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"For six decades, databases have adhered to traditional structures, constrained by rows and columns. Yet, as our data universe expands exponentially, these rigid frameworks struggle to keep pace with the complexities of modern information. Enter graph technology—a critical enabler for our data-driven era. By embracing interconnectedness over linear constraints, graphs empower us to navigate the intricate webs of data relationships with unparalleled agility and depth. In a world where understanding connections is paramount, graphs illuminate the pathways to insight, innovation, and transformative change." #DataRevolution #GraphTechnology #Innovation #DataInsights #ModernDatabases #Interconnectedness #GraphDatabase #DataAnalytics #MachineLearning #RealTimeInsights #TechDisruption

In this episode, we discuss Source2Synth: Synthetic Data Generation and Curation Grounded in Real Data Sources by Alisia Lupidi, Carlos Gemmell, Nicola Cancedda, Jane Dwivedi-Yu, Jason Weston, Jakob Foerster, Roberta Raileanu, Maria Lomeli. The paper presents Source2Synth, a method designed to enhance Large Language Models (LLMs) by generating synthetic data with intermediate reasoning steps, grounded in real-world sources, to improve performance without costly human annotations. Source2Synth also filters out low-quality data points to ensure high-quality datasets. The method demonstrates significant improvements in performance for multi-hop question answering and tool usage in tabular question answering, with respective boosts of 22.57% on HotPotQA and 25.51% on WikiSQL.

What is Retrieval Augmented Generation and why is the data you feed it so important? http://spkl.io/6041fVMXS Read on to understand the importance of the information retrieval steps in such a workflow and how vector and ontology-based methods compare in our blog by Joseph Mullen, Director of Data Science & Professional Service at SciBite. http://spkl.io/6041fVMXS #LargeLanguageModels #LLMs #Ontologies

What is Retrieval Augmented Generation and why is the data you feed it so important? http://spkl.io/60484CS7A Read on to understand the importance of the information retrieval steps in such a workflow and how vector and ontology-based methods compare in our latest blog by Joseph Mullen Joe Mullen, Director of Data Science & Professional Service at SciBite. http://spkl.io/60484CS7A #LargeLanguageModels #LLMs #Ontologies

We are starting soon! Combine the power of #graphs with #GenAI ! #RAG enables #LLMs to combine private business or other domain specific data with public data for more relevant results: https://lnkd.in/eiAC_jXK Melli Annamalai will explain how Graphs can give additional insights into #data, enabling richer context to be provided to an #LLM, and will demonstrate how easy graph RAG is with graph and #vector technologies in #AutonomousDatabase. See you there! #oracle #adblearninglounge #learninglounge #adb

Combine the power of graphs with #GenAI! RAG enables LLMs to combine private business or other domain specific data with public data for more relevant results. #Graph RAG takes it further by using data relationship for richer insights and context. https://lnkd.in/geVngCyF

💥Discover the Game-Changer in Data Integrity!💥 🚀 Are you tired of data anomalies sneaking in and disrupting your systems? Fear not! The future of anomaly detection has arrived with the Robust Random Cut Forest (RCF) algorithm. Unveiled at the prestigious 33rd international conference on machine learning, RCF is revolutionizing how we safeguard our data. 💡 With its unparalleled ability to identify subtle or massive disruptions in real-time, RCF stands as a sentinel against potential threats to data quality and system performance. Whether you're in finance, healthcare, or any field reliant on constant data monitoring, RCF is your new best friend. But wait, there's more! ✨ Navigating the Basics of Robust Random Cut Forest (RCF): At its heart, RCF is an unsupervised algorithm that's impressively adept at handling vast sets of data. Forget about the hassle of classifying your data into 'normal' or 'abnormal'. RCF learns from the data itself, evolving and adapting to ensure precision in anomaly detection. This efficiency isn't just about saving time; it's about offering peace of mind in knowing your systems are protected by one of the most advanced tools out there. Why settle for traditional models when RCF offers adaptability, efficiency, and precision without the need for labeled data? Join the forefront of anomaly detection and ensure your systems are shielded against unforeseen disruptions. 🌐 Want to deep dive into the intricacies of RCF and how it can transform your data integrity strategies? Click through to read the full article and elevate your understanding of this groundbreaking tool! #AnomalyDetection #DataIntegrity #MachineLearning #InnovationInTech #RobustRandomCutForest #RCFRevolution

Combine the power of graphs with #GenAI! RAG enables LLMs to combine private business or other domain specific data with public data for more relevant results. #Graph RAG takes it further by using data relationship for richer insights and context. https://lnkd.in/gAZfcG2W

Combine the power of graphs with #GenAI! RAG enables LLMs to combine private business or other domain specific data with public data for more relevant results. #Graph RAG takes it further by using data relationship for richer insights and context. https://lnkd.in/demGtQUe

🔊 Exciting Announcement: Check out this new blog post on "A Principled Approach for a New Bias Measure" which provides a comprehensive algorithmic framework for quantifying bias in datasets and introduces a new bias measure. Understanding and mitigating data bias is critical, especially in decision-making processes. Explore the full details and insights in the post at https://bit.ly/3yriYtb. #DataScience #AIethics #MachineLearning