AI Architecture Hub
Apr 8, 2026 · Artificial Intelligence

Turn LLMs into Knowledge Engineers: Build a Self‑Growing Obsidian Wiki

This article explains how Andrej Karpathy's LLM‑plus‑Obsidian workflow transforms large language models into continuous knowledge engineers, detailing a three‑layer architecture, core operations, practical setup steps, and open‑source tools that enable a self‑maintaining, compounding personal wiki.

Knowledge EngineeringLLMObsidian
0 likes · 16 min read
Turn LLMs into Knowledge Engineers: Build a Self‑Growing Obsidian Wiki
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Mar 17, 2026 · Artificial Intelligence

Andrew Ng’s Agent Skills: From Basics to Must‑Know Essentials

This article breaks down Andrew Ng and Anthropic’s Agent Skills course, explaining how organized skill folders give general AI agents domain expertise, repeatable workflows, and new capabilities, while using portable, composable design and progressive disclosure to make agents reliable, scalable, and industrial‑grade.

AI AgentAgent SkillsArtificial Intelligence
0 likes · 9 min read
Andrew Ng’s Agent Skills: From Basics to Must‑Know Essentials
Efficient Ops
Efficient Ops
Jan 26, 2026 · Artificial Intelligence

Why AI Skills Will Redefine Agents Beyond MCP

This article explains how AI Skills serve as structured knowledge bases that complement, rather than replace, Model Context Protocols, enhance Retrieval‑Augmented Generation, and drive three major trends—standardized agent stacks, low‑code knowledge engineering, and the emergence of personal AI agents.

AI agentsAI ecosystemKnowledge Engineering
0 likes · 8 min read
Why AI Skills Will Redefine Agents Beyond MCP
AsiaInfo Technology: New Tech Exploration
AsiaInfo Technology: New Tech Exploration
Jan 16, 2026 · Artificial Intelligence

How to Evaluate Ontology Quality: Metrics, Methods, and Tools

This article surveys ontology quality evaluation by outlining key metrics such as consistency, completeness, and coverage, and reviewing five major assessment approaches—including corpus‑based, gold‑standard, metric‑driven, rule‑based, and application‑driven methods—while highlighting representative tools, open‑source implementations, and future research challenges.

Knowledge EngineeringLarge Language Modelsevaluation methods
0 likes · 20 min read
How to Evaluate Ontology Quality: Metrics, Methods, and Tools
AI2ML AI to Machine Learning
AI2ML AI to Machine Learning
Oct 24, 2025 · Artificial Intelligence

Beyond RAG: Three Emerging Knowledge‑Engineering Strategies (ICL, Online Learning, SLM)

The article outlines three post‑RAG knowledge‑engineering approaches—In‑Context Learning with dynamic few‑shot selection, Online Learning encompassing Meta‑Learning and Lifelong Learning to quickly adapt to new tasks, and the Small Language Model path that combines fine‑tuned task‑specific experts with LLM‑SLM collaboration for efficient, privacy‑preserving inference.

In-Context LearningKnowledge EngineeringLLM
0 likes · 4 min read
Beyond RAG: Three Emerging Knowledge‑Engineering Strategies (ICL, Online Learning, SLM)
DataFunTalk
DataFunTalk
Feb 11, 2025 · Artificial Intelligence

Roundtable on Enhancing Large Model Effectiveness: RAG, Tool Use, and Knowledge Engineering

Experts from Dipu, Ant Financial, iKang, and Zhihu discuss practical strategies for improving large model performance, covering RAG, tool‑using, offline knowledge engineering, multimodal training, evaluation metrics, and future trends, while sharing case studies from manufacturing, healthcare, retail, and C‑end applications.

Knowledge EngineeringLarge Language ModelsRAG
0 likes · 9 min read
Roundtable on Enhancing Large Model Effectiveness: RAG, Tool Use, and Knowledge Engineering
AntTech
AntTech
Aug 12, 2024 · Artificial Intelligence

DKCF Trustworthy Framework for Large Model Applications and AI Security Practices

The article outlines the DKCF (Data‑Knowledge‑Collaboration‑Feedback) trustworthy framework presented at the 2024 Shanghai Cybersecurity Expo, detailing challenges of large AI models, four key trust factors, and Ant Group's practical security implementations for professional AI deployments.

AI SafetyDKCFKnowledge Engineering
0 likes · 10 min read
DKCF Trustworthy Framework for Large Model Applications and AI Security Practices
DataFunTalk
DataFunTalk
May 5, 2022 · Artificial Intelligence

NLP Evolution: Symbolic Deep Parsing vs Neural Pre‑trained Models, Low‑Code Trends, and Semi‑Automated Applications

The article reviews the history and current state of NLP, compares symbolic deep‑parsing and neural pre‑trained approaches, discusses the knowledge‑bottleneck and low‑code trend, and illustrates semi‑automated, low‑code NLP deployment in the financial domain while pondering future integration of symbolic and neural methods.

Knowledge EngineeringNLPSemi-Automated
0 likes · 23 min read
NLP Evolution: Symbolic Deep Parsing vs Neural Pre‑trained Models, Low‑Code Trends, and Semi‑Automated Applications
DataFunTalk
DataFunTalk
Jan 20, 2020 · Artificial Intelligence

The Second Half of Knowledge Graphs: Opportunities and Challenges

This comprehensive report analyzes the evolution of knowledge graphs, reviews achievements of the first half, and examines the challenges and opportunities of the emerging second half, highlighting shifts from large‑scale simple applications to complex, expert‑driven scenarios, and outlining strategies for representation, acquisition, and application in the era of big data and AI.

AIKnowledge Engineeringknowledge graph
0 likes · 30 min read
The Second Half of Knowledge Graphs: Opportunities and Challenges
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 4, 2018 · Artificial Intelligence

Turning Fashion Into AI‑Ready Data: Building Practical Image Datasets

This article explains how Alibaba's Image & Beauty team designs and iterates a practical fashion image dataset by aligning data purpose, integrating professional knowledge, handling sample scarcity and structured noise, and defining fine‑grained evaluation metrics to enable AI models that truly understand clothing.

Computer VisionKnowledge Engineeringdata annotation
0 likes · 34 min read
Turning Fashion Into AI‑Ready Data: Building Practical Image Datasets
Alibaba Cloud Developer
Alibaba Cloud Developer
Dec 23, 2017 · Artificial Intelligence

How Large-Scale Knowledge Graphs Are Shaping AI and Natural Language Understanding

The December 20 Knowledge Graph symposium in Hangzhou, organized by Alibaba and the Chinese Society of Computational Linguistics, gathered leading Chinese scholars who discussed the pivotal role of massive knowledge graphs in AI, natural language processing, knowledge engineering, reasoning, and data‑driven intelligence.

Artificial IntelligenceKnowledge Engineeringknowledge graph
0 likes · 12 min read
How Large-Scale Knowledge Graphs Are Shaping AI and Natural Language Understanding