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编程The Fastest Way to Become an AI Engineer in 2026
A practical 90-day roadmap to become an AI engineer: the skills that matter, the projects that get you hired, and tips to skip what slows most people down.
2026年11月2日 · 阅读约 5 分钟
智能体 AIWhat Is Agentic AI? A Plain-English Guide
Agentic AI doesn't just answer questions. It plans, uses tools and completes tasks. Here's how AI agents work, where they help today and where to be careful.
2026年10月27日 · 阅读约 2 分钟
生成式 AIThe AI Family Tree: AI vs Machine Learning vs Deep Learning vs Generative AI vs Agents
A simple map of how AI, machine learning, deep learning, generative AI, LLMs, RAG and AI agents fit together, with a tree diagram and plain-English examples.
2026年11月2日 · 阅读约 4 分钟
网络安全Cybersecurity News Roundup: October 2026
The biggest cyber attacks and breaches of October 2026, the AI security trends behind them, India's DPDP and CERT-In rules, and what to do now.
2026年11月2日 · 阅读约 4 分钟
开发者工具Google's Elephant-Goldfish Model (EGM) for AI Coding, Explained
Google's open-source Elephant-Goldfish Model for AI coding: a long-memory 'elephant' writes the design and memory-less 'goldfish' review it.
2026年11月2日 · 阅读约 5 分钟
生成式 AIHow to Build a RAG App Step by Step (2026 Guide)
Build a retrieval-augmented generation (RAG) app that answers from your own documents with sources: chunking, embeddings, vector search, prompts and evaluation.
2026年11月2日 · 阅读约 3 分钟
智能体 AIHow to Build an AI Agent from Scratch (Step-by-Step Guide)
Build an AI agent that plans, uses tools and completes tasks: the agent loop, tool design, memory, guardrails, evaluation and when to use multiple agents.
2026年11月2日 · 阅读约 3 分钟
开发者工具How to Build an MCP Server in Python (Beginner's Guide)
Build a Model Context Protocol (MCP) server in Python: tools, resources and prompts, testing with an inspector, connecting to AI apps, and keeping it secure.
2026年11月2日 · 阅读约 3 分钟
智能体 AIMLOps vs LLMOps vs AgentOps: Lifecycles Explained
What MLOps, LLMOps and AgentOps are, how their lifecycles differ, the tools and metrics for each, and which one your AI project needs.
2026年11月2日 · 阅读约 4 分钟
未来科技Generative AI vs Agentic AI, and What Comes Next
From chatbots that create, to agents that act, to multi-agent systems, world models and robots: a simple map of where AI is heading.
2026年10月24日 · 阅读约 2 分钟
智能体 AIModel Context Protocol (MCP) Explained Simply
MCP is the open standard that lets AI assistants connect to your tools and data. What it is, how it works and why it matters for agentic AI.
2026年10月20日 · 阅读约 2 分钟
AI 动态The Biggest Recent AI Updates, Explained
Reasoning models, multimodal AI, open-weight models, on-device AI and much longer memory: the changes behind today's AI tools, in plain English.
2026年10月17日 · 阅读约 2 分钟
AI 工具AI Tools Worth Trying, by What You Want to Do
The best AI tools for writing, research, images, video, voice and coding, grouped by job so you can pick the right one quickly.
2026年10月14日 · 阅读约 1 分钟
开发者工具AI Coding Assistants and Agents: What's New for Developers
From autocomplete to agents that change whole codebases: how AI coding tools work today and how to use them without losing control of your code.
2026年10月10日 · 阅读约 1 分钟
编程Programming Languages to Watch: New and Rising
Rust, Zig, Gleam, Mojo, Carbon and the big changes to Python and TypeScript: which programming languages are rising and why.
2026年10月7日 · 阅读约 2 分钟
智能家居Matter and Thread Explained: The Smart Home Standard
Why Matter means smart devices finally work with Apple, Google, Amazon and Samsung at once, what Thread adds, and what to check before you buy.
2026年10月4日 · 阅读约 2 分钟
数码产品Smart Rings, Smart Glasses and AI Wearables: What's Worth It
The newest wearable gadgets, from health-tracking smart rings to AI smart glasses and mixed-reality headsets, and how to decide if one is right for you.
2026年10月1日 · 阅读约 1 分钟
新发明8 New Inventions and Breakthroughs Shaping the Next Decade
Gene editing cures, fusion milestones, better solar cells, solid-state batteries, quantum error correction and humanoid robots: the breakthroughs to watch.
2026年9月28日 · 阅读约 2 分钟
生成式 AIHow Generative AI Works (No Maths Required)
Tokens, training, transformers and diffusion explained simply, plus why AI sometimes makes things up and how to get better answers.
2026年9月24日 · 阅读约 2 分钟
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