Why Language Models Are “Lost in the Middle”
pub.towardsai.net·2h
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Adaptive AI: Making Edge Inference Smart and Fast by Arvind Sundararajan
dev.to·3h·
Discuss: DEV
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Nested Learning: The Illusion of Deep Learning Architectures
arxiviq.substack.com·7h·
Discuss: Substack
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Beyond Pipelines: A Survey of the Paradigm Shift toward Model-Native Agentic AI
paperium.net·8h·
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Using Knowledge Elicitation Techniques To Infuse Deep Expertise And Best Practices Into Generative AI
forbes.com·1d
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Just know stuff (or, how to achieve success in a machine learning PhD) (2023)
kidger.site·2d·
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Evaluating LLMs' Reasoning Over Ordered Procedural Steps
arxiv.org·19h
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Andrej Karpathy on LLM cognitive deficits
lesswrong.com·3h
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Enhancing maritime accident causation analysis through a hybrid machine learning approach
sciencedirect.com·7h
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Right-sized AI: Good for business, users, and the planet
web.dev·7h·
Discuss: Hacker News
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Import AI 434: Pragmatic AI personhood; SPACE COMPUTERS; and global government or human extinction;
importai.substack.com·10h·
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Fine-tune VLMs for multipage document-to-JSON with SageMaker AI and SWIFT
aws.amazon.com·4h
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Controlled Vocabularies
jessicatalisman.substack.com·19h·
Discuss: Substack
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Show HN: Charl – ML language with native tensors and autograd
charlbase.org·10h·
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🚨 Meta just dropped a breakthrough that could change how AI agents learn forever.
threadreaderapp.com·14h
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Context rot: the emerging challenge that could hold back LLM progress
understandingai.org·7h
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Annotation-Efficient Universal Honesty Alignment
paperium.net·15h·
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LLMs Talking in Tongues: A New Era of Semantic AI Collaboration?
dev.to·1d·
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Cracking the Code: Why AI Still Struggles with List Languages by Arvind Sundararajan
dev.to·1d·
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Deep Learning for Molecules and Materials
dmol.pub·15h·
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