https://www.youtube.com/watch?v=VutssD7EVK4

Finding the right dataset remains a significant challenge in AI development, impacting model accuracy, fairness and usability.

In this conversation, Ambica Rajagopal explores key issues such as data availability, bias, quality control and ethical considerations in sourcing and refining datasets. She discusses how businesses struggle with incomplete or biased data, the impact of privacy regulations like GDPR along with the need for robust validation and augmentation techniques. She also highlights innovative solutions such as synthetic data, federated learning, and strategic data partnerships that can help organizations enhance AI performance while maintaining ethical integrity.

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