OCC 2025 - Drivers, IRC, 3D and a more fitting keyboard and mouse
82mhz.net·11h
🕸️WASM Archives
spdk/spdk
github.com·2d
🔩Systems Programming
I don't think LLM's are making us stupider
news.ycombinator.com·3d·
Discuss: Hacker News
📏Code Metrics
Show HN: I built an AI tool to retrieve technical achievements from your GitHub
git-achievements.com·4d·
Discuss: Hacker News
🌀Brotli Internals
[R] Deep-dive into RoPE and why it matters
reddit.com·1d·
Discuss: r/MachineLearning
🦠Parasitic Compression
Help Request: Best way to run many chrome profiles in parallel
reddit.com·13h·
Discuss: r/homelab
🔄Sync Engine
How much attention do you need, really? Experiments in O(1) task completion
notion.so·1d·
Discuss: Hacker News
🌀Brotli Internals
Show HN: Local Lens – MCP that captures logs and network reqs for debugging
github.com·11h·
Discuss: Hacker News
👁️Observatory Systems
A Single-Case Study: Using Grok 4 to Reframe a “Beauty Analysis” Prompt for ChatGPT o3
dev.to·1d·
Discuss: DEV
🏛Digital humanities
A Data-Driven Review of Remote Sensing-Based Data Fusion in Precision Agriculture from Foundational to Transformer-Based Techniques
arxiv.org·7h
🧠Machine Learning
"high level" languages are easier to optimize
jyn.dev·2d·
Discuss: Hacker News
🔨Compilers
Managing Amazon Q Developer Profiles and Customizations in Large Organizations
aws.amazon.com·21h
🦋Format Metamorphosis
DOM Serialization for AI Testing: Why We Bet on Structure Over Screenshots
dev.to·15h·
Discuss: DEV
⚡Proof Automation
Maneuver Detection via a Confidence Dominance Maneuver Indicator
arxiv.org·1d
📊PCAP Analysis
A Practical Two-Stage Recipe for Mathematical LLMs: Maximizing Accuracy with SFT and Efficiency with Reinforcement Learning
arxiv.org·1d
💻Local LLMs
Recursive Reward Aggregation
arxiv.org·1d
🔲Cellular Automata
🚀 Is Mojo Really 1,000,000x Faster Than Python3?
dev.to·1d·
Discuss: DEV
📏Code Metrics
Transitioning from Linux to FreeBSD
discoverbsd.com·1d
🔌Operating system internals
Building a Simple Router with OpenBSD
discoverbsd.com·23h
🐡OpenBSD
From Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer Research
arxiv.org·7h
🧠Machine Learning