Explore the importance of high-quality data in computer vision models through this 50-minute talk by Iva Gumnishka, founder and CEO of Humans in the Loop. Learn about the shift from model-centric to data-centric AI, focusing on data quality, diversity, and consistency. Discover methods for collecting and annotating datasets, ensuring representativeness, and avoiding harmful biases. Gain insights into algorithmic bias mitigation, self-supervised pretraining, and the future of computer vision data. Understand the EU's perspective on AI and examine canonical large-scale datasets. Perfect for data scientists, AI professionals, and anyone interested in improving computer vision model performance through better data practices.