#GPU fault tolerance
65 related articles
·6 min
AI Agent Learning Roadmap: A Four-Stage Guide from Beginner to Practical Mastery
A systematic AI Agent learning roadmap in four progressive stages: fundamentals → ReAct core paradigm → memory & tools → multi-agent collaboration. Master LangChain, AutoGen, and more, growing from beginner to practical developer in three months.
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·5 min
A Programmer's Guide to Large Language Models: The Complete Path from Prompts to Agents
A tailored large-model learning path for ordinary programmers: from prompt engineering, API calls, and LangChain, to RAG, Agents, fine-tuning, and enterprise deployment—six steps to build AI application skills fast.
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·5 min
Nonuniform Tensor Parallelism: NVIDIA's New Fault-Tolerance Approach to Boost LLM Training Goodput
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.
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·4 min
NVFP4 Quantization in Practice: A Guide to Compressing Large Models with NVIDIA Model Optimizer
Deep dive into NVFP4 quantization: using NVIDIA Model Optimizer to compress Nemotron 3 Ultra to FP4 checkpoints, reducing memory by 75% and boosting inference throughput on Blackwell GPUs.
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·6 min
LangChain + MCP in Practice: A Pitfall-Avoidance Guide to LLM Selection and Local Deployment
DeepSeek R1 lacks Function Calling and JSON Output by default. Qwen3's programmable thinking modes make it the top open-source agent choice. Key LLM selection pitfalls and MCP protocol updates.
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·5 min
Tracking a Year-Long Crash Mystery: A Complete Investigation of Hardware Defects and an 18-Year-Old Open Source Bug
An engineering team spent a year tracing crashes to two root causes: a silent hardware defect and an 18-year-old open source bug. A deep dive into debugging methodology for distributed systems.
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·3 min
Running Local LLMs on AMD GPUs: Ditching Ollama for LM Studio Delivers 7x Speed Boost
AMD GPU black screens running local LLMs? This post-mortem covers Ollama's 3 fatal flaws and how switching to LM Studio boosted token speed from 5 to 36, with ROCm setup, Speculative Decoding, and GFX version tips.
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·4 min
OpenAI Agents SDK in Practice: Harness and Sandbox Separation Architecture Explained
Deep dive into OpenAI Agents SDK updates covering Harness-Compute separation, Codex-style orchestration, sandbox snapshots, skills system, and multi-agent collaboration with practical demos.
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·1 min
Google TPU: Five Generations Decoded — From v2 to Ironwood, a 30x Leap in Energy Efficiency
Deep dive into Google's latest paper tracing TPU v2 to Ironwood: 36x chip scaling, 30x energy efficiency gains, 3D Torus interconnects, liquid cooling, and resilience design.
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·3 min
The Complete Skill Map for AI Application Engineers: A Progressive Roadmap from Fundamentals to Production
A systematic breakdown of the complete skill structure for AI application engineers, covering Python & deep learning fundamentals, small model engineering, LLM fine-tuning, Agent development, and enterprise projects.
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·4 min
From Vibe Coding to AI-Engineered Programming: A Practical Guide to Three Levels of Mastery
A deep dive into three levels of AI programming: Vibe Coding for rapid prototyping, Plan Mode for structured development, and AI-engineered programming for enterprise-grade projects with SDD and Claude Code SuperPower.
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·4 min
GLM 5.2 & Zcode Hands-On Review: A Deep Dive into the Free AI Coding Tool with 5 Million Tokens/Day
In-depth review of Zhipu's GLM 5.2 model and Zcode programming tool: interface experience, coding benchmarks, and long-horizon Agent performance compared to GPT and Opus. 5M free tokens/day with MIT license.
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·4 min
Learning Path for AI Agent Development: A Complete Guide from Core Architecture to Production Deployment
A complete learning path for AI Agent development covering core architecture, ReAct paradigm, multi-agent collaboration, RAG integration, and lightweight deployment to guide developers from basics to production.
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·4 min
AI Super Week: Hundred-Billion-Dollar Capital, the Agent Revolution, Safety Crises, and China's New Landscape
Deep analysis of AI Super Week's four themes: Alphabet's $80B raise and Anthropic's IPO ignite capital markets, OpenAI Codex drives the Agent work revolution, Florida's first AI lawsuit sounds safety alarms, and China's WeChat Agent charts a differentiated path.
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Deep Dives·3 min
Deep Dive into Hermes Agent Self-Evolution: The GIPA Algorithm and Engineering Practice
Deep analysis of NousResearch's Hermes Agent Self Evolution project: GIPA genetic Pareto prompt evolution algorithm, six-step optimization loop, and five guardrail mechanisms for real-world Agent self-evolution.
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Expert Opinions·3 min
The Salary Ceiling for Agent Engineers: Two Critical Dividing Lines
Agent engineer salary gaps hinge on two dividing lines: real production deployment experience and depth of foundational theory including deep learning, fine-tuning, and reinforcement learning.
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Industry Insights·3 min
Alibaba's $52B AI Investment: A Full-Stack Cloud Infrastructure Upgrade for the Agent Era
Alibaba invests $52B in AI cloud infrastructure over 3 years. Bailian Platform hits 8B yuan ARR with 11 quarters of triple-digit AI revenue growth. Deep analysis of Alibaba Cloud's full-stack Agent upgrade strategy.
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Product Reviews·3 min
Picaboo: An Open-Source AI Desktop Automation Tool That Directly Controls Your Computer
Picaboo is an open-source AI desktop automation tool that controls your computer like a human through screenshot recognition and intelligent operations. Learn how it works, its use cases, and security considerations.
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Tech Frontiers·1 min
Cloudflare Contributes Critical KV Cache and Mooncake Fixes to SGLang
Cloudflare contributes decode KV cache offload and Mooncake recovery fixes to SGLang, resolving garbled output under high concurrency for Kimi K2.6 and enabling automatic fault recovery in distributed inference.
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Industry Insights·3 min
AI Fully Automated Orchestration in Practice: How Software Production Costs Are Being Completely Disrupted
Deep analysis of AI fully automated software orchestration: from Claude Code workflows to parallel orchestration strategies, exploring how models like MiniMax M1 drive software production costs toward zero.
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