Topographical sparse mapping: A training framework for deep learning models
sciencedirect.com·3d·
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Gullible bots struggle to distinguish between facts and beliefs
theregister.com·4d·
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How we built the demo for the Current NOLA Day 2 keynote using Flink and AI
rmoff.net·11h·
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Accumulating Context Changes the Beliefs of Language Models
lm-belief-change.github.io·1d·
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Making MCP Tool Calls Scriptable with mcp_cli
joshbeckman.org·11h·
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Intelligent end-to-end monitoring for AI agents
trysentinel.vercel.app·13h·
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A Week of Teaching
fivetwelvethirteen.substack.com·10h·
Discuss: Substack
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Planning > Agents: Getting Reliable Code from LLMs
repoprompt.com·3d·
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Who Wrote That Headline? Maybe a Robot.
nytimes.com·12h·
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Claude Code to manage engineering teams
devashish.me·9h·
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The future of LLMs: cognitive core and cartridges?
killerstorm.github.io·2d·
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Humans and neural networks show similar patterns of transfer and interference
nature.com·3d·
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Computational Turing Test Reveals Systematic Differences Between Human and AI Language
arxiv.org·1d·
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Show HN: Trying to Help Fellow Red Team Operators
github.com·15h·
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Reflection
alexpolozov.com·1d·
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OlmoEarth: A new state-of-the-art Earth observation foundation model family
allenai.org·3d·
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OpenAI Model Spec
model-spec.openai.com·1d·
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Why Python's deepcopy() is surprisingly slow (and better alternatives)
codeflash.ai·1h·
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LLM As A Judge is not the shortcut you think
softwaredoug.com·4d·
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Beyond Standard LLMs
magazine.sebastianraschka.com·3d·
Discuss: Hacker News, r/LLM
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