Modern Toasts Using the Native Popover API
telebugs.com·17h·
Discuss: Hacker News
✍️Prompt Engineering
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Cure - Verification-First Programming for the BEAM
cure-lang.org·1d·
Discuss: Lobsters
⚡Model Efficiency
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On this day in 1988, the Morris worm infected 10% of the Internet within 24 hours — worm slithered out and sparked a new era in cybersecurity
tomshardware.com·18h·
Discuss: Hacker News
🔓Hacking
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Horror Coding Stories: Therac-25
read.thecoder.cafe·4d·
Discuss: r/programming
✍️Prompt Engineering
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Inline vs. Pipeline Ray Tracing
evolvebenchmark.com·18h·
Discuss: Hacker News
⚡Model Efficiency
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The ZeroAccess Developer and His Windows Kernel-Mode Debugger
r136a1.dev·2d·
Discuss: Hacker News
🔓Hacking
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Balancing Cost, Power, and AI Performance
oreilly.com·14h
⚡Model Efficiency
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C++ move semantics from scratch (2022)
cbarrete.com·1d·
Discuss: Lobsters, Hacker News
🗄️SQLite
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How LLMs Cheat: Modifying Tests and Overloading Operators
enbao.me·1d·
Discuss: Hacker News
✍️Prompt Engineering
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Why Engineers Can't Be Rational About Programming Languages
spf13.com·1d·
Discuss: Lobsters, Hacker News
✍️Prompt Engineering
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The world’s tallest chip defies the limits of computing: goodbye to Moore’s Law?
english.elpais.com·16h·
Discuss: Hacker News
✍️Prompt Engineering
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Enhanced Slater Determinant Calculation via Hybrid Tensor Decomposition & Adaptive Mesh Refinement
dev.to·2d·
Discuss: DEV
⚡LLM Optimization
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How to Build a RAG Solution with Llama Index, ChromaDB, and Ollama
dev.to·1h·
Discuss: DEV
⚡LLM Optimization
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From Vulnerable to Production-Ready: A Real-World Security Hardening Journey
dev.to·14h·
Discuss: DEV
🔓Hacking
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Nonlinear Instabilities in Computer Network Dynamics
arxiv.org·3h
🔓Hacking
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Tech With Tim: Build a Python AI Agent in 10 Minutes
dev.to·22h·
Discuss: DEV
🤖AI
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Day 2 of building Secrin
dev.to·5h·
Discuss: DEV
📊Data Visualization
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TypeScript Rewrote Itself in Go?! What That “10x Faster” Hype Really Means
dev.to·16h·
Discuss: DEV
🛠️Developer Tools
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Disciplined Biconvex Programming
arxiv.org·1d
⚡LLM Optimization
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Efficiency vs. Alignment: Investigating Safety and Fairness Risks in Parameter-Efficient Fine-Tuning of LLMs
arxiv.org·1d
⚡LLM Optimization
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