#Infrastructure as Code
2738 related articles
Tech Frontiers·2 min
Qwen Core Team Turmoil, OpenAI and Google Release New Models in Rapid Succession | AI Daily
Multiple core leaders depart Alibaba's Qwen team amid metric disputes. Same day: MiniMax Music 2.5+, OpenAI GPT 5.3 Instant, Google Gemini 3.1 Flashlight, and Seedance 2.0 pricing announced.
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Tech Frontiers·2 min
DeepSeek OCR2, Kimi K2.5, and Microsoft Maia 200 All Launched on the Same Day
DeepSeek releases OCR2 replacing CLIP with an LLM as visual encoder; Moonshot AI launches Kimi K2.5 with 100+ sub-agent cluster mode; Microsoft deploys 3nm Maia 200 chip; Alibaba releases Qwen3 Max Thinking.
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Tech Frontiers·2 min
Qwen Launches 400+ New Features as Wenxin 5.0 and Multiple LLMs Drop Simultaneously
Alibaba's Qwen APP launches 400+ features integrating Alipay and Taobao, Baidu releases ERNIE 5.0, Meituan unveils deep reasoning model, StepFun tops global speech AI rankings, and Anthropic's share nears Google's.
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Product Reviews·3 min
Gemini 3.1 Pro vs Claude Opus 4.6: Five Real-World Tests to Determine the Winner
Hands-on comparison of Gemini 3.1 Pro vs Claude Opus 4.6 across five real-world tests including SVG generation, interactive components, website building, and complex reasoning, with practical usage recommendations.
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Product Reviews·3 min
Claude 4.5 vs Gemini 3 Pro: A Comprehensive Coding Showdown
In-depth comparison of Claude 4.5 vs Gemini 3 Pro across five benchmarks including ARC-AGI-V2, SWE-Bench, and Terminal Bench 2.0, revealing their real coding and reasoning strengths.
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Tutorials·2 min
Five Core Differences Between Claude Code and Traditional AI Chat Tools
Compare Claude Code vs traditional AI chat tools like ChatGPT across 5 dimensions: interaction, context, execution, memory, and tool invocation to decide if this AI coding assistant is right for you.
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Product Reviews·3 min
AI Agent Investment Research Showdown: ChatGPT vs. Kimi vs. Manus — Who Delivers Better Financial Analysis?
Testing ChatGPT, Manus, and Kimi on the same investment analysis task reveals how multi-agent architecture, fault tolerance, and parallel workflows define the real capability boundaries of AI Agents in professional finance.
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Tutorials·3 min
Getting Started with AI Full-Stack Development: A Knowledge Framework from Machine Learning to Large Language Models
A systematic guide to the relationships between AI, machine learning, deep learning, and large language models, helping developers build a clear knowledge framework and find an efficient learning path.
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Product Reviews·2 min
TangPing.skill: An Open-Source Meme Project That Teaches AI Agents to Slack Off
TangPing.skill is an open-source AI Agent Skill on the OpenClaw ecosystem that teaches AI to "lie flat." Explore its hot-loading mechanism, lightweight Skill distribution, and what it reveals about AI Agent ecosystems.
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Tutorials·3 min
LangChain Core Concepts Explained: A Complete Guide to Components, Chains, and Agents
Deep dive into LangChain's three core concepts—Components, Chains, and Agents. Learn how this open-source framework connects LLMs to the external world and helps developers build enterprise AI apps.
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Tech Frontiers·2 min
Kimi K2.5 Fully Open-Sourced: Deep Dive into 1T Parameter MoE Architecture + Agent Cluster Capabilities
Deep dive into Moonshot AI's fully open-sourced Kimi K2.5: 1T parameter MoE architecture, Vision-to-Code capabilities, and 100-Agent parallel cluster system topping open-source benchmarks.
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Product Reviews·2 min
AI Coding Appliance vs Cloud LLMs: Can ¥480K in Annual Fees Buy 4 Local Deployment Solutions?
A deep cost comparison between AI coding appliances and cloud LLM APIs. A 20-person team spending ¥480K/year on tokens can deploy 4 local OnePanel units at ¥99K each, breaking even in 2.5 months.
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Tutorials·3 min
Agent Loop Explained: Solving Code Refactoring Pain Points with the ReAct Pattern
Deep dive into Agent Loop, the core mechanism of AI coding tools. Learn how the ReAct pattern's reason-act-observe cycle enables autonomous multi-step code refactoring.
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Tutorials·2 min
Running Out of Codex Credits? AnySearch Skill Saves You Massive Token Overhead
Real-world testing shows AnySearch Skill saves ~27% Token overhead for Codex while significantly improving search quality. Learn how it works, how to install it, and when to use it.
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Deep Dives·3 min
Getting Started with RAG: A Complete Guide from LLM Hallucinations to Retrieval-Augmented Generation
A deep dive into RAG (Retrieval-Augmented Generation) technology, covering LLM hallucinations, data staleness, and limited expertise, plus RAG workflows, core components, and LangChain learning paths.
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Tutorials·3 min
The Complete Vibe Coding Workflow: A Step-by-Step Guide for Non-Developers to Build and Ship Products Independently
A complete 7-step Vibe Coding guide from requirements to deployment. Learn how non-developers can independently build and ship products using VS Code and Claude Code, with PRD writing, static Demo validation, and step-by-step development.
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Tutorials·3 min
LLM Learning Roadmap: A Complete Guide from Beginner to Project Implementation Across Seven Core Modules
A systematic breakdown of seven core LLM learning modules covering environment setup, Prompt Engineering, RAG, Agents, dev frameworks, fine-tuning, and hands-on projects for developers.
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Product Reviews·2 min
One Person, One Month: Building a Chinese Writing Community from Scratch with AI Development Tools
A Bilibili creator used AI coding tools to single-handedly build a Chinese writing community called "YouTi" in one month. This article breaks down the product design, prompt-response mechanics, manual review strategy, and how AI tools are reshaping indie dev capabilities.
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Tutorials·3 min
Liberal Arts Grad's Vibe Coding Journey: How a Simple Link Aggregation Page Earned 10K+ Views
A liberal arts creator built a concert seat view website using Gemini AI in one afternoon, earning 15K views. Learn her idea selection, simplification methods, and pitfalls for a replicable Vibe Coding path.
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Product Reviews·2 min
GPT-5 Codex Deep Dive: 93% Token Savings But Tool Ecosystem Still Needs Work
Deep testing GPT-5 Codex: 93.7% Token savings on simple tasks with deeper reasoning on complex ones. But UI quality drops, search is poor, and tool ecosystem fragmentation remains a major issue.
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