GDG AI for Science - Australia
Let's explore how Aeneas could transform how historians connect the past
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Join the GDG AI for Science community to explore Aeneas, the artificial intelligence model from Google DeepMind designed to contextualise ancient inscriptions. Historically, identifying "parallels" in ancient texts has been a complex and time-consuming task for historians, especially when dealing with fragmentary or defaced inscriptions. Aeneas significantly accelerates this work by reasoning across thousands of Latin inscriptions, retrieving textual and contextual parallels in seconds. This allows historians to interpret and build upon the model's findings, providing richer insights into the diversity of everyday life in the Roman world.
In this collaborative session, we will unpack the capabilities of Aeneas to understand:
What Aeneas is: The first AI model designed to contextualise ancient inscriptions.
How it works: Reasoning across vast collections of Latin inscriptions to find textual and contextual parallels.
What Aeneas is capable of: Searching for parallels, processing multimodal input (text and images) for geographical provenance, and restoring gaps in texts. Aeneas has shown state-of-the-art performance in restoring damaged texts and predicting when and where they were written.
How to use it: We can demo the freely available interactive version for researchers, students, educators, and museum professionals, as well as its open-sourced code and dataset for further research on your data.
Its impact and limitations: How Aeneas aids in interpreting isolated fragments, draws richer conclusions, and offers a new quantitative way to engage with historical debates.
Whatever else?
This is a virtual facilitated session, interaction and active participation is encouraged. Discussion is aimed to go where we deem interesting.
This event is ideal for anyone interested in AI, history, classics, and digital humanities, including researchers, developers, students, and academics.
Prerequisites:
Read the DeepMind blog post.
Read the Nature article.
Explore the online demos in Latin and Greek.
Have a Google account to follow along examples in the interactive Google Colab Notebook (we will slowly guide everyone through this).
Fill in our community survey to express your ideas.
Science Catalyst Program Manager
Monash University
Organizer
Haizea Analytics
Organizer
Monash University
Organizer
Macquarie University
Macquarie University
The University of Queensland
University of Queensland
Science Catalyst Program Manager
University of Sydney
University of Sydney
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