30 related articles

Exploring the core principle of separating object identity from representation in software design, covering interfaces, ECS, DDD, and distributed systems.

A deep dive into the complete workflow of training a 1.3B parameter LLM from scratch, covering Transformer architecture design, data preparation, and distributed training optimization.

The Go team proposes new generic collection types under container/, including Set, ordered Map, queues, and more. A deep dive into the proposal and its design trade-offs.

Colibri uses MoE hot-cold separation and 4-bit quantization to run 744B-parameter models like GLM 5.2 on consumer hardware. Learn about its three-tier memory architecture and speculative decoding.

A deep dive into building high-performance lock-free queues with modern C++, covering CAS atomic operations, memory ordering, Michael-Scott algorithm, ring buffers, ABA problem solutions, and memory reclamation mechanisms.

DeepSeek's paper 'Thinking with Visual Primitives' was online for just 4 hours before being pulled. It uses bounding boxes and points as reasoning primitives, letting models 'point at' images to outperform GPT, Gemini, and Claude on maze navigation and counting.
Can LLMs Really Understand Computer Ar…
Can LLMs truly understand computer architecture papers? This article analyzes core challenges—from surface pattern matching to deep reasoning—and defines their capability limits for researchers.

Bernini is a ComfyUI video super-resolution node package using Tile Split/Select/Merge to solve seams, drift, and VRAM overflow. Benchmarked at 325s for 39 frames at 1920×1080.
Why Tokio and Rayon Don't Mix Well: A …
Why mixing Tokio and Rayon in Rust async code causes performance traps, how spawn_blocking isolates blocking tasks, and the key difference between concurrency and parallelism.

A deep dive into two frontier dense retrieval works: Hobbit uses gradient analysis to automatically construct hard batches; Disco replaces single-document competition with submodular collaborative coverage, reshaping Top-K retrieval.
CUDA Kernel Fusion: A Practical Guide …
Learn how CUDA Kernel Fusion merges multiple GPU kernels to reduce global memory traffic and launch overhead, with real-world examples from AI inference and deep learning.
Flash-MSA: How Sparse Attention Kernel…
Flash-MSA uses GPU sparse attention kernels to reduce complexity from O(n²) to near-linear, tackling the compute bottleneck of million-token LLM training.

A developer builds a 3D editor from scratch in C++, modeling programs as dataflow graphs rather than object collections. Exploring dataflow vs. OOP, Greenspun's Tenth Rule, and the debugging dividend of visual programming.

SiliconLLM builds a CPU-native LLM architecture from scratch, combining selective SSM, ternary (1.58-bit) LUT MLP, and granular MoE, co-designed around the L3 cache bandwidth cliff. Ternary kernels show 4-5x speedup over fp32.

An in-depth look at the core design challenges of MPMC queues: bounded waiting, lock-free mechanisms, sequence-number slots, dual-path strategies, and helping. Helping engineers balance throughput, fairness, and latency.

A deep dive into the Claude Code source code, systematically analyzing the five-layer Harness Engineering architecture: environment, tool, control, memory, and evaluation. Build a stable runtime system for production AI Agents.

meshoptimizer is a lightweight C++ open-source library offering vertex cache optimization, overdraw reduction, mesh compression, quantization, and LOD simplification for game engines, WebGL, and glTF pipelines.

Explore the math behind the Triple Dragon Fractal: from paperfolding dragon curves to L-systems, threefold symmetry, Hausdorff dimension, and fractal programming.

A YouTuber spent 24 hours learning Rust from zero with no AI tools, mastering ownership, borrowing, and a game engine to build a complete Brick Breaker game. Full account of every challenge.

Ternlight is a 7MB WebAssembly-based browser-side text embedding model requiring no server or GPU. Explore its tech, use cases, and tradeoffs for private, offline semantic search.