Two essential processes for building quality datasets are data curation and data labeling. While both are critical for successful AI projects, they serve distinct purposes and play different roles in preparing datasets. Check out our recent blog where we’ll break down the differences between data curation and data labeling, explore why each is important, and show how they work together to improve AI model performance. https://lnkd.in/etGzFu9d #datacuration #datalabeling #AI
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Planning your AI Journey? Start by using AI to Clean Up Your Data Embarking on your #AI journey? The first step is crucial: cleaning up your #data using AI itself! Discover how AI can be leveraged to improve the long term quality of your data and set a strong foundation for your AI initiatives, ensuring accuracy and efficiency from the get-go. Read our latest article, to learn more about streamlining your path to AI integration. #GenAI #DataQuality #ArtificialIntelligence #DataManagement #TechInnovation #DigitalTransformation https://lnkd.in/gNCwXawx
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At EXL, we know that data is the foundation for AI, but could Generative AI also hold the key to streamlining your approach to data management? This Forbes article explains how GenAI could help manage data overload by predicting and generating new data. #AI #BigData #DataManagement
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