Learnings from a landscape analysis of AI/ML infrastructure opportunities and challenges

AI is increasingly integrated into scientific discovery. It augments and accelerates research, helping scientists generate hypotheses, design experiments, collect and interpret large datasets, and gain insights that might not have been possible using traditional scientific methods alone. Australia is both safety-centric and behind in the adoption of generative AI. This work takes a progressive posture mapping out a strategy for disruptive, scaled-out, safe and sustainable generative AI participation and adoption by the omics community. As a naturally data-centric enabler of research infrastructure, Bioplatforms Australia (BPA) has embarked on a mission to understand AI s impact on the omics community (genomics, proteomics, metabolomics, and synthetic biology are BPA s focus areas) and the role AI will play in the advanced utility of increasingly integrated laboratory data outputs. It seeks to ensure impact through AI adoption by its partner infrastructure facilities, data framework initiatives, and platform capabilities (BioCommons). We ve invited friends from structural biology, geoscience and nanoparticles to contribute their recent learnings. What discoveries will be made because of AI? How and why do partner facilities adopt AI innovation? How are big-tech, pharma, and investment ecosystems changing the roles and opportunities for our research ecosystem? What are the workforce needs? What are the data needs? What do we require from the DRI? Do we need / when do we need an AI factory? What does a re-imagined ecosystem of industry, researchers, and research infrastructure look like? This BoF will briefly share what we have learned from our journey thus far. A panel of selected stakeholders will discuss the nature of the change being faced by infrastructure enablers.