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Hand-picked articles showcasing the best of LLM practice
Compare DeepSeek V3 vs Llama 4 architecture: MLA vs GQA attention, MoE vs dense models. Learn how 671B parameters run at 37B speed. Includes code examples and design trade-offs.
Complete guide to Transformer architecture: self-attention mechanisms, encoder-decoder design, and how Transformers power GPT, BERT, and modern LLMs. With code examples and visual diagrams.
Compare 7 LLM sampling methods: Top-P (Nucleus), Temperature, Beam Search, Min-P, Mirostat. Fix repetitive outputs, improve quality. Includes parameter tuning guide for GPT/Claude/Gemini.
Fresh insights and practical techniques
DeepSeek-V3.2 rivals Gemini 3.0-Pro with 3 breakthrough innovations: DSA sparse attention, scalable RL framework, and 85K+ agent training tasks. Compare V3.2 vs Speciale for your use case.
Discover how AI inference engines evolved from edge-optimized CNNs to cloud-scale LLMs. Learn the key differences between vLLM, TensorRT-LLM, and traditional frameworks like MNN and TVM in this comprehensive 2025 guide.
Compare the top 10 AI models of 2025 including Claude Opus 4.5, GPT-5.1, Gemini 3 Pro, and Grok 4.1. Real pricing data, benchmark results, and use case recommendations. Updated November 2025.
OpenAI co-founder Ilya Sutskever declares the 'Age of Scaling' is over in exclusive interview. Discover why pre-training limits are here, what's next for AI research, and SSI's mission for safe superintelligence.
xAI launches Grok 4.1 with 2M context window, 3x lower hallucination rate, EQ-Bench3 #1 ranking, and ultra-affordable API pricing at $0.20 input/$0.50 output per 1M tokens. Full performance breakdown & pricing guide.
Google Gemini 3 Pro tops LMSYS Arena with record 1501 Elo score and dominates GPT-5.1 on AGI-critical benchmarks including Humanity's Last Exam (37.5% vs 26.5%) and ARC-AGI (45.1%), while achieving 100% on AIME 2025 with code execution.
Practical wisdom from the intersection of research and production
Every technique shared comes from real production systems handling millions of requests. No theoretical fluff, just what works.
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