🧠 LLM Year in Review 2025: Shifts, Insights, and Emerging Paradigms
A thoughtful synthesis that blends technical trends and philosophical insights, offering a practitioner’s view of how large language models and human–AI interaction evolved in 2025.
Andrej Karpathy’s review surveys the defining AI shifts of 2025 — from the rise of Reinforcement Learning from Verifiable Rewards (RLVR) to the reimagining of LLMs as ‘ghosts’ instead of ‘animals.’ It highlights the evolution of natural-language-based coding tools like Cursor and Claude Code, and Google’s Gemini Nano as a step toward multimodal intelligence.
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💥 A Better Zip Bomb: Compression, Exploits, and Algorithmic Ingenuity
A benchmark in compression and security research—showing how deep algorithmic knowledge can expose and mitigate real-world vulnerabilities.
David Fifield’s seminal article dissects the design of non-recursive zip bombs that exploit overlapping data blocks to achieve staggering compression ratios over 28 million:1. It combines rigorous mathematical modeling with DEFLATE optimization insights, analyzing both security risks and parser resilience strategies.
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🌦️ NOAA Launches AI-Powered Global Weather Models
A landmark step in climate AI, underscoring the shift toward hybrid models that blend machine learning with physical simulations in Earth sciences.
NOAA introduces a new generation of AI-enhanced weather prediction systems that merge artificial intelligence with atmospheric science to improve the precision of global forecasts and extreme weather prediction.
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🔷 Understanding Dart Class Modifiers Through Lattice Theory
A mathematically elegant explanation that helps developers grasp Dart’s class semantics and design consistency through lattice visualization.
A deep exploration of Dart 3.0’s class modifiers—base, final, interface, and mixin—using lattice theory to map their logical relationships. The article explains how modifier combinations form a structured capability space that clarifies valid and invalid type hierarchies.
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🗄️ A Decade on Datomic – Davis Shepherd & Jonathan Indig (Netflix)
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