Excited to share our latest ESOMAR paper called "Synthetic Data in Marketing Studies: Exploring the promise of generative AI and synthetic data," created in collaboration with Thomas Duhard from GROUPE IFOP as part of ESOMAR Congress 2024 🚀 In this paper, we dive into the promising potential of synthetic data and generative AI to transform market research. Discover how AI can improve the representation of under-sampled groups and revolutionize data collection, providing richer granular insights in any quantitative study. A must-read for anyone looking to stay at the forefront of data-driven market research innovation!
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Founder at Panoplai | #SaaS Founder | Product and Technology Leader | Data and Insights Expert | Published in HBR, Barron's, AdWeek, Nasdaq
A lot of people ask me about AI and about 'synthetic data' in particular. While we are launching our unique version of "AI-generated data", we have very specific thoughts around it, about its usefulness, its applications, and in particular the fusion of real-world data with AI-created data. Take a look at my article! https://lnkd.in/gpZYKSFX #AIGeneratedData #MarketResearch #SyntheticData #FutureOfAI #GlimpseInsights
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🚨Speaker Announcement! We have Roman Swoszowski, Chief Product Officer, g.IQ for Chief Data and Analytics Officers (CDAO) Germany in Munich! Roman will be discussing the key topic of ‘Maximising Insights from Your Data: Leveraging Generative AI for Enhanced Analytics’. ✅Attendees can learn: • The transformative potential of Generative AI in revolutionizing the analytics landscape, aiming to unravel the proficiency of Generative AI models in synthesizing, interpreting, and augmenting data analytics processes. • Common challenges related to data and analytics initiatives and offer recommendations on how to avoid them. • Real-world case studies, demonstrating how businesses and researchers have successfully harnessed generative AI to unearth deep insights, foster innovation, and drive strategic decision-making. 🎤Find out what else will be discussed across the 2-day conference on 17-18 April: https://bit.ly/49h4Qjb #CDAO #CDO #CAO #Data #Analytics #DataIntelligence #DataDriven #DataAndAnalytics #DataAnalytics #AnalyticsInsights #DataLed #DataTransformation #DataCulture #TestAutomation #TestManagement #MachineLearning #ArtificialIntelligence #AI #CDAOGermany
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Value NOT Volume of Data: The key to unlocking the mysteries of artificial intelligence doesn’t lie in the volume of data but in its intrinsic value. Organizations can uncover hidden insights, make informed decisions, and drive transformative change by prioritizing relevant data. Explore why the value, not the volume of data, is essential in AI discovery: https://lnkd.in/d6Guhm9S
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Value NOT Volume of Data: The key to unlocking the mysteries of artificial intelligence doesn’t lie in the volume of data but in its intrinsic value. Organizations can uncover hidden insights, make informed decisions, and drive transformative change by prioritizing relevant data. Explore why the value, not the volume of data, is essential in AI discovery: https://lnkd.in/d6Guhm9S
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ChunkRAG: Novel LLM-Chunk Filtering Method for RAG Systems The research paper introduces a method called ChunkRAG, which aims to enhance Retrieval-Augmented Generation (RAG) systems by filtering irrelevant information at a fine-grained, chunk level rather than the entire document level. Key Findings from the Paper: 🔹🔹 Improved Accuracy with Chunk-Level Filtering: ChunkRAG achieved an accuracy of 64.9% on the PopQA dataset, outperforming traditional RAG models like CRAG (54.9%). The 10-point improvement demonstrates the effectiveness of chunk-level filtering in enhancing the precision and factuality of generated responses. 🔹🔹Reduction in Hallucinations and Irrelevance: By filtering irrelevant chunks before generation, ChunkRAG significantly reduced hallucinations and irrelevant information in responses. This was particularly valuable in fact-checking and multi-hop reasoning tasks, where accuracy is crucial. 🔹🔹Enhanced Multi-Step Reasoning Capabilities: Chunk-level filtering and relevance scoring helped improve response accuracy in multi-step reasoning tasks, as errors did not accumulate over multiple retrieval stages. This yielded a success rate improvement of up to 66% over similar models in complex multi-step applications. 🔹🔹Robust Relevance Assessment: The use of dynamic relevance thresholds and LLM-based relevance scoring allowed for a more granular and accurate retrieval process. This made ChunkRAG effective in extracting only the most contextually relevant chunks for the query, minimizing unnecessary data inclusion. 🔹🔹Scalability Potential: While the primary evaluation was on the PopQA dataset, ChunkRAG was designed with scalability in mind, suggesting its potential effectiveness across other datasets like Biography and PubHealth. Future testing on more extensive datasets could validate this adaptability. 🔹🔹High Computational Cost: The multi-level scoring and relevance assessment of chunks require substantial computational resources, particularly in real-time applications. Optimizing ChunkRAG for efficiency and cost-effectiveness remains an area for future research. #GenAI #AI #LLM #Datascience #machinelearning #data #Analytics Reference : https://lnkd.in/gE5hrnWG
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Value NOT Volume of Data: The key to unlocking the mysteries of artificial intelligence doesn’t lie in the volume of data but in its intrinsic value. Organizations can uncover hidden insights, make informed decisions, and drive transformative change by prioritizing relevant data. Explore why the value, not the volume of data, is essential in AI discovery: https://lnkd.in/d6Guhm9S
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Value NOT Volume of Data: The key to unlocking the mysteries of artificial intelligence doesn’t lie in the volume of data but in its intrinsic value. Organizations can uncover hidden insights, make informed decisions, and drive transformative change by prioritizing relevant data. Explore why the value, not the volume of data, is essential in AI discovery: https://lnkd.in/d6Guhm9S
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The Data Dilemma: The key to unlocking the mysteries of artificial intelligence doesn’t lie in the volume of data but in its intrinsic value. Organizations can uncover hidden insights, make informed decisions, and drive transformative change by prioritizing relevant data. Explore why the value, not the volume of data, is essential in AI discovery: https://lnkd.in/d6Guhm9S
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The Human Touch in High-Tech Research: A 2024 Outlook on Industry Trends Our 7th annual Future Trends in Research and Technology webinar brought together leaders in the market research industry to discuss how innovations are reshaping the field. Featuring Barry Jennings from Microsoft, Charlie Rader from Procter & Gamble (P&G), Lenny Murphy from Greenbook, and Brett Watkins and Kelli Hammock from L&E Research, the panel delved into advancements in AI, synthetic data, insourcing, and participant experience. This discussion provided a nuanced look at the balance between embracing technology and maintaining a human-centered approach in research. https://hubs.ly/Q02--gys0
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Value NOT Volume of Data: The key to unlocking the mysteries of artificial intelligence doesn’t lie in the volume of data but in its intrinsic value. Organizations can uncover hidden insights, make informed decisions, and drive transformative change by prioritizing relevant data. Explore why the value, not the volume of data, is essential in AI discovery: https://lnkd.in/d6Guhm9S
