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🎄🎅VAM! Christmas Edition AI Reading Group🎅🎄: Nested Learning: The Illusion of Deep Learning Architectures
📄 Paper: “Nested Learning: The Illusion of Deep Learning Architectures”
🎤 Presenter: Nimitha Gopinath
🔗 Link: https://abehrouz.github.io/files/NL.pdf
To maximize engagement, please try to read the paper in advance.
✨ Summary: This paper introduces Nested Learning (NL), a framework that represents a model and its training as nested, multi-level optimization processes with their own “context flows.” NL explains how in-context learning emerges in large models and motivates more expressive optimizers, a self-modifying sequence model, and a new continuum memory system. These ideas are combined in HOPE, a continual learning module that shows promising results in language modeling, continual learning, and long-context reasoning.
🎅 🎄Festive twist: Feel free to come in your coziest Christmas sweater 🎁 and we might have little goodie bags with chocolates to keep the discussion extra sweet. 🍫✨🎄
Want to present?
The list of papers will be available here: https://docs.google.com/spreadsheets/d/1HET5sjnHjwiF3IaCTipR_ZWspfgglqwdBFRWAfKBhp8/edit?usp=sharing
To connect with the group, join the Discord: https://discord.gg/teJvEejs94
Timeline:
🕠 6:30 PM – Arrival & Networking.
🗣️ 6:45 PM ~ 7:15 – Paper Presentation
🗣️ 7:15 PM - Discussions
About the Facilitator
Issam Laradji is a Research Scientist at ServiceNow and an Adjunct Professor at University of British Columbia. He holds a PhD in Computer Science and a PhD from the University of British Columbia, and his research interests include natural language processing, computer vision, and large-scale optimization.
Looking forward to discussing the latest AI Papers!
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