Download our #MachineLearning whitepaper to discover how to effectively integrate #ML in your lab. Get your free copy here: https://lnkd.in/eBTBQ-Hd #whitepaper
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We're excited to present CiteAssist, a tool designed to automate the generation of BibTeX entries for preprints, streamlining the process of bibliographic annotation. 🔗 Try CiteAssist Now: https://lnkd.in/eqXZMneE 🔗 Read the Paper: https://lnkd.in/e9cfUKY8 📚 Accepted at: SDProc @ ACL2024 What is CiteAssist? CiteAssist is a system that extracts metadata such as author names, titles, publication dates, and keywords to create standardized annotations within preprints. This system ensures that citations are easily accessible and consistent, potentially increasing the citational impact of your work. 🌟 Key Features: - Automatically attaches the BibTeX citation to the end of a PDF - Links the citation on the first page of the document - Ensures annotations remain accessible regardless of the repository - Adds relevant related papers based on extracted keywords 🔧 How it Works: CiteAssist simplifies the creation and distribution of citation annotations by generating a new PDF with the annotation or creating a LaTeX file for direct integration into the source document. This platform-independent approach makes it publishable at any preprint repository. 📑 Related Papers: CiteAssist suggests additional literature on potentially overlooked works, complementing traditional “related work” sections and mitigating citation amnesia. With CiteAssist, you can enhance your preprints' organization and reference management workflows through a free and publicly available web interface. #BibTeX #Preprints #ACL #SDProc #ResearchTools #CiteAssist #BibliographicManagement #NLProc Terry Ruas Jan Philip Wahle Bela Gipp
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Technical Terminology: RAG (Retrieval Augmented Generation) AKA: Trusted data source query (or subset of data from a larger trusted data pool) It's like the difference between a barracks lawyer...(aka someone who heard something from an untrusted source)....and a real lawyer (Licensed, passed the BAR, and accredited by the state).....also I don't need to know everything the lawyer knows....just the things that pertain to my case..... RAG is like that. The data you source will dictate the results you get. If I just use GenAI to ask the internet....then you will get the internet's answer (scary). If I ask my GenAI to review my on own data sources then I can trust the data is accurate (to the best of our internal ability). Also if I have ALL the data in the world....do I need to analyze ALL of that just to find out what time the grocery store closes......js.....RAG also gives you smart analytics (using Data Discipline concepts). Only ingest what you need...it's like a buffet.....why did you take so much....you can always go back for seconds. So next time you're running a query....ask yourself....do I trust the data? If not, then you need RAG..... Bad Data = Bad Results.....which wastes your time, costs you money, power, and potentially a whole lot more. Checkout the document below...it's nine pages....but the value is worth the time to understand the topics....cause it will change how you do business.... Disclaimer: Jason is not responsible for ingested data that was inaccurate, stale, or compromised......as with all things data - Consume responsibly. Happy Friday! LLM - Large Language Models (AI model) #IAmIntel #RAG #AIEverywhere #TechnicalLexicon
Transform your GenAI applications with Retrieval Augmented Generation (RAG), the innovative approach that defines how organizations harness the value of their data with LLMs. In our latest eBook by Eduardo Alvarez and Sancha N., we’ll explore some of the Intel hardware and software building blocks that optimize RAG application and enable contextual, real-time responses, while simplifying deployment and enabling scale. Learn more and access the eBook here: https://intel.ly/3wNn7am #GenAI #Developer #LLM
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Transform your GenAI applications with Retrieval Augmented Generation (RAG), the innovative approach that defines how organizations harness the value of their data with LLMs. In our latest eBook by Eduardo Alvarez and Sancha N., we’ll explore some of the Intel hardware and software building blocks that optimize RAG application and enable contextual, real-time responses, while simplifying deployment and enabling scale. Learn more and access the eBook here: https://intel.ly/3wNn7am #GenAI #Developer #LLM
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If you enjoyed this Thread, I wrote an entire book on Addressing Industry Challenges with ML Applications you might enjoy: - Real-world case studies 📚 - Step-by-step implementation guides 🛠️ - Expert insights and tips 💡 Over 10,000 copies sold & 500 reviews. Visit our website: dakesolutions.com #MachineLearning #IndustryChallenges #DataAnalytics #dakesolutions
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It's Success Story Time! ⏰ Our second Volume of the Success Story Booklet has been published, you can download it here: https://lnkd.in/eirc_UE9 Learn about the great work of our NCCs, get inspired by new Use Cases and see how companies profited from using #HPC!
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Revolutionize Your #GenAI Applications with Retrieval Augmented Generation (#RAG) Unleash the full potential of your GenAI applications and maximize the value of your data with Retrieval Augmented Generation (RAG). This groundbreaking approach is transforming how organizations leverage large language models (LLMs) to deliver contextual, real-time responses. Discover how Intel's innovative solutions simplify deployment, enable scalability, and empower your organization to: #Enhance Response Accuracy: RAG augments LLMs with relevant information retrieved from external sources, ensuring responses are more accurate, informed, and reliable. #Deliver Real-time Insights: Harness the power of RAG to generate responses based on the most up-to-date information, providing users with timely and actionable insights. #Streamline Deployment: Intel's optimized solutions simplify the deployment of RAG applications, reducing complexity and accelerating time-to-value. #Scale with Confidence: Leverage Intel's scalable infrastructure to handle growing data volumes and ensure your RAG applications can meet increasing demand. Don't miss out on this opportunity to transform your GenAI applications with Retrieval Augmented Generation. #Download the eBook now and embark on your RAG journey with Intel! [Link to eBook: https://intel.ly/3wNn7am]
Transform your GenAI applications with Retrieval Augmented Generation (RAG), the innovative approach that defines how organizations harness the value of their data with LLMs. In our latest eBook by Eduardo Alvarez and Sancha N., we’ll explore some of the Intel hardware and software building blocks that optimize RAG application and enable contextual, real-time responses, while simplifying deployment and enabling scale. Learn more and access the eBook here: https://intel.ly/3wNn7am #GenAI #Developer #LLM
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Every successful journey depends on the right amount of preparation. What do you need to know when embarking on a zero-trust journey? Download this eBook for the three tips you need to know to get started. Let CPAC, Inc.com help you along the way with solutions from Dell Technologies.
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Securing and managing your business data presents many challenges, from cyberthreats to accessibility and performance. NetApp ONTAP can help you conquer those challenges. 💪 Read how in this NetApp eBook.
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