How can RPKI can be made quantum-safe?
blog.apnic.net·1d
🔐Quantum Security
CISO Conversations: How IT and OT Security Worlds Are Converging
darkreading.com·17h
🔓Hacking
AI Safety Course Intro Blog
windowsontheory.org·2d
🔲Cellular Automata
Unsupervised Learning NO. 490
newsletter.danielmiessler.com·1d
🖥️Terminal Renaissance
In Defense of Defensive Forecasting
argmin.net·1d·
Discuss: Hacker News
🔲Cellular Automata
Do You Really Know How `or` And `and` Work in Python?
thepythoncodingstack.com·5d
🔗Lisp
Swift and C++ Interoperability in Practice
arturgruchala.com·2d·
Discuss: Hacker News
✅Format Verification
Architecture Styles – Azure Architecture Center
learn.microsoft.com·21h·
Discuss: Hacker News
🔌Interface Evolution
Colodebug: A simple way to improve bash script debugging
johannes.truschnigg.info·2d·
Discuss: Hacker News
🐚Shell Optimization
Almost Always Auto (2013)
herbsutter.com·6d·
Discuss: Hacker News
🔒Type Safety
Where have the IMO gold medallists ended up, part four of three?
xquant.substack.com·1d·
Discuss: Substack
📐Proof Assistants
Mind the Gap: A Review of Arabic Post-Training Datasets and Their Limitations
arxiv.org·1d
⚙️Compression Benchmarking
Hallucination Score: Towards Mitigating Hallucinations in Generative Image Super-Resolution
arxiv.org·1d
📊Learned Metrics
FinSurvival: A Suite of Large Scale Survival Modeling Tasks from Finance
arxiv.org·1d
📐Archive Calculus
EPSilon: Efficient Point Sampling for Lightening of Hybrid-based 3D Avatar Generation
arxiv.org·2d
🏺Computational Archaeology
End-to-end Joint Punctuated and Normalized ASR with a Limited Amount of Punctuated Training Data
arxiv.org·1d
🗜️LZSS Variants
9 Leading Machine Learning Algorithms Powering AI Advancements
dev.to·8h·
Discuss: DEV
🧠Machine Learning
Strategically Robust Game Theory via Optimal Transport
arxiv.org·1d
🔲Cellular Automata
Persona-Based Synthetic Data Generation Using Multi-Stage Conditioning with Large Language Models for Emotion Recognition
arxiv.org·2d
⚙️Compression Benchmarking
Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning
arxiv.org·1d
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