Machine learning (ML) has enabled and accelerated frontier research in the life sciences, but democratised access to such methods is, unfortunately, not a given. Access to necessary hardware and software, knowledge and training, is limited, while methods are typically insufficiently documented and hard to find. Furthermore, even though modern AI-based methods typically generalize well to unseen data, no standard exists to enable sharing and fine-tuning of pre-trained models between different analysis tools. Existing user-facing platforms operate entirely independently from each other, often failing to comply with FAIR data and Open Science standards. The field of AI and ML is developing at a staggering pace, making it impossible for non-specialists to stay up to date.

To enable the life science communities to benefit from AI/ML-powered image analysis methods, AI4Life builds bridges, providing urgently needed services on the common European research infrastructures. The project builds an open, accessible, community-driven repository of FAIR pre-trained AI models and develops services to deliver these models to life scientists, including those without substantial computational expertise. AI4Life's direct support and ample training activities prepare life scientists for the responsible use of AI methods, while contributor services and open standards drive community contributions of new models and interoperability between analysis tools. Open calls and public challenges provide state-of-the-art solutions to yet unsolved image analysis problems in the life sciences.

The AI4Life consortium brings together AI/ML researchers, developers of popular open-source image analysis tools, providers of European scale storage and compute services and European life sciences Research Infrastructures -- all united behind the common goal of enabling life scientists to fully benefit from the untapped but potentially tremendous power of AI-based analysis methods.