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Writer's pictureSteve Quenette

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

It is that time of the year when those #enabling the #digital aspects of #research get together - eResearch Australasia 2024 in Melbourne. It is also timely, as the National Research Digital Infrastructure (NDRI) working group has been surveying the community.


This year, our contribution to the conference is putting together a BOF entitled: Learnings from a landscape analysis of AI/ML infrastructure opportunities and challenges.


Building on our work with Bioplatforms Australia this year, the BOF expands to explore recent learnings in other research domains. The panel include Amanda Barnard (Deputy Director at ANU's School of Computing), Andrew Gilbert (CEO of Bioplatforms Australia), Tim Rawling (CEO of AuScope), and Kate Mitchie (Chief Scientist at UNSW's Structural Biology Facility).


Come join us from 11:25 to 12:45 on Wednesday, 30th October, where we explore how these communities are beginning to create an environment for success in the generative AI era.





Abstract

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.

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