Human Factors Technology
Personalization at scale takes data - and a lot of it. In this episode we explore types of data that can can be “home grown” to help create ever more powerful and personalized experiences. In particular we dive into the concepts of synthetic and augmented data and their implications for technology and human experience. Resources AWS’ Guide To Data Augmentation - https://aws.amazon.com/what-is/data-augmentation/ [https://aws.amazon.com/what-is/data-augmentation/] Synthetic Data Generation using LLM: Crash Course for Beginners - https://youtu.be/hMjtdECXlYo?si=AHLaad4fj13VlG2N [https://youtu.be/hMjtdECXlYo?si=AHLaad4fj13VlG2N] Synthetic Data and the Future of AI - https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4722162 [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4722162] Personalization Done Right (Spotify Case Study) - https://hbr.org/2024/11/personalization-done-right [https://hbr.org/2024/11/personalization-done-right] Takeaways Synthetic data mimics statistical properties of real data. Augmented data enriches existing data sets for better insights. Context is crucial when utilizing data for decision-making. Collaboration with data scientists enhances data utilization. Synthetic data allows for scaling and running simulations. Augmented data can personalize experiences across various industries. Data limitations can hinder effective personalization efforts. Elasticity testing can benefit from larger synthetic data sets. Understanding different data types is essential for professionals. The implications of data types extend to healthcare and user experience. Chapters 00:00 - Introduction to Synthetic and Augmented Data 03:18 - Understanding Augmented Data 06:35 - Exploring Synthetic Data 09:18 - Applications of Augmented Data 12:08 - The Intersection of Data and Personalization 15:15 - Conclusion and Future Implications
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