July 24, 2025 : Issue #95
lawrenceweschler.substack.com·2d·
Discuss: Substack
🌈Holographic Archives
18 months. 12,000 questions. A whole lot of anxiety. What I learned from reading students’ ChatGPT logs
theguardian.com·7h
🏴󠁧󠁢󠁳󠁣󠁴󠁿Scottish Computing
Berlin celebrates Pride parade with techno beats and rainbow flags
the-independent.com·23h
📼Cassette Culture
Ethical imperatives in the commercialization of brain-computer interfaces
papers.ssrn.com·1d·
Discuss: Hacker News
⚖️Emulation Ethics
How We Rooted Copilot
research.eye.security·1d·
Discuss: Hacker News, Hacker News, r/linux
🔌Operating system internals
It Takes a Village: Bridging the Gaps between Current and Formal Specifications for Protocols
cacm.acm.org·3d
🌐NetworkProtocols
Multi-Model and Multi-Agent Is the Future
mainfunc.ai·3d·
Discuss: Hacker News
🔲Cellular Automata
Hackaday Podcast Episode 330: Hover Turtles, Dull Designs, and K’nex Computers
hackaday.com·1d
⚡Circuit Archaeology
Dwm Commented
github.com·1d·
Discuss: Hacker News
❄️Nixpkgs
LLMs remain vulnerable to "jailbreaking" through adversarial prompts
link.springer.com·3d·
Discuss: Hacker News
💻Local LLMs
A Beginner’s Guide to Channel Attribution Modeling in Marketing (using Markov Chains, with a case study in R)
dev.to·3d·
Discuss: DEV
🎯Arithmetic Coding Theory
The Algorithmic con: Is Our AI-Powered World Becoming The Matrix?
hackernoon.com·2d
🧲Magnetic Philosophy
Cryptocurrency Price Movements as Predictors of Virtual LAND Valuations
hackernoon.com·20h
🧬Bitstream Evolution
🚀 Just discovered this evening productivity hack:
dev.to·14h·
Discuss: DEV
⛏️File Carving
Today's productivity insight:
dev.to·14h·
Discuss: DEV
🏺ZIP Archaeology
Show HN: Mcp-chromautomation – Chrome MCP that is not a puppeteer
github.com·18h·
Discuss: Hacker News
🕸️WebAssembly
🌟 Ask a Philosopher: Voice AI Agent Powered by AssemblyAI and Gemini
dev.to·1d·
Discuss: DEV
🌀Brotli Internals
The Complete DevOps Roadmap for 2025 🚀
dev.to·23h·
Discuss: DEV
❄️Nix Adoption
What is Machine Learning?
dev.to·11h·
Discuss: DEV
🧠Machine Learning
Exploring the Frontiers of kNN Noisy Feature Detection and Recovery for Self-Driving Labs
arxiv.org·3d
🧠Machine Learning