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📡 Network Protocol Design

TCP/IP, BGP, DNS, Protocol Verification

Orchestra Conductors are Prompt Engineers
blog.charliemeyer.co·21h·
Discuss: Hacker News
🎧Learned Audio
How JIT builds of CPython work
savannah.dev·2d·
Discuss: Hacker News
📝Concrete Syntax
Guarding the herd – managing database servers at scale
engineering.monday.com·1d·
Discuss: Hacker News
🗄️Database Internals
Cisco Donates the AGNTCY Project to the Linux Foundation
linux.slashdot.org·2d
🏠Homelab Federation
Voting by mail: a Markov chain model for managing the security risks of election systems
arxiv.org·2d
📼Tape Combinators
Security platform: Socket expands security offering with Scala and Kotlin
heise.de·3d
💧Liquid Types
Supercharge Your Email Marketing with True AI Personalization
shaped.ai·2d
🎯Content Recommendation
From Nope to "Yes, Mom, I Applied." Or almost.
dev.to·16h·
Discuss: DEV
🚀Indie Hacking
Which AI Reigns? GPT‑4, Claude, LLaMA, Perplexity & AI Studio
dev.to·31m·
Discuss: DEV
🤖AI Curation
RLVMR: Reinforcement Learning with Verifiable Meta-Reasoning Rewards for Robust Long-Horizon Agents
arxiv.org·1d
🔲Cellular Automata
Cloud storage
reddit.com·3h·
Discuss: r/kubernetes
💿WORM Storage
Sophos named a Leader in the 2025 Frost Radar™ for Managed Detection and Response
news.sophos.com·21h
🖥️Modern Terminals
Comparing Cluster-Based Cross-Validation Strategies for Machine Learning Model Evaluation
arxiv.org·1d
🧠Machine Learning
Clean numerical simulation (CNS) of three-dimensional turbulent Kolmogorov flow
arxiv.org·3d
🔗Tailscale
Helping or Homogenizing? GenAI as a Design Partner to Pre-Service SLPs for Just-in-Time Programming of AAC
arxiv.org·2d
🎙️Whisper
Python Automation Testing Guide
dev.to·1d·
Discuss: DEV
🧪Property-Based Testing
Deep-Dive Reports on Leading Topics in AI and Digital Modernity
dev.to·2d·
Discuss: DEV
🌀Brotli Internals
Building AI Agents: Choose your fighter
dev.to·1d·
Discuss: DEV
⚡Proof Automation
Prompt template for a fictitious LLM agent in a content-flagging experiment
arxiv.org·2d
🎨Nordic Design
FedCVD++: Communication-Efficient Federated Learning for Cardiovascular Risk Prediction with Parametric and Non-Parametric Model Optimization
arxiv.org·7h
🤐Secure Multiparty
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