Earth Observation presents unique challenges for machine learning due to its non-stationary data distribution, spatio-temporal biases, and multimodal nature. TerraBytes aims to address these challenges by fostering discussions at the intersection of data curation, machine learning, and remote sensing. The workshop focuses on (1) curating less biased, globally representative EO datasets, (2) developing adaptable ML models for EO applications, and (3) bridging the gap between data acquisition and ML communities. By promoting interdisciplinary collaboration, TerraBytes seeks to advance EO research and enable inclusive, fair, and impactful applications.