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How Agentic Hybrid Search Creates Smarter RAG Apps

How Agentic Hybrid Search Creates Smarter RAG Apps

By Ryan Michael If you’re building a [retrieval-augmented generation (RAG)](https://www.datastax.com/guides/what-is-retrieval-augmented-ge

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How I Built Smarter AI Tools for Pharma: From Generative AI to Agentic AI

How I Built Smarter AI Tools for Pharma: From Generative AI to Agentic AI

When I first started developing AI tools for the pharmaceutical industry, my idea was simple: to tackle real, everyday challenges. I’ve spent years watching compliance teams drowning in paperwor

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RAGFlow an Open-Source Retrieval-Augmented Generation (RAG) Engine

RAGFlow an Open-Source Retrieval-Augmented Generation (RAG) Engine

RAGFlow is an open-source Retrieval-Augmented Generation (RAG) engine that integrates with Large Language Models (LLM

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Beyond Text2SQL: A New Frontier in Natural Language Database Queries

Beyond Text2SQL: A New Frontier in Natural Language Database Queries

Introducing TAG, a Unified Model for Complex Question Answering Bridging the Gap Between AI and Databases The Promise and the Bottleneck Artificial intelligence (AI) is rapidly

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How to build Agentic RAG using CrewAI and Langchain

How to build Agentic RAG using CrewAI and Langchain

In the rapidly evolving landscape of AI, the ability to provide accurate, context-aware responses to user queries is a game-changer. Retrieval-Augmented Generation (RAG) has emerged as a powerf

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How to Use Structured Generation for LLM-as-a-Judge Evaluations

How to Use Structured Generation for LLM-as-a-Judge Evaluations

Structured generation is fundamental to building complex, multi-step reasoning agents in LLM evaluations — especially for open source models *Disclosure: I am a maintainer of [Opik](https

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Synthetic Data Generation with Language Models: A Practical Guide

Synthetic Data Generation with Language Models: A Practical Guide

In the evolving landscape of artificial intelligence, data remains the fuel that powers innovation. But what happens when acquiring real-world data becomes challenging, expensive, or even impos

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[ OpenAI 給的 2024 年聖誕禮物 ] — 3 Sora 影片生成工具 | by Simon Liu | Dec, 2024 | Medium

[ OpenAI 給的 2024 年聖誕禮物 ] — 3 Sora 影片生成工具 | by Simon Liu | Dec, 2024 | Medium

備註：部分內容有使用 AI 工具進行處理，內容已經審閱過，如有發現錯誤再請留言告知，感謝大家！ OpenAI Day 3 發表會在這邊，全程 20 分鐘，大家可以聽聽，或者先滑到下面，我將為各位整理本次重點。 幫大家整理十大 Sora 重點 I. 推出 Sora 影片生成工具 OpenAI 發表全新影片生成產品 Sora，這是專為影片創作設計的人工

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Mastering the 25 Types of RAG Architectures: When and How to Use Each One

Introduction Retrieval-Augmented Generation (RAG) architectures have revolutionized the way we approach information retrieval. These architectures bridge the gap between generating responses

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Building a Reliable Text Classification Pipeline with LLMs: A Step-by-Step Guide

Building a Reliable Text Classification Pipeline with LLMs: A Step-by-Step Guide

Overcoming common challenges in LLM-based text classification In this step-by-step tutorial, we’ll walk through how to use large language models (LLMs) to build a text classification pi

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Comparing Leading Text-to-Image Generation Models for Adding Text to Images

Comparing Leading Text-to-Image Generation Models for Adding Text to Images

A comparison of nine leading image generation models’ ability to render accurate text (words and phrases) within an image. In this post, we will assess the capabilities of nine state-of-the-a

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Artifacts: Top Mindblowing uses of Claude 3.5 Sonent

Artifacts: Top Mindblowing uses of Claude 3.5 Sonent

Anthropic recently launched its most advanced LLM, “Claude 3.5 Sonnet,” and it’s mindblowing. People on social media called this model the most advanced LLM currently available. This AI model out

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LongRAG: Giving AI a Bigger Net to Catch More Fish in the Sea of Information

LongRAG: Giving AI a Bigger Net to Catch More Fish in the Sea of Information

In my previous article, I introduced whether RAG would become obsolete due to long-context LLMs. Today, let’

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Retrieval-Augmented Generation: Approaches, State of the Art, and Optimization Strategies

Retrieval-Augmented Generation: Approaches, State of the Art, and Optimization Strategies

⭐ RAG is particularly useful in knowledge-intensive scenarios or domain-specific applications that require knowledge that’s continually updating. RAG has been popularized recently with its app

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