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🔮 AI prompt engineering tools
Infinite Mac Construction Set
blog.persistent.info·5d·
Discuss: blog.persistent.info, Lobsters, Hacker News
⌨️Prompt Engineering
Show HN: YUPE – AI-powered app that removes language barriers from restaurants
yupe.app·4d·
Discuss: Hacker News
🤖AI
Practical Bitwise Tricks in Everyday Code (Opinioned)
maltsev.space·3d·
Discuss: r/programming
🏡Local running LLMs
guile lab notebook: on the move!
wingolog.org·5d·
Discuss: Lobsters, Hacker News, r/programming
⌨️Prompt Engineering
Show HN: A generative audio VST plugin using Gemini API, JUCE, and React
news.ycombinator.com·4d·
Discuss: Hacker News
⌨️Prompt Engineering
Modeling CORS frameworks with CodeQL to find security vulnerabilities
github.blog·3d
🏡Local running LLMs
I created a Python library for derivatives pricing and quantitative finance
reddit.com·4d·
Discuss: r/programming
🏡Local running LLMs
Building the Hugging Face MCP Server
huggingface.co·4d·
Discuss: Hacker News
🏡Local running LLMs
Digital Wargames to Enhance Military Medical Evacuation Decision-Making
arxiv.org·4d
⌨️Prompt Engineering
Robust Speech-Workload Estimation for Intelligent Human-Robot Systems
arxiv.org·5d
🏡Local running LLMs
LumiCRS: Asymmetric Contrastive Prototype Learning for Long-Tail Conversational Movie Recommendation
arxiv.org·6d
🤖AI
Can adversarial attacks by large language models be attributed?
arxiv.org·4d
🏡Local running LLMs
Evolution without Large Models: Training Language Model with Task Principles
arxiv.org·5d
⌨️Prompt Engineering
Explainable Hierarchical Deep Learning Neural Networks (Ex-HiDeNN)
arxiv.org·5d
🤖AI
Red Teaming AI Red Teaming
arxiv.org·5d
🏡Local running LLMs
Towards integration of Privacy Enhancing Technologies in Explainable Artificial Intelligence
arxiv.org·6d
🏡Local running LLMs
Extracting ORR Catalyst Information for Fuel Cell from Scientific Literature
arxiv.org·3d
🤖AI
An overlapping domain decomposition method for parametric Stokes and Stokes-Darcy problems via proper generalized decomposition
arxiv.org·4d
🤖AI
Understanding Everything as Code: A Taxonomy and Conceptual Model
arxiv.org·6d
⌨️Prompt Engineering
How Much Content Do LLMs Generate That Induces Cognitive Bias in Users?
arxiv.org·6d
🏡Local running LLMs
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