Topic: retrieval-augmented generation rag
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Moroccan Founder Secures $4.2M for AI Search Startup Backed by YC
ZeroEntropy, a startup co-founded by Moroccan entrepreneur Ghita Houir Alami, secured $4.2 million to develop AI-powered search infrastructure for retrieval-augmented generation (RAG) systems, backed by investors like Y Combinator. The company’s all-in-one API simplifies data retrieval for AI app...
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RAG: The Essential AI Tool Marketers Need to Know
Retrieval-Augmented Generation (RAG) enhances AI outputs by integrating targeted external data, addressing issues like hallucinations and generic responses in marketing applications. RAG's success depends on high-quality, structured data, including machine-readable inputs and precise retrievabili...
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How Delphi AI Scaled with Pinecone to Manage User Data
Delphi AI's personalized chatbots, called Digital Minds, faced scalability issues as increasing user data inputs threatened real-time responsiveness and performance. The company adopted Pinecone's managed vector database to ensure data privacy, low-latency queries, and scalable infrastructure, al...
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Master AI Search: Boost Your Brand in the New SEO Era [Webinar]
AI-driven search tools like ChatGPT are reducing clicks on traditional results, making it crucial for brands to optimize content for AI reference to maintain visibility. Generative Engine Optimization (GEO) is emerging as a key strategy, requiring marketers to adapt how AI models perceive and cit...
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S3: Train Search Agents Faster with Less Data
s3 is an open-source framework that simplifies RAG development by streamlining retriever model training and reducing data requirements, making LLM applications more efficient. The framework introduces a modular approach, separating search from generation and improving retrieval quality with...
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Mistral's New Code Model Beats OpenAI in Retrieval Tasks
Mistral AI launched Codestral Embed, a specialized code embedding model that outperforms competitors like OpenAI and Cohere in benchmarks, priced at $0.15 per million tokens. The model excels in retrieval-augmented generation (RAG) workflows, semantic code search, and similarity matching, with cu...
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Google Tops Embedding Model Rankings as Alibaba Gains Ground
Google's Gemini Embedding model leads performance benchmarks, offering advanced capabilities like semantic search and retrieval-augmented generation for enterprise AI workflows. The model features Matryoshka Representation Learning, providing flexible dimensionality options to balance accuracy an...
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ElevenLabs Launches AI Voice Assistants That Master Natural Conversation
ElevenLabs launched Conversational AI 2.0, a major upgrade to its AI voice platform, featuring advanced turn-taking algorithms and multilingual capabilities for more natural enterprise applications like customer service. The update includes a Retrieval-Augmented Generation (RAG) system fo...
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TD Securities Leverages Layer 6 & OpenAI for Real-Time Equity Insights
TD Securities has launched an AI Virtual Assistant, integrating OpenAI's GPT models with proprietary systems to provide real-time market insights and streamline workflows for institutional teams. The solution uses retrieval-augmented generation (RAG) and TD's proprietary Prism model to ensure acc...
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