Frontier tech insights and engineering notes on GPT-5.4, Claude 4.6, and Gemini 3.1
Curated in-depth articles
Stop theorizing, start quantizing. From downloading pre-quantized models, to hands-on weight compression with AWQ/GPTQ/GGUF, to vLLM FP8 zero-calibration production deployment and QLoRA fine-tuning—four routes, each with complete copy-paste code.
Read Full Article →Explore the latest trends and deep analysis in AI tech
Cease the obsession with writing more code; shift focus to deep evaluation thinking. We deconstruct LLM-as-a-Judge biases, the mathematics behind metrics, and reshaping CI/CD defenses for probabilistic systems.
Read Full Article →A retrospective of six pivotal technology crossroads in AI's seventy-year history, dissecting the compute constraints, data dividends, and scalability logic behind each historical choice.
Read Full Article →A deep dive into vLLM's core architecture (PagedAttention, continuous batching, APC prefix caching, speculative decoding) for online serving. Covers OpenAI-compatible API setup, performance tuning, token billing systems, and complete Docker deployment with Prometheus monitoring.
Read Full Article →A deep dive into the complex Linux NVIDIA GPU driver package structures. Understand the 5-layer architecture bridging nvidia-dkms, libnvidia, nvidia-utils, and driver metapackages. Plus, discover enterprise best practices and troubleshooting guides for 4 core deployment scenarios, including Docker model servers and DGX clusters.
Read Full Article →A comprehensive comparison of FP32, BF16, FP16, FP8, INT8, INT4, NF4, FP4, 1.58-bit and all major quantization formats — with real benchmark data and an in-depth FP8 vs INT8 technical analysis.
Read Full Article →Based on a real data analysis agent project, this article distills 7 reusable Agent Runtime practices covering state exposure, tool design, context control, guardrails, delegation, and trace-driven iteration.
Read Full Article →A panoramic view of the capabilities of the top 3 AI models
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Dedicated to technical research and practical sharing in the field of AI large models.
Recording the development context of frontier technologies and exploring the application boundaries of artificial intelligence.