The End of Cheap Data: Rethinking the Scaling Laws
The shift from cheap passive data to interaction data is crucial for AI. Engineers must focus on creating high-quality environments for effective learning.
The first era of AI scaling relied on cheap passive data, but the focus is shifting to interaction data, which captures models acting in real-world scenarios. This transition highlights the need for engineers to create high-quality environments for models to learn and adapt, marking a significant change in the data economy.