The search for life in the universe and an understanding of the origin, evolution, and future of life involves a complex hierarchy of scientific areas in pursuit of an even more complex hierarchy of phenomena; from the complexity of molecular evolution to the integrated nature of livings systems and environments that span from the very local to planet-wide and to the breadth of stellar systems and galaxies.
Many of the theoretical questions and experimental and observational challenges of astrobiology call for scientific tools beyond the traditional. AI/ML approaches can provide those tools with capabilities in decoding and modeling highly non-linear correlative properties and high dimensionality/feature number in data.
Although AI/ML tool frameworks are increasingly accessible as off-the-shelf or open-source software, their choice and application involve a very steep human learning curve and the development of hands-on experience and skills to optimize tool structures and understand their limitations.
AI-Astrobiology is a ‘living’ resource that focuses on the needs of the astrobiology community by providing collated and curated information on AI/ML applications, learning materials, software resources, training data resources, and current literature relevant to the field.