Author

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.

2.7k

Articles

Likes

15.2k

Views

Comments

Latest from DataFunTalk

100 recent articles max

DataFunTalk

Sep 3, 2026 · Industry Insights

Snowflake Extends Data Lineage to AI Agents: Semantic Layer Becomes Governance Boundary

Snowflake's new Data Lineage for Cortex Agents tracks agent data reachability through governed semantic views, extending lineage from tables to AI agents; Databricks pursues similar governance via Unity Catalog and Genie Ontology, positioning the semantic layer as a critical AI governance boundary for accuracy, authorization, consistency, and auditability.

AI GovernanceCortex AgentsDatabricks

0 likes · 16 min read

Snowflake Extends Data Lineage to AI Agents: Semantic Layer Becomes Governance Boundary

DataFunTalk

Sep 2, 2026 · Operations

Why Smarter Data Platforms Are Harder to Operate and How Next‑Gen System Intelligence Solves It

As data platforms become increasingly intelligent, operational complexity rises due to heterogeneous workloads and finer‑grained configurations, but Tencent Cloud's TCInsight introduces system intelligence with specialized agents that automate selection, migration, usage and tuning, cutting migration time by 50%, reducing resource waste by 15% and shrinking fault‑diagnosis from hours to minutes.

AI AgentsCloud ComputingSystem Intelligence

0 likes · 11 min read

Why Smarter Data Platforms Are Harder to Operate and How Next‑Gen System Intelligence Solves It

DataFunTalk

Sep 2, 2026 · Artificial Intelligence

How Edge AI Agents Run on Phones and PCs: Architecture Deep Dive

The article breaks down the three‑layer foundation—compute unlocking with Arm SME2, model slimming via Tencent's ultra‑low‑bit quantization, and deployment using ExecuTorch and Windows on Arm—that enables large AI agents to operate efficiently on mobile, PC, and other edge devices.

Arm SME2ExecuTorchMNN

0 likes · 3 min read

How Edge AI Agents Run on Phones and PCs: Architecture Deep Dive

DataFunTalk

Sep 2, 2026 · Artificial Intelligence

Fusion Model by FUMO Lab Sets New Frontier in Multi‑Model AI Performance

FUMO Lab’s Fusion Model unifies heterogeneous AI models through a closed‑loop intelligence allocation process, achieving first place on four leading benchmarks, cutting inference cost by 30‑40%, and demonstrating superior stability on scientific QA tasks with concrete case studies.

AI for scienceFusion Modelbenchmark

0 likes · 16 min read

Fusion Model by FUMO Lab Sets New Frontier in Multi‑Model AI Performance

DataFunTalk

Sep 1, 2026 · Artificial Intelligence

Cracking the Last Mile of Edge Agents: Quantization, Instruction Sets, and Deployment

The article examines how large‑model agents can finally run on phones, PCs, cars and IoT devices by tackling three engineering layers—unlocking compute with Arm SME2, slimming models through ultra‑low‑bit quantization, and deploying with ExecuTorch and Windows on Arm—presented at the free Arm Create 2026 events.

Arm SME2ExecuTorchMNN

1 likes · 3 min read

Cracking the Last Mile of Edge Agents: Quantization, Instruction Sets, and Deployment

DataFunTalk

Sep 1, 2026 · Big Data

From Three Months to Two Weeks: DataWorks Data Agent Revamps Xinfēi Technology’s Multi‑Country Data‑Warehouse Delivery

Xinfēi Technology, a fintech data‑intelligence provider, cut its multi‑country data‑warehouse rollout from three months to about two weeks by adopting Alibaba Cloud’s DataWorks Data Agent, which unified data ingestion, task development, quality configuration, lineage analysis and release verification, introduced Skills and an enterprise semantic layer, and achieved up to six‑fold efficiency gains across ODS, DWD, DWS, DQC and reporting.

AutomationBig DataData Agent

0 likes · 10 min read

From Three Months to Two Weeks: DataWorks Data Agent Revamps Xinfēi Technology’s Multi‑Country Data‑Warehouse Delivery

DataFunTalk

Sep 1, 2026 · Artificial Intelligence

How Palantir’s AI Agents Are Moving Beyond Q&A to Orchestrate Enterprise Workflows

Palantir’s August 27 update adds Automate tools to AI Forward Deployed Engineer, letting agents configure business automation, manage conditions and effects, and integrate with Ontology, Action, and Function, while introducing governance via branching and approval, yet still with clear capability limits.

AI AgentsAI GovernanceAutomate

0 likes · 12 min read

How Palantir’s AI Agents Are Moving Beyond Q&A to Orchestrate Enterprise Workflows

DataFunTalk

Aug 31, 2026 · Artificial Intelligence

Palantir Adds Skills to Agents: How Enterprise AI Begins Reusing Analysis Methods

Palantir's August 18 update to AIP Analyst introduces Skills and Analysis Lookup, turning reusable analysis procedures into callable commands and using historical analyses as templates, thereby extending agent memory with method reuse tightly integrated with the Ontology framework.

AI AgentsAnalysis LookupEnterprise AI

0 likes · 10 min read

Palantir Adds Skills to Agents: How Enterprise AI Begins Reusing Analysis Methods

DataFunTalk

Aug 30, 2026 · Artificial Intelligence

How Ontology-Driven Agents Provide Secure, Controllable Execution in Harness Engineering

The article analyzes the current Agent hype, explains why autonomous agents often lack business‑level safety and control, and proposes an ontology‑driven Harness Engineering framework that embeds constraints, context management, and feedback loops directly into the business semantics, illustrated with the Knora implementation and real‑world case studies.

AI AgentsEnterprise AIKnora

0 likes · 21 min read

How Ontology-Driven Agents Provide Secure, Controllable Execution in Harness Engineering

DataFunTalk

Aug 29, 2026 · Artificial Intelligence

Deep Dive into Agent Harness: Dissecting the Architecture Behind AI Agents

The article defines the Agent Harness as the full software infrastructure that turns a stateless LLM into a capable autonomous agent, details its three engineering layers, enumerates twelve production‑grade components, walks through a step‑by‑step execution loop, compares implementations in Anthropic, OpenAI, LangChain, CrewAI and AutoGen, and discusses key design decisions and future trends, emphasizing that harnesses remain essential even as model capabilities improve.

AI AgentsAnthropicLLM

0 likes · 22 min read

Deep Dive into Agent Harness: Dissecting the Architecture Behind AI Agents