News from generation RAG
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Automated Recruiter Calls with Claude 3, ElevenLabs, and LlamaIndex
The Challenges of Manual Recruiter Calls The traditional approach to recruiter calls is fraught with inefficiencies and pitfalls that can frustrate both candidates and hiring managers. One of the primary issues is the time-consuming nature of manual recruiting. Recruiters often find themselves overwhelmed with countless meetings, interviews, events, and phone calls, making it challenging to…
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Building a Graph RAG System: Enhancing LLMs with Knowledge Graphs
Graph RAG (Retrieval Augmented Generation) is a groundbreaking approach that combines the power of knowledge graphs with large language models (LLMs) to deliver more accurate, contextual, and cost-effective search results. Pioneered by NebulaGraph, Graph RAG addresses the limitations of traditional RAG techniques, which often struggle with complex queries and the high demands of cutting-edge technologies…
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RAG in the Cloud: Comparing AWS, Azure, and GCP for Deploying Retrieval Augmented Generation Solutions
Retrieval Augmented Generation (RAG) is a cutting-edge technique that enhances the capabilities of generative AI models by integrating them with information retrieval systems. RAG addresses the limitations of large language models (LLMs) by providing them with access to up-to-date, domain-specific information, resulting in more accurate, contextually relevant, and timely responses to user queries. The importance…
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ElevenLabs’ Commercial Use: Terms, Pricing, and Safety Explained
Introduction to ElevenLabs ElevenLabs is a cutting-edge software company that has been making waves in the world of artificial intelligence and natural language processing. Founded in 2022 by ex-Google machine learning engineer Piotr Dąbkowski and ex-Palantir deployment strategist Mateusz Staniszewski, ElevenLabs has quickly established itself as a leader in the development of natural-sounding speech synthesis…
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Optimizing Retrieval Augmented Generation (RAG) for Production with LlamaIndex
Introduction to RAG and LlamaIndex Retrieval Augmented Generation (RAG) is a powerful technique that enhances the accuracy and relevance of generative AI models by integrating them with external knowledge sources. RAG addresses the limitations of large language models (LLMs) which, despite being trained on vast amounts of data, may lack up-to-date or domain-specific information. By…
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Claude 3 vs GPT-4: Is Anthropic’s New AI Chatbot Superior?
Claude 3 is the latest family of large language models (LLMs) developed by AI startup Anthropic. This new suite of AI models includes three versions: Claude 3 Opus, Claude 3 Sonnet, and the unreleased Claude 3 Haiku. Anthropic claims that Claude 3 not only outperforms its predecessor, Claude 2.1, but also rivals the capabilities of…
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Ultimate Guide to Air-Gapped Local AI Setup for Sensitive Documents
An air-gapped environment, also known as an air-gapped network or system, is a computing setup that is physically isolated from all other networks, including the internet. This isolation is achieved by creating a physical gap or disconnection between the air-gapped system and any external connections, ensuring that no data can be transmitted or received through…
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ElevenLabs: Automatically Translate Your Podcast into 27+ Languages
ElevenLabs, a trailblazing software company founded in 2022, is revolutionizing the world of podcasting and content creation with its cutting-edge AI voice technology. By harnessing the power of deep learning models, ElevenLabs enables users to generate lifelike spoken audio in any voice and style, making it an indispensable tool for podcasters looking to expand their…
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Elevenlabs: Generating Beautiful Podcasts With Your AI Voice
Do you have a lot of incredible information to share, but cant find the motivation to create your first podcast episode? It can be easier than you think to get started with the AI tools available today. Imagine dumping all of your useful notes, research, and documents into a folder, then asking AI to read…
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What is a rag system in AI?
In the rapidly evolving landscape of artificial intelligence (AI), one of the most significant advancements in recent years has been the development and implementation of Retrieval-Augmented Generation (RAG) systems. These systems represent a paradigm shift in how AI models interact with and generate information, offering a more nuanced, accurate, and contextually relevant output than ever…
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What Is Retrieval-Augmented Generation (RAG)?
Introduction to Retrieval-Augmented Generation In the rapidly evolving landscape of artificial intelligence (AI), a groundbreaking innovation known as Retrieval-Augmented Generation (RAG) is setting new benchmarks in the realm of Natural Language Processing (NLP). At its core, RAG is a sophisticated technique that synergizes the strengths of retrieval models and generative models to produce text that…
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RAG 101: How Retrieval Augmented Generation is Revolutionizing Enterprise Information Retrieval
Welcome to the inaugural post on the Rag About It blog! As a new technical writer here, I’m excited to dive into the fascinating world of Retrieval Augmented Generation (RAG) and explore how this cutting-edge AI technology is transforming the way enterprises handle information retrieval. In this “RAG 101” post, we’ll break down the basics…