Research Libraries UK

Digital Shift Forum – How can libraries make the most of open-source AI and machine learning?

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RLUK’s Digital Shift Forum brings together colleagues from across the information, research, cultural and heritage communities, and third and commercial sectors, to discuss the future of the digital shift in collections, services, and audiences.

The series aims to promote cross-sector discussion and debate, to enable knowledge exchange, and inspire collaborative endeavour across sectors and communities, for the benefit of RLUK members and the wider research and information management communities.

The Digital Shift Forum is open to all, and you do not need to belong to an RLUK member institution to attend or participate.

New Digital Frontiers  – How can libraries make the most of open-source AI and machine learning?

Wednesday 3 July 2024, 14:00 – 15:00 (BST), 15:00 – 16:00 (CEST/SAST), 16:00 – 17:00 (EEST), 09:00 – 10:00 (EDT), 21:00 – 22:00 (AWST/CST)

New Digital Frontiers will explore the role AI and Machine learning can play in our libraries, the platforms we use, the challenges we face and the opportunities we have.

There is currently a lot of interest in libraries regarding the use of AI. Much of this enthusiasm comes from the increasing capabilities of generative AI systems. Vendors are increasingly offering “AI-enabled” products and services, and people across all sectors and industries are eager to “do something with AI.” In this discussion, Daniel will explore practical ways in which libraries can leverage AI and machine learning, and why this often doesn’t necessitate the use of generative AI. Daniel will also advocate for more libraries to consider adopting and contributing to open-source AI.

Daniel van Strien is a Machine Learning Librarian at Hugging Face, a startup focused on democratising good machine learning. Before joining Hugging Face, Daniel was a Digital Curator for the Living with Machines project at the British Library. Daniel has a strong interest in the role AI can play in libraries and how libraries and concepts from library science can contribute to creating a healthier machine learning ecosystem.

 

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