Planetary science: Evolutionary dichotomy for rocky planets

Artificial intelligence for geoscience: Progress, challenges, and perspectives

This paper explores the evolution of geoscientific inquiry, tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence (AI) and data collection techniques. Traditional models, which are grounded in physical and numerical frameworks, provide robust explanations by explicitly reconstructing underlying physical processes. However, their limitations in comprehensively capturing Earth's complexities and uncertainties pose challenges in optimization and real-world applicability. In contrast, contemporary data-driven models, particularly those utilizing machine learning (ML) and deep learning (DL), leverage extensive geoscience data to glean insights without requiring exhaustive theoretical knowledge. ML techniques have shown promise in addressing Earth science-related questions. Nevertheless, challenges such as data scarcity, computational demands, data privacy concerns, and the "black-box" nature of AI models hinder their seamless integration into geoscience. The integration of physics-based and data-driven methodologies into hybrid models presents an alternative paradigm. These models, which incorporate domain knowledge to guide AI methodologies, demonstrate enhanced efficiency and performance with reduced training data requirements. This review provides a comprehensive overview of geoscientific research paradigms, emphasizing untapped opportunities at the intersection of advanced AI techniques and geoscience. It examines major methodologies, showcases advances in large-scale models, and discusses the challenges and prospects that will shape the future landscape of AI in geoscience. The paper outlines a dynamic field ripe with possibilities, poised to unlock new understandings of Earth's complexities and further advance geoscience exploration.

Habitability on Early Mars and the Search for Biosignatures with the ExoMars Rover

The second ExoMars mission will be launched in 2020 to target an ancient location interpreted to have strong potential for past habitability and for preserving physical and chemical biosignatures (as well as abiotic/prebiotic organics). The mission will deliver a lander with instruments for atmospheric and geophysical investigations and a rover tasked with searching for signs of extinct life. The ExoMars rover will be equipped with a drill to collect material from outcrops and at depth down to 2 m. This subsurface sampling capability will provide the best chance yet to gain access to chemical biosignatures. Using the powerful Pasteur payload instruments, the ExoMars science team will conduct a holistic search for traces of life and seek corroborating geological context information. Key Words: Biosignatures-ExoMars-Landing sites-Mars rover-Search for life. Astrobiology 17, 471-510.