AI's capabilities may be exaggerated by flawed tests, according to new study
nbcnews.com·1d·
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Continuous Autoregressive Language Models
shaochenze.github.io·2d·
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Show HN: Linguistic RL – A 7B model discovers Occam's Razor through reflection
github.com·3h·
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Topographical sparse mapping: A training framework for deep learning models
sciencedirect.com·2d·
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How to Build AI Agents from Scratch: A Strategic Guide for CEOs and CXOs
lightrains.com·5h·
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Forecasts of AI and Economic Growth
tecunningham.github.io·2h·
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Mathematical exploration and discovery at scale
terrytao.wordpress.com·1d·
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Reasoning with Sampling: Your Base Model Is Smarter Than You Think
aakaran.github.io·1d·
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Context Engineering 2.0: The Context of Context Engineering
arxiviq.substack.com·19h·
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Modern Optimizers – An Alchemist's Notes on Deep Learning
notes.kvfrans.com·12h·
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DS-STAR: A state-of-the-art versatile data science agent
research.google·1d·
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The Means of Prediction: How AI Works (and Who Benefits)
hks.harvard.edu·1d·
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AI Agent Guides from Google, Anthropic, Microsoft, etc. Released This Week
sarthakai.substack.com·20h·
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Neuromorphic Intelligence Promises a New Era of Brain-Like Sustainable AI
dailyneuron.com·5h·
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The Complexity Cliff: Why Reasoning Models Work Right Up Until They Don't
rewire.it·1d·
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Rubber Duck Debugging with LLMs: Why Explaining Your Problem Is the Solution
tidesofsea.com·7h·
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Learning to Model the World with Language
dynalang.github.io·18h·
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Teaching robots to map large environments
news.mit.edu·2d·
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AI Native Architecture: Intelligence by Design
sumant.bearblog.dev·1d·
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Show HN: TabPFN-2.5 – SOTA foundation model for tabular data
priorlabs.ai·23h·
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