36 related articles

A systematic learning path for understanding the Kimi K3 technical report, covering MoE, MLA, distributed training, and modern post-training techniques.

An in-depth look at the real daily work of data scientists, MLEs, and MLOps engineers — covering responsibilities, essential tools, and career paths to help you find your direction in AI.
JAX Host Offloading: A Practical Guide…
Memory capacity is the core bottleneck in LLM training. This guide explores JAX-based host offloading — covering optimizer state offloading, activation strategies, PCIe bandwidth trade-offs, and how it complements activation recomputation.

A deep dive into distributed AI systems engineering: data/model/tensor parallelism for training, KV cache, quantization, elastic scaling for inference, and cloud deployment with Kubernetes, Ray, and DeepSpeed.

A deep dive into the five genuinely tough challenges of production MLOps: fault-tolerant training on Spot instances, cross-team GPU scheduling, data reproducibility, model observability, and inference cost optimization.

NYT accuses OpenAI of faking inability to search training data and hiding billions of logs. A deep dive into the allegations, legal implications, and impact on AI copyright compliance.

Unsloth v0.1.461-beta fixes local GGUF vision model loading on llama-server in Studio, adds variant directory companion file lookup for stable multimodal deployment.

NVIDIA introduces Nonuniform Tensor Parallelism, letting GPUs bear different compute loads so training can continue without checkpoint rollback during hardware failures—boosting LLM training Goodput and fault tolerance at scale.

A complete guide to reproducing GitHub projects from scratch: due diligence, virtual environments, dependency installation, script interpretation, and breakpoint debugging — helping grad students and junior developers run others' code efficiently.

A deep dive into core challenges and key technologies for LLM infrastructure, covering GPU cluster management, inference optimization, distributed training, cost control, and observability.
TutorialsIn-depth analysis of Google's Gemma 4 open-source models: 31B, 26B MOE, and 14B/12B benchmarks, deployment guides for all platforms, and MS-Swift fine-tuning tutorial for building local Agent workflows.
TutorialsStep-by-step tutorial to deploy Hermes Agent with Qwen3.6 open-source LLM locally. Covers WSL setup, model download, Telegram bot integration for a zero-cost private AI Agent.
TutorialsDeep dive into NVIDIA NCCL Inspector for real-time GPU cluster communication monitoring with Prometheus integration, covering straggler detection, alerting, and Grafana visualization for distributed training optimization.
Product ReviewsDeep dive into Cube Studio, Tencent Music's open-source one-stop AI platform, covering architecture design, distributed training, large model fine-tuning and inference, and domestic chip adaptation.
TutorialsComplete WSL2 installation tutorial covering enabling Windows features, installing Ubuntu 22.04, and migrating to a non-system drive. Includes PowerShell commands and user configuration for AI developers.
Product ReviewsDeep dive into Tencent Music's open-source Cube Studio cloud-native AI platform, covering distributed training, LLM fine-tuning & inference, Pipeline orchestration, and domestic hardware adaptation.
Product ReviewsUnsloth is an open-source LLM training tool with 63K+ GitHub stars, supporting Gemma 4, Qwen 3, DeepSeek. Reduces VRAM by 50–80%, enabling RTX 4090 to fine-tune 7B models with a no-code Web UI.
Product ReviewsDeep dive into Tencent Music's open-source Cube Studio cloud-native AI platform, covering Notebook development, Pipeline orchestration, distributed training, LLM fine-tuning, inference deployment, and domestic hardware adaptation for full MLOps lifecycle.
Product ReviewsDeep dive into the GitHub 8000+ star project awesome-LLM-resources, covering LLM training, multimodal generation, AI Agents, MCP protocol, AI-assisted coding, and more for developers.
Deep DivesExplore Hugging Face Transformers, the 160K-star open-source AI framework powering text, vision, audio, and multimodal models with elegant APIs and massive community support.