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DataFunTalk

Dedicated to sharing and discussing big data and AI technology applications, aiming to empower a million data scientists. Regularly hosts live tech talks and curates articles on big data, recommendation/search algorithms, advertising algorithms, NLP, intelligent risk control, autonomous driving, and machine learning/deep learning.

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Latest from DataFunTalk

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DataFunTalk

Jun 28, 2026 · Artificial Intelligence

How Knora Uses Ontology + Large Models to Overcome Hallucination and Execution Gaps in Enterprise AI

The article presents Knora 4.0, an ontology‑enhanced AI platform that tackles six enterprise AI challenges—hallucination, instability, weak planning, poor responsiveness, data integration, and long cold‑start—by tightly coupling domain ontologies with large language models, detailing its architecture, autonomous agents, real‑world LED production line use case, roadmap, and expert round‑table insights.

AI platformAutonomous AgentsKnowledge Graph

0 likes · 15 min read

How Knora Uses Ontology + Large Models to Overcome Hallucination and Execution Gaps in Enterprise AI

DataFunTalk

Jun 28, 2026 · Artificial Intelligence

Why AlphaFold’s Success Refutes the ‘Bitter Lesson’ Myth – Insights from Nobel Laureate John Jumper

In a deep interview, AlphaFold’s core developer John Jumper explains how domain‑specific engineering, extensive ablation studies, and a hybrid Evoformer‑IPA architecture—not sheer compute—enabled protein‑folding breakthroughs, while distinguishing AI’s roles in prediction, control, and human‑in‑the‑loop understanding.

AlphaFoldDeep LearningEvoformer

0 likes · 39 min read

Why AlphaFold’s Success Refutes the ‘Bitter Lesson’ Myth – Insights from Nobel Laureate John Jumper

DataFunTalk

Jun 27, 2026 · Industry Insights

How Ontology Turns Data Platforms into Decision Engines

The article examines why costly data middle platforms often become "data swamps," cites real‑world failures, and shows how Palantir's ontology‑driven three‑layer architecture (semantic, dynamics, decision) can transform read‑only data warehouses into automated decision engines delivering triple‑digit ROI.

Decision AutomationEnterprise ArchitectureOntology

0 likes · 4 min read

How Ontology Turns Data Platforms into Decision Engines

DataFunTalk

Jun 27, 2026 · Artificial Intelligence

OpenAI Unveils GPT‑5.6 ‘Solar System’ Models: Sol, Terra, Luna Outperform Mythos

OpenAI released GPT‑5.6 with three tiered models—Sol, Terra and Luna—named after celestial bodies, offering lower pricing, record‑breaking benchmark scores in programming, security, biology and health, new max and ultra inference modes, limited partner access, and a deployment plan on Cerebras that could make it the fastest flagship LLM.

AI benchmarksGPT-5.6OpenAI

0 likes · 8 min read

OpenAI Unveils GPT‑5.6 ‘Solar System’ Models: Sol, Terra, Luna Outperform Mythos

DataFunTalk

Jun 26, 2026 · Artificial Intelligence

Building an Enterprise‑Grade RAG 2.0 System: Architecture, Challenges, and Best Practices

This article examines how large‑model shortcomings such as hallucination, staleness, and data‑privacy risks are mitigated by Retrieval‑Augmented Generation, and walks through a layered enterprise‑grade RAG 2.0 design—including offline document parsing, multi‑turn query rewriting, hybrid vector‑plus‑full‑text retrieval, two‑stage ranking, knowledge filtering, and prompt‑driven generation—while sharing concrete model choices, evaluation metrics, and lessons learned.

Document ParsingHybrid RetrievalPrompt engineering

0 likes · 23 min read

Building an Enterprise‑Grade RAG 2.0 System: Architecture, Challenges, and Best Practices

DataFunTalk

Jun 26, 2026 · Industry Insights

Ontology Is a Management Challenge, Not a Technical One – Enterprise AI Insights

In a 90‑minute roundtable, industry veterans from Huawei, Ping An and a startup dissect why ontology is a governance issue rather than a technical hurdle, expose the paradox of modeling pain, describe two common AI‑adoption ailments, warn of hidden technical debt in highlight projects and share hard‑won lessons on building AI‑native organizations from the ground up.

AI Native OrganizationAI transformationOntology

0 likes · 17 min read

Ontology Is a Management Challenge, Not a Technical One – Enterprise AI Insights

DataFunTalk

Jun 26, 2026 · Artificial Intelligence

Why Prompts Are Obsolete and Loop Engineering Is the Next AI Paradigm

The article explains how the AI community is shifting from writing prompts to designing autonomous loops that iteratively execute, evaluate, and repeat tasks, detailing the technical differences from traditional agents, real‑world implementations like Claude Code and OpenAI Codex, and a step‑by‑step roadmap for building reliable loops.

AI LoopAgentAutomation

0 likes · 13 min read

Why Prompts Are Obsolete and Loop Engineering Is the Next AI Paradigm

DataFunTalk

Jun 26, 2026 · Databases

How SelectDB Tackles Speed, Unification, Agent‑Native and Cloud Elasticity for the Agent Era

The 2026 SelectDB AI product launch outlines how the database addresses four Agent‑era challenges—sub‑second speed, unified multi‑modal data, Agent‑Native interfaces, and cloud elasticity—through benchmark‑backed performance, a new MCP server, Litefuse observability, and a serverless architecture.

AI Data InfrastructureAgent‑NativeMulti-modal

0 likes · 10 min read

How SelectDB Tackles Speed, Unification, Agent‑Native and Cloud Elasticity for the Agent Era

DataFunTalk

Jun 25, 2026 · Big Data

From Writing SQL to Speaking Requirements: Practical Guide to DataWorks Data Agent

This article walks through using DataWorks Data Agent to automate end‑to‑end data‑warehouse development—from preparing source tables and a structured requirement document, uploading it, crafting task commands, selecting execution modes and models, to the agent generating SQL, building workflows, publishing them, and producing a final report—all without writing SQL manually.

AI automationBig DataData Agent

0 likes · 16 min read

From Writing SQL to Speaking Requirements: Practical Guide to DataWorks Data Agent

DataFunTalk

Jun 24, 2026 · Big Data

How Xiaohongshu Re‑engineered Its Data Architecture for the Big AI Data Era

Xiaohongshu, with over 350 million monthly users and daily logs in the billions, migrated its data platform from AWS to Alibaba Cloud and iterated four times—from a ClickHouse‑based ad‑hoc layer to a Lambda architecture and finally a Lakehouse with incremental compute—cutting architecture complexity, resource cost and development effort each to about one‑third while delivering second‑level analytics on trillion‑scale data.

Big DataFlinkIncremental Compute

0 likes · 22 min read

How Xiaohongshu Re‑engineered Its Data Architecture for the Big AI Data Era