Modern business intelligence demands speed, and utilizing AI tools for Excel is the ultimate way to hyper-charge your data workflows this year.

本文介绍一个完整的"AI智能体工厂"平台的设计与实现。该平台以本体模型（Ontology Model）作为中间表示层，打通了从原始业务需求到可运行AI智能体的完整链路：需求探索 → 本体建模 → 可视化验证 → 能力代码生成 → 技能封装 → Agent动态发布。 今天完整分享下最近通过AI编程实现的一个基于本体模型+AI大模型驱动的端到端AI智能体交付平台。包括需求分析，整体设计，核心功能实现。

Spread the love“`html In the ever-evolving world of online retail, understanding customer feedback is crucial for maintaining a competitive edge. Google Cloud has recently launched a groundbreaking ...

Generative artificial intelligence (AI) may have planted the seeds for the ongoing fervour over AI, but agentic AI is the true breakthrough that will revolutionise enterprise data pipelines and ...

Abstract: The iceberg cubing problem is to compute the multidimensional group-by partitions that satisfy given aggregation constraints. Pruning unproductive computation for iceberg cubing when ...

Google Cloud Summit came to London last week, and we took the opportunity to sit down with database execs Sailesh ...

Effective prompts use four core elements. Start by assigning a role, then give background context, state a clear task with an ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the generation of plausible-sounding but factually incorrect information. KAIST ...

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This repository contains the Azure SQL bindings for Azure Functions extension code as well as a quick start tutorial and samples illustrating how to use the binding in different ways. The types of ...