Type Systems, Compiler Theory, Syntax Evolution, Memory Models, Syntax Creation, Parser Design, Domain Languages, Programming Paradigms

"Think" in Japanese
languagelog.ldc.upenn.eduยท1d
๐Ÿ‡จ๐Ÿ‡ณChinese Computing
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Explicit Lossless Vertex Expanders!
gilkalai.wordpress.comยท4d
๐Ÿ’ŽInformation Crystallography
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The Double Education of My Twins' Chinese School (2023)
newyorker.comยท5hยท
Discuss: Hacker News
๐Ÿ‡จ๐Ÿ‡ณChinese Computing
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This one weird trick makes the AI a better writer.
blog.fsck.comยท2d
โšกProof Automation
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Managing Product Design Teams
designsystems.internationalยท1dยท
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๐ŸŽจNordic Design
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Transforming the physical world with AI: the next frontier in intelligent automation
aws.amazon.comยท1d
๐Ÿ Homelab Orchestration
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Advise Needed !!
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Discuss: r/homelab
๐Ÿด๓ ง๓ ข๓ ณ๓ ฃ๓ ด๓ ฟScottish Computing
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How Generative AI Gives Newcomers an Edge Over Experts
hackernoon.comยท12h
๐ŸŒCultural Algorithms
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Abstraction for Abstractionโ€™s Sake: How Developers Talk Themselves Into Complexity
hackernoon.comยท6d
๐ŸงฌFunctional Programming
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Show HN: Using Haskell to write an NES emulator
github.comยท3dยท
Discuss: Hacker News
๐Ÿ•นEmulation
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Ask r/kubernetes: What are you working on this week?
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Discuss: r/kubernetes
๐Ÿ”ฉSystems Programming
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Stress-Testing Model Specs Reveals Character Differences among Language Models
arxiv.orgยท5d
๐Ÿ“‹Document Grammar
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CoMAS: Co-Evolving Multi-Agent Systems via Interaction Rewards
arxiv.orgยท5d
๐Ÿ”ฒCellular Automata
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SPAD: Specialized Prefill and Decode Hardware for Disaggregated LLM Inference
arxiv.orgยท5dยท
Discuss: r/LLM
๐Ÿ’ปLocal LLMs
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Title: Understanding the Mysterious "return increment" in Python Functions
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๐Ÿ‘‘Isabelle
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Unlocking the Power of AI in Your Development Workflow: Practical Insights and Tools
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๐Ÿ”„Language Evolution
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Hierarchical Bayesian Flow Networks for Molecular Graph Generation
arxiv.orgยท1d
๐Ÿ”„Graph Rewriting
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Tech With Tim: ULTIMATE AI Coding Tutorial with Warp Code
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๐ŸŽฌWebCodecs
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Tech With Tim: Why 1M People Tried This AI Coding Tool (Full Vibe Coding Tutorial)
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๐ŸŒ€Brotli Internals
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AI-Driven Retention Time Prediction for Complex Peptide Mixtures via Gradient Boosting and Multi-Dimensional Optimization
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๐Ÿ”Vector Forensics
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