In the rapidly evolving field of artificial intelligence (AI), data is the lifeblood of innovation. It is what trains machine learning models, allowing them to learn patterns and make predictions. The quality, quantity, and diversity of this data directly determine an AI system's performance and accuracy. Consequently, as a general rule, no matter how much data they have, AI researchers and developers could always use just a little bit more.
This is a companion discussion topic for the original entry at https://www.edgeimpulse.com/blog/solving-ais-data-drought-synthetic-data-workflows-with-nvidia-cosmos-predict