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七站完整目录Complete seven-site directory
主站Home · 3
学 AILearn · 324
- 名词对照Term index
- AI 编年史与版图AI Chronicle and Atlas
- 2026 下半年变化线The 2026 Second-Half Timeline
- 2026 评测基准地图The 2026 Benchmark Map
- Agent 评估怎么做How to Evaluate Agents
- AI 常犯什么错What AI Gets Wrong
- AI 常见误区总索引AI Misconceptions: Index
- AI 真的读懂了你的话吗Does AI Really Understand You
- few-shot 示例怎么选How to Pick Few-Shot Examples
- RAG 全链路:从文档到答案RAG End to End: From Documents to Answers
- 上下文工程怎么做How to Do Context Engineering
- 上下文窗口越大越好Bigger Context Is Always Better
- 什么时候不该用 RAGWhen Not to Use RAG
- 加了护栏就安全了Guardrails Make It Safe
- 参数越多就越聪明More Parameters Always Means Smarter
- 它在一步步推理It Reasons Step By Step
- 它拒绝,是因为做不到Refusal Means Inability
- 它记得你之前说过的It Remembers What You Said Earlier
- 它说得笃定,所以可信Confident Tone Means Correct
- 它逐字读懂你的文字It Reads Your Words One By One
- 开源模型一定更省钱Open Models Are Always Cheaper
- 怎么估算一次上线的安全成本How to Estimate the Safety Cost of a Launch
- 怎么保护自己的数据How to Protect Your Data
- 怎么做混合检索How to Do Hybrid Search
- 怎么写一份能被复核的任务指令How to Write a Task Brief Someone Can Review
- 怎么判断 AI 新闻是不是炒作How to Tell if AI News Is Hype
- 怎么向 AI 提问How to Ask AI
- 怎么处理一次误发事故How to Handle a Misfire Incident
- 怎么安全地用 MCP 工具How to Use MCP Tools Safely
- 怎么审一次第三方插件How to Audit a Third-Party Plugin
- 怎么对照 EU AI Act 自查How to Self-Check Against the EU AI Act
- 怎么把安全要求写进采购条款How to Write Safety Requirements into a Procurement Contract
- 怎么把提示词写结构How to Structure a Prompt
- 怎么挑 embedding 模型How to Choose an Embedding Model
- 怎么排查 AI 的数据泄露路径How to Trace AI Data Leak Paths
- 怎么搭一条最小评测流程How to Set Up a Minimal Evaluation Pipeline
- 怎么查 AI 生成内容的版权风险How to Check Copyright Risk for AI-Generated Content
- 怎么查生成式 AI 合规义务How to Check Generative AI Compliance Duties
- 怎么给 AI 内容做发布前检查How to Run a Pre-Publication Check on AI Content
- 怎么给 AI 内容加来源标识How to Label AI-Generated Content
- 怎么给 AI 工具配权限How to Set Permissions for AI Tools
- 怎么给团队做 AI 风险清单How to Build an AI Risk List for Your Team
- 怎么给文档做分块How to Chunk Documents for Retrieval
- 怎么给检索结果重排How to Rerank Retrieval Results
- 怎么自建评测口径How to Build Your Own Eval
- 怎么让 AI 按格式输出How to Get AI to Output in Your Format
- 怎么设计人工复核环节How to Design a Human Review Step
- 怎么评测 RAG 的效果How to Evaluate a RAG System
- 怎么读一篇AI论文How to Read an AI Paper
- 怎么读开源模型的许可证How to Read an Open-Model License
- 怎么读模型卡How to Read a Model Card
- 怎么读模型卡与系统卡How to Read Model Cards and System Cards
- 怎么防提示注入How to Guard Against Prompt Injection
- 怎么验证 AI 的输出How to Verify AI Output
- 思维链什么时候有用When Chain-of-Thought Helps
- 换模型前怎么迁移评估How to Assess a Model Migration
- 换模型只是改个名字Switching Models Is Just Renaming
- 接口兼容就等于行为一致A Compatible API Means Identical Behaviour
- 提示词怎么版本化How to Version Your Prompts
- 数据标注与质检怎么看How to Read Data Annotation and QA
- 显存不够就跑不了Not Enough VRAM Means It Will Not Run
- 本地部署就等于合规Local Deployment Means Compliance
- 榜单分数高就是好用A High Benchmark Score Means It Works For You
- 榜单怎么读How to Read a Leaderboard
- 注意力就是它注意到重点Attention Means It Notices What Matters
- 温度调高会更聪明Higher Temperature Means Smarter
- 系统提示怎么设计How to Design a System Prompt
- 论文卡-Attention Is All You NeedPaper Card - Attention Is All You Need
- 论文卡-ChinchillaPaper Card - Chinchilla
- 论文卡-Constitutional AIPaper Card - Constitutional AI
- 论文卡-Distilling the KnowledgePaper Card - Distilling the Knowledge in a Neural Network
- 论文卡-GPT-3Paper Card - GPT-3
- 论文卡-HELMPaper Card - HELM
- 论文卡-InstructGPTPaper Card - InstructGPT
- 论文卡-LIMAPaper Card - LIMA
- 论文卡-Llama 2Paper Card - Llama 2
- 论文卡-Self-InstructPaper Card - Self-Instruct
- 评测分数高就等于可靠A High Evaluation Score Means It Is Reliable
- 通用人工智能快到了AGI Is Just Around the Corner
- 通过一次评测就可以上线Passing One Evaluation Is Enough to Ship
- 量化、蒸馏、剪枝的区别Quantisation vs Distillation vs Pruning
- 量化会让模型变笨一半Quantisation Halves the Quality
- 预览版不能用于生产Preview Models Are Toys
- 学 AI · 名词地图Learn AI · Term Map
- 一个下午看懂原理One Afternoon Under the Hood
- 动手开发者路线The Builder's Route
- 普通消费者路线The Everyday User's Route
- 图像 / 视频 / 音频创作者路线The Image / Video / Audio Creator's Route
- 评测与质量路线The Evaluation and Quality Route
- 选型决策者路线The Decision-Maker's Route
- 运维上线路线The Operator's Route
- 研究学习者路线The Researcher's Route
- 安全与合规评审路线The Safety and Compliance Review Route
- 内容工作者路线The Writer's Route
- 一周路线The Full Week
- 半小时入门The Half-Hour Primer
- ACPAgent Client Protocol
- Agentic RAGAgentic RAG
- AGI(通用人工智能)AGI (Artificial General Intelligence)
- AI Agent 与聊天机器人的区别Agent vs Chatbot
- AI 产品 vs AI 模型Product vs Model
- AI 安全AI Safety
- AI 搜索AI Search
- AI 芯片AI Accelerator
- API / 接口调用API
- App ServerApp Server
- bpwBits Per Weight
- CLIPContrastive Language-Image Pre-training
- Computer UseComputer Use
- ControlNetControlNet
- CPU 推理CPU Inference
- FlashAttentionFlashAttention
- GGUFGGUF
- GPUGraphics Processing Unit
- GPU 层卸载-ngl / Offload
- KV 缓存KV Cache
- llama.cppllama.cpp
- LM StudioLM Studio
- logits 与概率分布Logits and Probability Distribution
- LoRALoRA (Low-Rank Adaptation)
- MCPModel Context Protocol
- MLXMLX
- MoE(混合专家)Mixture of Experts (MoE)
- OllamaOllama
- OpenAI 兼容接口OpenAI-compatible API
- PagedAttentionPagedAttention
- Prompt CachePrompt Cache
- QLoRAQLoRA
- safetensorssafetensors
- TokenToken
- TransformerTransformer
- vLLMvLLM
- Workflow 还是 AgentWorkflow vs Agent
- 上下文压缩Compaction
- 上下文学习In-context Learning
- 上下文工程Context Engineering
- 上下文并行Context Parallelism
- 上下文窗口Context Window
- 上下文窗口的代价Context Cost
- 上线前检查门禁Pre-launch Gates for AI Features
- 专家卸载MoE Offload / ncmoe
- 世界模型World Model
- 事故响应预案Incident Response Plan for an AI Feature
- 人工复核队列Human Review Queue
- 人工智能Artificial Intelligence, AI
- 人机协作Human-in-the-Loop
- 仓库级理解Repository-level Understanding
- 代码补全Code Completion
- 传输方式Transport
- 位置编码Positional Encoding
- 供应商安全问卷怎么读How to Read a Vendor Security Questionnaire
- 供应商锁定Vendor Lock-in
- 偏好对齐RLHF / Alignment
- 偏见Bias
- 具身智能Embodied AI
- 分块Chunking
- 分块预填充Chunked Prefill
- 前馈网络Feed-Forward Network
- 剪枝Pruning
- 区域可用性Regional Availability
- 单次调用成本Cost per Call
- 参数Parameter
- 参考服务器Reference Server
- 可替换性Portability
- 可观测性Observability
- 合成数据Synthetic Data
- 合规义务映射Compliance Obligation Mapping
- 向量 / 嵌入Embedding / Vector
- 向量数据库Vector Database
- 吞吐Throughput, TPS
- 困惑度Perplexity (PPL)
- 图灵测试Turing Test
- 基准测试Benchmark
- 基础模型Foundation Model
- 多 Agent 协作Multi-Agent
- 多头注意力Multi-Head Attention
- 多模态Multimodal
- 多模态输入风险Multimodal Input Risk
- 大模型 / 大语言模型Large Language Model, LLM
- 子代理隔离Sub-agent Isolation
- 子词分词Subword Tokenization
- 安全能力尽调清单Security Capability Due-Diligence Checklist
- 密钥与凭据管理Secret and Credential Management
- 对齐与拒答训练Alignment and Refusal Training
- 小语言模型Small Language Model (SLM)
- 层归一化Layer Normalization
- 嵌入层Embedding Layer
- 工作流编排Orchestration / Pipeline
- 工具定义Tool Definition
- 工具调用Tool Calling / Function Calling
- 差异对比Diff
- 幻觉Hallucination
- 幻觉检测信号Hallucination Warning Signs
- 幻觉的成因Why Hallucination Happens
- 开放权重Open Weights
- 开源模型Open-weight Model
- 开源生态Open-source Ecosystem
- 引用与可追溯Citations and Traceability
- 张量并行Tensor Parallelism
- 强化学习Reinforcement Learning (RL)
- 微调Fine-tuning
- 思维链Chain of Thought (CoT)
- 总分 / 综合评测Aggregate Score
- 成本Cost
- 扩散模型Diffusion Model
- 扩散模型怎么生成How Diffusion Models Generate
- 技能 / SkillsSkills
- 投机解码Speculative Decoding
- 护栏Guardrails
- 护栏与内容过滤Guardrails and Content Filtering
- 拒答Refusal
- 持续集成Continuous Integration, CI
- 推理Inference
- 推理成本Inference Cost
- 推理服务的访问控制Access Control for an Inference Service
- 推理模型Reasoning Model
- 提示注入Prompt Injection
- 提示词Prompt
- 提示链Prompt Chaining
- 插件与 MCP 的信任边界Plugin and MCP Trust Boundary
- 数字人Digital Avatar
- 数据不出网Data Sovereignty
- 数据外带路径Data Exfiltration Paths
- 数据污染Data Contamination
- 数据驻留Data Residency
- 数据驻留与出境Data Residency and Cross-border Transfer
- 文字怎么变成声音How Text Becomes Speech
- 文生图Text-to-Image Generation
- 无监督学习Unsupervised Learning
- 日志里留下了什么What the Logs Keep
- 显存VRAM
- 智能体 / AgentAgent
- 服务中断风险Vendor Dependency
- 本地部署Local Deployment
- 本地部署的隔离面Isolation Surfaces of a Local Deployment
- 机器学习Machine Learning, ML
- 机器视觉Computer Vision
- 权限Permission
- 校准Calibration
- 检索质量度量Retrieval Quality Metrics
- 模型卡Model Card
- 模型指纹与溯源Model Fingerprinting and Provenance
- 模型版本与变体Model Family, Version, Variant
- 模型评测的局限Evaluation Limits
- 模型退役Model Retirement
- 残差连接Residual Connection
- 水印与内容凭证Watermarks and Content Credentials
- 沙箱Sandbox
- 泛化Generalization
- 注意力机制Attention
- 流式输出Streaming Output
- 流水线并行Pipeline Parallelism
- 测试时计算Test-time Compute
- 浏览 / 网页操作Browser Automation
- 涌现能力Emergent Abilities
- 深度伪造Deepfake
- 深度学习Deep Learning
- 温度Temperature
- 潜空间Latent Space
- 版本控制Version Control
- 生成式 AIGenerative AI
- 生成式 AI 合规义务Generative AI Compliance Duties
- 监督学习Supervised Learning
- 知识截止Knowledge Cutoff
- 知识蒸馏Knowledge Distillation
- 社区与文档Community & Docs
- 神经网络Neural Network
- 离线评测与在线评测Offline vs Online Evaluation
- 系统提示System Prompt
- 红队测试Red Teaming
- 终端 AgentCLI Agent
- 结构化输出Structured Output
- 缓存策略Caching Strategy
- 编排模式Agentic Workflow Patterns
- 编码器与解码器Encoder & Decoder
- 缩放定律Scaling Laws
- 联网 / 检索增强Retrieval-Augmented Generation, RAG
- 能力边界Capability Boundary
- 自动化偏见Automation Bias
- 自动驾驶Autonomous Driving
- 自回归生成Autoregressive Generation
- 自托管成本Self-hosting Cost
- 蒸馏与知识来源Distillation and Knowledge Provenance
- 视频生成Video Generation
- 视频生成是怎么做的How Video Generation Works
- 训练Training
- 训练三阶段SFT → Reward Model → RL
- 训练内容摘要Training Content Summary
- 训练算力Compute
- 训练语料Training Corpus
- 训练集与测试集Training Set, Test Set
- 记忆Memory
- 许可证License
- 评估Evaluation, Evals
- 评测集设计Eval Set Design
- 评测饱和Benchmark Saturation
- 词表Vocabulary
- 语音克隆是怎么做的How Voice Cloning Works
- 语音合成TTS, Text-to-Speech
- 语音识别ASR, Automatic Speech Recognition
- 语音识别是怎么听的How Speech Recognition Works
- 贪心解码与束搜索Greedy Decoding and Beam Search
- 越狱Jailbreak
- 路由Routing
- 输出越界与拒答Output Overreach and Refusal
- 迁移评估Migration Evaluation
- 过拟合Overfitting
- 远程执行Remote Execution
- 连续批处理Continuous Batching
- 迭代速度Release Cadence
- 退出成本Exit Cost
- 速率限制Rate Limiting
- 配对编程Pair Programming
- 采样 / 采样参数Sampling
- 量化Quantization
- 量化方法Quantization Methods (GPTQ, AWQ)
- 长上下文Long Context
- 长时任务Long-running Task
- 闭源模型Closed / Proprietary Model
- 隐私与合规Privacy & Compliance
- 预填充Prefill
- 预览版与正式版Preview vs GA
- 预训练Pre-training
- 首字延迟Time To First Token, TTFT
AI 工具Tools · 310
- AIVAAIVA
- AssemblyAIAssemblyAI
- CartesiaCartesia
- CosyVoiceCosyVoice
- DeepgramDeepgram
- ElevenLabsElevenLabs
- F5-TTSF5-TTS
- fish audiofish audio
- AI 音频与语音AI audio & voice
- MiniMax Audio(海螺语音)MiniMax Audio (Hailuo Voice)
- 魔音工坊Moyin Workshop
- MurfMurf
- Otter.aiOtter.ai
- Resemble AIResemble AI
- SoundrawSOUNDRAW
- SunoSuno
- UdioUdio
- WhisperWhisper
- ActivepiecesActivepieces
- Salesforce AgentforceSalesforce Agentforce
- AutoGPT(现 Experts AI 团队平台)AutoGPT (now the Experts AI-team platform)
- Bedrock Agents / AgentCoreBedrock Agents / AgentCore
- BotpressBotpress
- Microsoft Copilot StudioMicrosoft Copilot Studio
- 扣子 / CozeCoze
- DifyDify
- FastGPTFastGPT
- FlowiseFlowise
- GumloopGumloop
- AI 自动化与工作流AI automation & workflows
- LangflowLangflow
- LindyLindy
- MakeMake
- MaxKBMaxKB
- n8nn8n
- Google OpalGoogle Opal
- Pipedream(Connect / Workflows)Pipedream(Connect / Workflows)
- Relevance AIRelevance AI
- SmythOSSmythOS
- Vertex AI Agent Builder(Gemini Enterprise 平台线)Vertex AI Agent Builder
- VoiceflowVoiceflow
- ZapierZapier
- 智谱清言ChatGLM (Zhipu Qingyan)
- ChatGPTChatGPT
- Claude(对话应用)Claude (chat app)
- DeepSeekDeepSeek Chat
- 豆包Doubao
- Gemini(对话应用)Gemini (chat app)
- GrokGrok
- 海螺AIHailuo AI
- HuggingChatHuggingChat
- AI 对话助手Chat assistants
- KimiKimi
- Le ChatLe Chat
- ManusManus
- Meta AIMeta AI
- Microsoft CopilotMicrosoft Copilot
- PoePoe
- Reka Chat(Reka Playground / Edge Chat)Reka Chat (Reka Playground / Edge Chat)
- 阶跃AIStepFun (Step Chat)
- 通义千问Tongyi Qianwen (Qwen Chat)
- 文心Wenxin
- 讯飞星火iFlytek Spark
- 腾讯元宝Tencent Yuanbao
- AiderAider
- Aider Watch 模式Aider (Watch mode)
- Amazon Q DeveloperAmazon Q Developer
- AmpAmp
- Augment CodeAugment Code
- 文心快码(Baidu Comate)Baidu Comate (Wenxin Kuaima)
- Bolt.newBolt.new
- Claude Code CLIClaude Code CLI
- Claude Code IDE 扩展Claude Code (IDE extension)
- ClineCline
- CodeBuddyCodeBuddy
- Codex CLICodex CLI
- Codex IDE 扩展Codex (IDE extension)
- ContinueContinue
- GitHub Copilot CLIGitHub Copilot CLI
- GitHub CopilotGitHub Copilot
- CrushCrush
- Cursor CLICursor CLI
- CursorCursor
- DevinDevin
- DroidDroid
- Gemini CLIGemini CLI
- Google AntigravityGoogle Antigravity
- GooseGoose
- xAI Grok BotxAI Grok Bot
- AI 编程AI coding
- JulesJules
- JunieJunie
- Kilo CodeKilo Code
- KiroKiro
- LovableLovable
- Meta MuseMeta Muse
- OpenAI DotOpenAI Dot
- OpenCodeOpenCode
- Qoder CN(原通义灵码)Qoder CN (formerly Lingma)
- QoderQoder
- Replit AgentReplit Agent
- TraeTrae
- v0v0
- WarpWarp
- Windsurf / Devin DesktopWindsurf / Devin Desktop
- ZedZed
- AG2AG2
- AgentScopeAgentScope
- Agno(原 Phidata)Agno (formerly Phidata)
- Claude Agent SDKClaude Agent SDK
- Codex SDKCodex SDK
- CrewAICrewAI
- Deep AgentsDeep Agents
- DSPyDSPy
- ElizaOS(Eliza)ElizaOS(Eliza)
- Google ADK(Agent Development Kit)Google ADK(Agent Development Kit)
- HaystackHaystack
- Hermes AgentHermes Agent
- 框架与运行时Frameworks & runtimes
- LangChainLangChain
- LangChain4jLangChain4j
- LangGraphLangGraph
- Letta / MemGPTLetta / MemGPT
- LlamaIndex FrameworkLlamaIndex Framework
- MastraMastra
- MetaGPTMetaGPT
- Microsoft Agent FrameworkMicrosoft Agent Framework
- Open InterpreterOpen Interpreter
- OpenAI Agents SDKOpenAI Agents SDK
- OpenHands Agent CanvasOpenHands Agent Canvas
- Pydantic AIPydantic AI
- Semantic Kernel(SK)Semantic Kernel(SK)
- smolagentssmolagents
- Spring AISpring AI
- Strands Agents SDKStrands Agents SDK
- SWE-agentSWE-agent
- Vercel AI SDK 7Vercel AI SDK 7
- Adobe FireflyAdobe Firefly
- ClipdropClipdrop
- FLUX(Black Forest Labs)FLUX (Black Forest Labs)
- IdeogramIdeogram
- AI 图像创作AI image creation
- 即梦Jimeng AI
- KreaKrea
- Leonardo AILeonardo AI
- Microsoft DesignerMicrosoft Designer
- MidjourneyMidjourney
- PlaygroundPlayground
- RecraftRecraft
- SeaArtSeaArt
- Stability AI(Stable Image 平台)Stability AI (Stable Image platform)
- Tensor.ArtTensor.Art
- 通义万相Tongyi Wanxiang (Wan)
- AI 工具AI Tools
- 1Password Environments MCP Server1Password Environments MCP Server
- Atlassian Remote MCP Server(Jira/Confluence)Atlassian Remote MCP Server(Jira/Confluence)
- Brave Search MCP ServerBrave Search MCP Server
- Browserbase MCP ServerBrowserbase MCP Server
- Chrome DevTools MCPChrome DevTools MCP
- Cloudflare MCP ServerCloudflare MCP Server
- Context7Context7
- Datadog MCP ServerDatadog MCP Server
- Everything MCP ServerEverything MCP Server
- Exa MCP ServerExa MCP Server
- Fetch MCP ServerFetch MCP Server
- Figma MCP ServerFigma MCP Server
- Filesystem MCP ServerFilesystem MCP Server
- Firecrawl MCP ServerFirecrawl MCP Server
- Git MCP ServerGit MCP Server
- GitHub MCP ServerGitHub MCP Server
- Grafana MCP ServerGrafana MCP Server
- 学术研究工具地图A map of academic research tools
- agent 记忆系统Agent memory systems
- API 还是本地跑API or local inference
- 2026 Q3–Q4 变更与迁移记录Q3–Q4 2026 changes and migration notes
- 聊天助手怎么选How to choose a chat assistant
- 采购与权限审计清单:问厂商的 18 个问题Procurement and access audit checklist
- 国内可用性怎么读:直连、主体与备案的口径How to read mainland availability
- Agent 框架:LangGraph / OpenAI Agents SDK / Google ADK / Claude Agent SDK 怎么选Agent frameworks: how to choose
- 浏览器 Agent 三选一:Playwright MCP / Browserbase MCP / Chrome DevTools MCPBrowser agents: Playwright, Browserbase, DevTools
- 聊天助手:ChatGPT / Gemini / Claude / Copilot 怎么选Chat assistants: ChatGPT vs Gemini vs Claude vs Copilot
- 写代码:终端 / IDE / 云端 Agent 怎么选Coding agents: terminal vs IDE vs cloud
- 本地跑模型:Ollama / LM Studio / llama.cpp / vLLM 怎么选Local runners: Ollama vs LM Studio vs llama.cpp vs vLLM
- 图像与视频:一条内容该用哪条工具链Image and video pipelines
- 研究工具:Perplexity / Kagi / NotebookLM / Elicit 怎么选Research tools compared
- 成本算式:云端、Agent、本地与视频四条线Cost formulas: cloud, agents, local and video
- agent 的成本控制Cost control for agents
- agent 评测Evaluating agents
- 练习包 · Builder:用 10 篇站内文档搭一个带引用的问答Exercise: cited answers from 10 source pages
- 练习包 · Creator:把一份官方资料做成三件套并留下事实表Exercise: three assets from one official source
- 练习包 · Manager:写一页供应商决策备忘录Exercise: a one-page vendor decision memo
- 失败库:按症状排查与十类资料误读Troubleshooting and ten evidence misreads
- agent 的护栏Guardrails for agents
- 怎么搭一条最小评测流程How to build a minimal evaluation pipeline
- 怎么估算合规投入How to estimate compliance effort
- 怎么做一次数据流梳理How to map a data flow
- 怎么给 agent 选护栏How to pick guardrails for an agent
- 怎么准备一次红队How to prepare a red-team session
- 怎么读一份第三方安全报告How to read a third-party safety report
- 怎么审 AI 供应商问卷How to vet an AI vendor questionnaire
- 怎么把评测接进发布How to wire evaluations into release
- 图像 / 视频 / 音频工具怎么选How to choose image, video and audio tools
- 多 agent 编排Multi-agent orchestration
- agent 的规划Planning for agents
- 任务:做一条 60 秒产品视频Playbook: producing a 60-second product video
- 任务:审阅长文与版本变化,保留原文位置Playbook: review document changes with evidence
- 任务:用编码 Agent 修一个真实 bugPlaybook: fixing a real bug with a coding agent
- 任务:在自己的机器上跑一个模型Playbook: running a model on your own machine
- 任务:把会议录音整理成可确认的纪要与行动项Playbook: meeting audio to notes and actions
- 任务:把 PDF 或扫描页转成可核对的表格Playbook: turn a PDF or scan into a checkable table
- 任务:做一份可核查的研究简报Playbook: producing a checkable research brief
- 任务:搭一个客服 Agent 并上线Playbook: building and shipping a customer-service agent
- 任务:合并多张表,留下冲突与异常Playbook: merge tables while preserving conflicts
- 团队 90 天落地 playbook:从试点到权限收口A 90-day team rollout playbook
- 20 题自测:AI 基础、评测与选型20-question self-test: fundamentals and evaluation
- 工具箱:Agent 评估、护栏、客服验收、故障清单Toolkit: agent ops checklists
- 工具箱:提示词、上下文预算、RAG 清单、选型表Toolkit: prompt and context
- 工具箱:权限矩阵、许可清单、视频权利表、成本算式Toolkit: rights and cost
- 工具箱:四张工作表(立项、发布、迁移、泄露)Toolkit: four worksheets
- MCP 工具MCP tools
- Intercom MCP ServerIntercom MCP Server
- Linear MCPLinear MCP
- Knowledge Graph Memory ServerKnowledge Graph Memory Server
- MongoDB MCP ServerMongoDB MCP Server
- Neon MCP ServerNeon MCP Server
- Notion MCPNotion MCP
- Playwright MCP ServerPlaywright MCP Server
- Sentry MCP / ToolkitSentry MCP / Toolkit
- Sequential Thinking MCP ServerSequential Thinking MCP Server
- Shopify Dev MCP ServerShopify Dev MCP Server
- Slack MCP ServerSlack MCP Server
- Stripe Agent Toolkit / MCPStripe Agent Toolkit / MCP
- Supabase MCPSupabase MCP
- Time MCP ServerTime MCP Server
- Zapier MCPZapier MCP
- Andi SearchAndi Search
- ConsensusConsensus
- DevvDevv
- ElicitElicit
- GensparkGenspark
- AI 搜索与研究AI search & research
- KagiKagi
- 秘塔 AI 搜索Metaso AI Search
- NotebookLMNotebookLM
- PerplexityPerplexity
- 天工 AI 搜索Tiangong AI Search
- You.comYou.com
- Docker Model RunnerDocker Model Runner
- ExLlamaV3ExLlamaV3
- GPT4AllGPT4All
- 本地模型运行器Local model runners
- JanJan
- KoboldCppKoboldCpp
- LemonadeLemonade
- llama.cppllama.cpp
- LlamaEdgeLlamaEdge
- LM StudioLM Studio
- LocalAILocalAI
- MLC LLMMLC LLM
- MLX(mlx-lm)MLX(mlx-lm)
- MstyMsty
- OllamaOllama
- OpenVINOOpenVINO
- SGLangSGLang
- TabbyAPITabbyAPI
- NVIDIA TensorRT-LLMNVIDIA TensorRT-LLM
- text-generation-webui / textgentext-generation-webui / textgen
- Text Generation Inference(TGI)Text Generation Inference(TGI)
- vLLMvLLM
- Content Credentials(内容凭证)Content Credentials
- Arize PhoenixArize Phoenix
- Azure AI Content SafetyAzure AI Content Safety
- Amazon Bedrock GuardrailsAmazon Bedrock Guardrails
- BraintrustBraintrust
- CanaryScanCanaryScan
- garakgarak
- GitGuardianGitGuardian
- HeliconeHelicone
- AI 安全与评测AI safety & evaluation
- InspectInspect
- LakeraLakera
- LangfuseLangfuse
- LangSmithLangSmith
- LangWatchLangWatch
- LiteLLM 网关(Proxy / AI Gateway)LiteLLM Proxy (AI Gateway)
- LLM GuardLLM Guard
- NeMo GuardrailsNeMo Guardrails
- NightfallNightfall
- OpenAI EvalsOpenAI Evals
- PresidioPresidio
- promptfoopromptfoo
- PyRITPyRIT
- RagasRagas
- RebuffRebuff
- Truepic Vision / LensTruepic Vision / Lens
- D-IDD-ID
- GenmoGenmo
- 海螺视频Hailuo Video
- HeyGenHeyGen
- HiggsfieldHiggsfield
- AI 视频创作AI video creation
- invideo AIinvideo AI
- 可灵 Kling AIKling AI
- Luma(Dream Machine)Luma (Dream Machine)
- PikaPika
- PixVersePixVerse
- RunwayRunway
- SynthesiaSynthesia
- Veo(Google)Veo (Google)
- ViduVidu
AI 模型Models · 48
- Claude(闭源 API)闭源模型 · 官方规格快照 · 带复核周期Claude (closed API)closed model · official spec snapshot · with review cycle
- 豆包(闭源 API)闭源模型 · 官方规格快照 · 带复核周期Doubao (closed API)closed model · official spec snapshot · with review cycle
- Gemini(闭源 API)闭源模型 · 官方规格快照 · 带复核周期Gemini (closed API)closed model · official spec snapshot · with review cycle
- GPT(闭源 API)闭源模型 · 官方规格快照 · 带复核周期GPT (closed API)closed model · official spec snapshot · with review cycle
- Grok(闭源 API)闭源模型 · 官方规格快照 · 带复核周期Grok (closed API)closed model · official spec snapshot · with review cycle
- Kimi(闭源 API)闭源模型 · 官方规格快照 · 带复核周期Kimi (closed API)closed model · official spec snapshot · with review cycle
- Command A模型家族谱系卡Command Amodel family lineage card
- DeepSeek模型家族谱系卡DeepSeekmodel family lineage card
- Gemma模型家族谱系卡Gemmamodel family lineage card
- GLM 智谱模型家族谱系卡GLM (Z.ai)model family lineage card
- gpt-oss模型家族谱系卡gpt-ossmodel family lineage card
- KAT Coder模型家族谱系卡KAT Codermodel family lineage card
- Kimi模型家族谱系卡Kimimodel family lineage card
- Laguna模型家族谱系卡Lagunamodel family lineage card
- Llama模型家族谱系卡Llamamodel family lineage card
- MiniCPM模型家族谱系卡MiniCPMmodel family lineage card
- Mistral模型家族谱系卡Mistralmodel family lineage card
- Muse模型家族谱系卡Musemodel family lineage card
- Ornith模型家族谱系卡Ornithmodel family lineage card
- Phi模型家族谱系卡Phimodel family lineage card
- 千问 Qwen模型家族谱系卡Qwenmodel family lineage card
- 腾讯混元模型家族谱系卡Tencent Hunyuanmodel family lineage card
- 偏好对齐:RLHF 与 DPO 在解决什么问题从业者视角的方法论 · 关键事实挂官方出处Preference alignment: what RLHF and DPO actually solvepractitioner-perspective methodology · key facts carry official sources
- 数据与算力:做模型的两大开销从业者视角的方法论 · 关键事实挂官方出处Data and compute: the two big bills of making a modelpractitioner-perspective methodology · key facts carry official sources
- 蒸馏:小模型怎么从大模型身上学从业者视角的方法论 · 关键事实挂官方出处Distillation: how small models learn from big onespractitioner-perspective methodology · key facts carry official sources
- GPU 事实与成本数学:跑模型的硬件账从业者视角的方法论 · 关键事实挂官方出处GPU facts and cost math: the hardware bill for running a modelpractitioner-perspective methodology · key facts carry official sources
- 把日志留在本地到底意味着什么从业者视角的方法论 · 关键事实挂官方出处What keeping logs on your own machine actually meanspractitioner-perspective methodology · key facts carry official sources
- 多模态模型的显存账怎么算从业者视角的方法论 · 关键事实挂官方出处Counting memory for a multimodal modelpractitioner-perspective methodology · key facts carry official sources
- 本地跑起来之前先确认的七件事从业者视角的方法论 · 关键事实挂官方出处Seven checks before a local run startspractitioner-perspective methodology · key facts carry official sources
- 预训练:模型怎么做到「什么都知道一点」从业者视角的方法论 · 关键事实挂官方出处Pre-training: how a model comes to know a bit of everythingpractitioner-perspective methodology · key facts carry official sources
- 量化档位与精度损失:能说什么、不能说什么从业者视角的方法论 · 关键事实挂官方出处Quantisation tiers and accuracy loss: what can be said, and what cannotpractitioner-perspective methodology · key facts carry official sources
- 怎么按官方口径读一个模型的评测说明从业者视角的方法论 · 关键事实挂官方出处How to read a model's evaluation write-up on its official termspractitioner-perspective methodology · key facts carry official sources
- 跑起来深水:KV 缓存、批处理与推理引擎从业者视角的方法论 · 关键事实挂官方出处Serving deep dive: KV cache, batching, and inference enginespractitioner-perspective methodology · key facts carry official sources
- SFT:让续写机器学会「好好回答」从业者视角的方法论 · 关键事实挂官方出处SFT: teaching a completion machine to answer wellpractitioner-perspective methodology · key facts carry official sources
- 任务模型:嵌入、重排、OCR 与语音识别从业者视角的方法论 · 关键事实挂官方出处Task models: embedding, reranking, OCR and ASRpractitioner-perspective methodology · key facts carry official sources
- 开源训练栈:多卡训练的工具链从业者视角的方法论 · 关键事实挂官方出处The open training stack: the toolchain behind multi-GPU trainingpractitioner-perspective methodology · key facts carry official sources
- 开放权重,该怎么选先选家族与规格,再选量化版——两步都有出处How to choose open-weight modelsPick the family and size first, the quantisation second — both steps carry sources
- DeepSeek V4DeepSeek V4
- Gemma 4Gemma 4
- GLM 5GLM 5
- gpt-ossgpt-oss
- KAT Coder V2.5KAT Coder V2.5
- Kimi K3Kimi K3
- Laguna 2.1Laguna 2.1
- MiniCPM 5MiniCPM 5
- Muse GlimmerMuse Glimmer
- Ornith 1.5Ornith 1.5
- 千问 3.8Qwen3.8
AI 导航Directory · 593
- AI 导航AI Directory
- ChatGPTChatGPT
- ClaudeClaude
- GeminiGemini
- DeepSeekDeepSeek
- KimiKimi
- 通义千问Qwen
- 文心一言ERNIE Bot
- 豆包Doubao
- GrokGrok
- PerplexityPerplexity
- 智谱清言ChatGLM
- 讯飞星火iFLYTEK Spark
- 百川智能Baichuan AI
- 腾讯混元Tencent Hunyuan
- 腾讯元宝Tencent Yuanbao
- 海螺 AIMiniMax
- 阶跃星辰StepFun
- CohereCohere
- Mistral Le ChatMistral Le Chat
- Character.aiCharacter.ai
- PoePoe
- HuggingChatHuggingChat
- Anthropic ConsoleAnthropic Console
- Meta AIMeta AI
- PiPi
- DeepSeek 平台DeepSeek
- Google AI StudioGoogle AI Studio
- Reka AIReka AI
- AI21 LabsAI21 Labs
- WriterWriter
- 秘塔 AI 搜索Metaso
- 天工 AI 搜索Tiangong AI
- DevvDevv
- You.comYou.com
- PhindPhind
- 博查 AI 搜索Bucha
- Brave SearchBrave Search
- ConsensusConsensus
- Andi SearchAndi Search
- PromptBasePromptBase
- PromptHeroPromptHero
- ArtbreederArtbreeder
- PromptFolderPromptFolder
- ChatGPT Prompt PlusChatGPT Prompt Plus
- SillyTavernSillyTavern
- Microsoft CopilotMicrosoft Copilot
- NotebookLMNotebookLM
- KagiKagi
- GitHub CopilotGitHub Copilot
- CursorCursor
- WindsurfWindsurf
- v0v0
- Bolt.newBolt.new
- Qoder CNQoder CN
- QoderQoder
- QodoQodo
- Kilo CodeKilo Code
- 文心快码Wenxin Kuaima (Baidu Comate)
- ReplitReplit
- Sourcegraph CodySourcegraph Cody
- CodeRabbitCodeRabbit
- TabnineTabnine
- ZedZed
- TabbyTabby
- ClineCline
- LovableLovable
- TempoTempo
- AnimaAnima
- LocofyLocofy
- Builder.ioBuilder.io
- AutoGPTAutoGPT
- DifyDify
- 扣子 CozeCoze
- CozeCoze
- ManusManus
- 百宝箱Baidu AI Studio Agents
- LangGraphLangGraph
- CrewAICrewAI
- Relevance AIRelevance AI
- SuperagentSuperagent
- BotpressBotpress
- SmythOSSmythOS
- Google AntigravityGoogle Antigravity
- TraeTrae
- Claude Code CLIClaude Code CLI
- Codex CLICodex CLI
- Gemini CLIGemini CLI
- KiroKiro
- OpenCodeOpenCode
- AmpAmp
- GooseGoose
- CanvaCanva
- Microsoft DesignerMicrosoft Designer
- Galileo AIGalileo AI
- UizardUizard
- 即时 AIJishi AI
- MidjourneyMidjourney
- Stable DiffusionStable Diffusion
- DALL·EDALL·E
- ComfyUIComfyUI
- Leonardo AILeonardo AI
- FireflyFirefly
- 通义万相Tongyi Wanxiang
- 文心一格Baidu Yige
- SeaArtSeaArt
- Krea AIKrea AI
- ClipdropClipdrop
- Tensor.artTensor.art
- RunwayRunway
- PikaPika
- 可灵 KlingKling
- SoraSora
- HeyGenHeyGen
- SynthesiaSynthesia
- Luma AILuma AI
- 即梦Dreamina
- PixversePixverse
- ViduVidu
- 剪映CapCut
- Haiper AIHaiper AI
- GenmoGenmo
- invideo AIinvideo AI
- FlikiFliki
- DescriptDescript
- SunoSuno
- UdioUdio
- ElevenLabsElevenLabs
- 魔音工坊Moyin
- Murf AIMurf AI
- Play.htPlay.ht
- SpeakSpeak
- AIVAAIVA
- SoundrawSoundraw
- BoomyBoomy
- MeshyMeshy
- Tripo AITripo AI
- CSM AICSM AI
- RodinRodin
- Spline AISpline AI
- DeepMotionDeepMotion
- KaedimKaedim
- Ready Player MeReady Player Me
- 小冰Xiaoice
- D-IDD-ID
- Hour OneHour One
- DeepBrain AIDeepBrain AI
- 腾讯智影Tencent Zhiying
- FLUXFLUX
- IdeogramIdeogram
- VeoVeo
- KlingKling
- Hailuo VideoHailuo Video
- LumaLuma
- WhisperWhisper
- DeepgramDeepgram
- GammaGamma
- JasperJasper
- Copy.aiCopy.ai
- GrammarlyGrammarly
- 通义听悟Tongyi Tingwu
- 讯飞听见iFLYTEK Listen
- Otter.aiOtter.ai
- Notion AINotion AI
- WPS AIWPS AI
- RytrRytr
- WritesonicWritesonic
- Jenni AIJenni AI
- AlphaFold DBAlphaFold DB
- RoseTTAFoldRoseTTAFold
- NVIDIA BioNeMoNVIDIA BioNeMo
- Isomorphic LabsIsomorphic Labs
- RecursionRecursion
- Viz.aiViz.ai
- PathAIPathAI
- AidocAidoc
- Butterfly NetworkButterfly Network
- TempusTempus
- 推想科技Infervision
- Harvey AIHarvey AI
- LawgeexLawgeex
- IroncladIronclad
- EverlawEverlaw
- 幂律智能Milvue
- KenshoKensho
- AlpacaAlpaca
- QuantConnectQuantConnect
- AlphaSenseAlphaSense
- NumeraiNumerai
- KavoutKavout
- KhanmigoKhanmigo
- Duolingo MaxDuolingo Max
- QuizletQuizlet
- Century TechCentury Tech
- Carnegie LearningCarnegie Learning
- Squirrel AISquirrel AI
- PersadoPersado
- PhraseePhrasee
- Albert AIAlbert AI
- AnywordAnyword
- OptimoveOptimove
- PencilPencil
- AI 工具AI Tools
- Hugging FaceHugging Face
- ModelScope 魔搭ModelScope
- OllamaOllama
- ReplicateReplicate
- CivitaiCivitai
- OpenRouterOpenRouter
- Together AITogether AI
- Fireworks AIFireworks AI
- GroqGroq
- OctoAIOctoAI
- AnyscaleAnyscale
- ModalModal
- Banana DevBanana Dev
- BasetenBaseten
- Leap AILeap AI
- LlamaLlama
- MistralMistral
- QwenQwen
- GemmaGemma
- PhiPhi
- Yi 零一万物Yi
- DeepSeek ModelsDeepSeek Models
- DBRX by DatabricksDBRX by Databricks
- OLMo by Allen AIOLMo by Allen AI
- IBM GraniteIBM Granite
- Snowflake ArcticSnowflake Arctic
- LM StudioLM Studio
- vLLMvLLM
- llama.cppllama.cpp
- MLXMLX
- SGLangSGLang
- TensorRT-LLMTensorRT-LLM
- PineconePinecone
- WeaviateWeaviate
- ChromaChroma
- MilvusMilvus
- QdrantQdrant
- ElasticsearchElasticsearch
- LangChainLangChain
- LlamaIndexLlamaIndex
- LangfuseLangfuse
- Vercel AI SDKVercel AI SDK
- HaystackHaystack
- TensorFlowTensorFlow
- PyTorchPyTorch
- OpenCVOpenCV
- KerasKeras
- ONNXONNX
- JAXJAX
- Weights & BiasesWeights & Biases
- MLflowMLflow
- Neptune.aiNeptune.ai
- ClearMLClearML
- BentoMLBentoML
- DagsHubDagsHub
- MetaflowMetaflow
- KubeflowKubeflow
- SeldonSeldon
- ValohaiValohai
- Scale AIScale AI
- LabelboxLabelbox
- Label StudioLabel Studio
- SuperAnnotateSuperAnnotate
- Snorkel AISnorkel AI
- Credo AICredo AI
- Robust IntelligenceRobust Intelligence
- Arthur AIArthur AI
- WhyLabsWhyLabs
- Guardrails AIGuardrails AI
- LMSYS Chatbot ArenaLMSYS Chatbot Arena
- Stanford HELMStanford HELM
- GalileoGalileo
- DeepEvalDeepEval
- TruLensTruLens
- ComposioComposio
- Prompt flowPrompt flow
- ExaExa
- CandleCandle
- MCP Servers(官方合集)MCP Servers (official collection)
- NVIDIANVIDIA
- AMDAMD
- IntelIntel
- 台积电 TSMCTSMC
- ARMARM
- 寒武纪Cambricon
- 海光信息Hygon
- 摩尔线程Moore Threads
- 地平线Horizon Robotics
- CerebrasCerebras
- GraphcoreGraphcore
- SambaNovaSambaNova
- 华为海思HiSilicon
- 壁仞科技Biren
- 燧原科技Enflame
- ImaginationImagination
- 昆仑芯Kunlunxin
- NeuralinkNeuralink
- SynchronSynchron
- Blackrock NeurotechBlackrock Neurotech
- LightmatterLightmatter
- Ayar LabsAyar Labs
- 曦智科技Lightelligence
- IBM QuantumIBM Quantum
- Google Quantum AIGoogle Quantum AI
- IonQIonQ
- QuantinuumQuantinuum
- 本源量子Origin Quantum
- Lambda LabsLambda Labs
- CoreWeaveCoreWeave
- AutoDLAutoDL
- RunPodRunPod
- PaperspacePaperspace
- Vast.aiVast.ai
- JarvisLabsJarvisLabs
- CadenceCadence
- SynopsysSynopsys
- AnsysAnsys
- KeysightKeysight
- Siemens EDASiemens EDA
- Samsung SemiconductorSamsung Semiconductor
- SK HynixSK Hynix
- MicronMicron
- Western DigitalWestern Digital
- 长江存储 YMTCYMTC
- ASMLASML
- Applied MaterialsApplied Materials
- Lam ResearchLam Research
- Tokyo ElectronTokyo Electron
- 中微半导体 AMECAMEC
- SiFiveSiFive
- RISC-V InternationalRISC-V International
- 赛昉科技 StarFiveStarFive
- 芯来科技 NucleiNuclei System Technology
- EsperantoEsperanto
- Tesla OptimusTesla Optimus
- Figure AIFigure AI
- Boston DynamicsBoston Dynamics
- Unitree 宇树Unitree
- 1X Technologies1X Technologies
- Agility RoboticsAgility Robotics
- 傅利叶智能Fourier
- 智元机器人AgiBot
- ApptronikApptronik
- 优必选科技UBTECH
- 达闼机器人CloudMinds
- 逐际动力EngineAI
- Clone RoboticsClone Robotics
- PAL RoboticsPAL Robotics
- Beyond ImaginationBeyond Imagination
- ABB RoboticsABB Robotics
- FANUCFANUC
- KUKAKUKA
- Yaskawa 安川Yaskawa
- 埃斯顿自动化Estun
- 新松机器人SIASUN
- 普渡机器人Pudu Robotics
- 擎朗智能Keenon
- 高仙机器人Gaussian Robotics
- 追觅科技Dreame
- 科沃斯ECOVACS
- 石头科技Roborock
- 大疆 RoboMasterRoboMaster
- ROS.orgROS.org
- NVIDIA IsaacNVIDIA Isaac
- ROS 2ROS 2
- Universal RobotsUniversal Robots
- MuJoCoMuJoCo
- NVIDIA OmniverseNVIDIA Omniverse
- CoppeliaSimCoppeliaSim
- WebotsWebots
- GazeboGazebo
- WaymoWaymo
- CruiseCruise
- 百度 ApolloApollo
- 文远知行 WeRideWeRide
- 小马智行 Pony.aiPony.ai
- MobileyeMobileye
- NuroNuro
- AuroraAurora
- ZooxZoox
- TuSimpleTuSimple
- Embark TrucksEmbark Trucks
- SkydioSkydio
- 亿航智能 EHangEHang
- ZiplineZipline
- WingWing
- 极飞科技 XAGXAG
- Intuitive SurgicalIntuitive Surgical
- Medtronic HugoMedtronic Hugo
- CMR SurgicalCMR Surgical
- 天智航TINAVI
- 极智嘉 Geek+Geek+
- Locus RoboticsLocus Robotics
- 海柔创新HAI ROBOTICS
- SeegridSeegrid
- Ekso BionicsEkso Bionics
- ReWalk RoboticsReWalk Robotics
- SuitXSuitX
- Blue River TechnologyBlue River Technology
- FarmBotFarmBot
- Carbon RoboticsCarbon Robotics
- 丰疆智能Farming Fortune
- Iron OxIron Ox
- OceaneeringOceaneering
- Saab SeaeyeSaab Seaeye
- Blue RoboticsBlue Robotics
- 深之蓝Deep Blue
- RoboCupRoboCup
- FIRST RoboticsFIRST Robotics
- VEX RoboticsVEX Robotics
- Maker FaireMaker Faire
- LEGO EducationLEGO Education
- ArduinoArduino
- Raspberry PiRaspberry Pi
- micro:bitmicro:bit
- MakeblockMakeblock
- Festo BionicFesto Bionic
- Soft RoboticsSoft Robotics
- Piaggio Fast ForwardPiaggio Fast Forward
- Open BionicsOpen Bionics
- RoboBeesRoboBees
- arXivarXiv
- Papers With CodePapers With Code
- Semantic ScholarSemantic Scholar
- Connected PapersConnected Papers
- ResearchGateResearchGate
- CourseraCoursera
- edXedX
- UdacityUdacity
- Fast.aiFast.ai
- DeepLearning.AIDeepLearning.AI
- LeetCodeLeetCode
- CodecademyCodecademy
- HackerRankHackerRank
- CodewarsCodewars
- ExercismExercism
- MIT OpenCourseWareMIT OpenCourseWare
- Stanford OnlineStanford Online
- Khan AcademyKhan Academy
- OpenStaxOpenStax
- 3Blue1Brown3Blue1Brown
- Learn PromptingLearn Prompting
- Prompting GuidePrompting Guide
- Anthropic Prompt LibraryAnthropic Prompt Library
- OpenAI CookbookOpenAI Cookbook
- FlowGPTFlowGPT
- Common CrawlCommon Crawl
- Hugging Face DatasetsHugging Face Datasets
- Google Dataset SearchGoogle Dataset Search
- ImageNetImageNet
- OpenStreetMapOpenStreetMap
- RustRust
- PythonPython
- TypeScriptTypeScript
- GoGo
- SwiftSwift
- Deep Learning BookDeep Learning Book
- d2l.aid2l.ai
- Pattern Recognition and Machine LearningPattern Recognition and Machine Learning
- Reinforcement Learning: An IntroductionReinforcement Learning: An Introduction
- The Elements of Statistical LearningThe Elements of Statistical Learning
- ZigZig
- JuliaJulia
- MojoMojo
- ElicitElicit
- 对比:写代码 Agent 怎么选Compare: coding agents
- 对比:聊天助手怎么选Compare: chat assistants
- 对比:图像与视频工具链怎么选Compare: image & video toolchains
- 对比:本地 runner 怎么选Compare: local runners
- 对比:Agent 框架怎么选Compare: agent frameworks
- 对比:研究工具怎么选Compare: research tools
- 对比:浏览器 Agent 三选一Compare: three browser agents
- 练习:Builder 带引用问答Exercise: builder cited Q&A
- 练习:Creator 三件套Exercise: creator three-piece kit
- 练习:Manager 决策备忘录Exercise: manager decision memo
- 自测:20 题(含答案)Self-test: 20 questions (with answers)
- Hacker NewsHacker News
- Product HuntProduct Hunt
- Reddit r/MachineLearningReddit r/MachineLearning
- Dev.toDev.to
- Stack OverflowStack Overflow
- MIT Technology ReviewMIT Technology Review
- The Verge AIThe Verge AI
- VentureBeat AIVentureBeat AI
- TechCrunch AITechCrunch AI
- Analytics India MagazineAnalytics India Magazine
- Google DeepMindGoogle DeepMind
- OpenAI ResearchOpenAI Research
- Meta AI ResearchMeta AI Research
- Anthropic ResearchAnthropic Research
- NVIDIA ResearchNVIDIA Research
- Hugging Face ForumsHugging Face Forums
- AI Alignment ForumAI Alignment Forum
- EleutherAI DiscordEleutherAI Discord
- 智源社区BAAI Community
- OpenAI Developer ForumOpenAI Developer Forum
- Lex Fridman PodcastLex Fridman Podcast
- Machine Learning Street TalkMachine Learning Street Talk
- Practical AIPractical AI
- Data SkepticData Skeptic
- This Week in StartupsThis Week in Startups
- GitHubGitHub
- VercelVercel
- NetlifyNetlify
- DeepLDeepL
- FigmaFigma
- CodePenCodePen
- KaggleKaggle
- StackBlitzStackBlitz
- ExcalidrawExcalidraw
- ObsidianObsidian
- RaycastRaycast
- WarpWarp
- LinearLinear
- PostmanPostman
- DockerDocker
- SupabaseSupabase
- GlitchGlitch
- CloudflareCloudflare
- AWSAWS
- FirebaseFirebase
- PlanetScalePlanetScale
- NeonNeon
- RailwayRailway
- Fly.ioFly.io
- RenderRender
- DribbbleDribbble
- BehanceBehance
- UnsplashUnsplash
- PexelsPexels
- IconifyIconify
- LottieFilesLottieFiles
- DatadogDatadog
- SentrySentry
- GrafanaGrafana
- New RelicNew Relic
- LogRocketLogRocket
- D3.jsD3.js
- ObservableObservable
- EChartsECharts
- PlotlyPlotly
- Chart.jsChart.js
- NamecheapNamecheap
- Cloudflare DomainsCloudflare Domains
- GitHub PagesGitHub Pages
- Vercel DomainsVercel Domains
- PorkbunPorkbun
- ZapierZapier
- MakeMake
- AirtableAirtable
- BubbleBubble
- RetoolRetool
- CertiKCertiK
- OpenZeppelinOpenZeppelin
- Trail of BitsTrail of Bits
- QuantstampQuantstamp
- 慢雾科技 SlowMistSlowMist
- VS CodeVS Code
- Sublime TextSublime Text
- iTerm2iTerm2
- AlacrittyAlacritty
- BrunoBruno
- KongKong
- ApigeeApigee
- TykTyk
- AWS API GatewayAWS API Gateway
- ZuploZuplo
- AlfredAlfred
- RectangleRectangle
- AltTabAltTab
- 1Password1Password
- BitwardenBitwarden
- NotionNotion
- WindmillWindmill
- TemporalTemporal
- Google OpalGoogle Opal
- Microsoft Copilot StudioMicrosoft Copilot Studio
- n8nn8n
- Specul 提示词与上下文模板Specul prompt & context templates
- Specul Agent 评估与护栏模板Specul agent evaluation & guardrail templates
- Specul 权限与成本模板Specul permission & cost templates
- Playbook:修一个真实 bugPlaybook: fix a real bug
- Playbook:做一条 60 秒视频Playbook: make a 60-second video
- Playbook:做一份可核查的研究简报Playbook: a verifiable research brief
- Playbook:搭一个客服 AgentPlaybook: build a support agent
- Playbook:在本机跑一个模型Playbook: run a model locally
- 指南:国内可用性怎么读Guide: reading mainland availability
- 速记:2026 Q3–Q4 变更Brief: 2026 Q3–Q4 changes
- Playbook:团队 90 天落地Playbook: 90-day team rollout
- 清单:采购与权限审计Checklist: procurement & access audit
AI 做游戏Game making · 41
- AI 生成内容的版权归属Copyright of AI-generated work
- AI 资产台账AI asset ledger
- 作品库与最小可玩原型Showcase and minimal prototypes
- BevyBevy
- Cocos CreatorCocos Creator
- GodotGodot
- libGDXlibGDX
- PhaserPhaser
- PixiPixi
- Three.jsThree.js
- UnityUnity
- Unreal EngineUnreal Engine
- 引擎对 AI 有多友好How AI-friendly each engine is
- Godot 的场景树Godot's scene tree
- 跟 AI 聊天把游戏做出来Make a game by talking to AI
- 学习路径Learning path
- 实战流程The build order
- S1 · 选引擎S1 · Pick an engine
- S2 · 核心循环S2 · The core loop
- S3 · 手感调参S3 · Game feel & tuning
- S4 · 资产合规S4 · Asset licensing
- S5 · 导出与发布S5 · Ship it
- 三颗星,一扇门:把同一个游戏逐步做完整Three stars, one door: complete one game step by step
- Vibe GamingVibe Gaming
- Web 导出可行性Web export feasibility
- 上下文窗口与 AI 写游戏Context window and AI-written games
- 先发极简版Ship a rough version first
- 关卡数据的组织方式How to organise level data
- 字体的授权陷阱Font licensing traps
- 存档与离线行为Save and offline behaviour
- 怎么做一份素材与许可台账How to build an asset and licence ledger
- 怎么做一次发布前检查How to run a pre-release check
- 怎么处理引擎版本差异How to handle engine version differences
- 怎么定一个两周能做完的范围How to scope a game down to two weeks
- 怎么给 AI 美术素材做商用可用性判断How to check AI art for commercial use
- 怎么验收 AI 生成的游戏代码How to accept AI-generated game code
- 手感问题清单Game feel checklist
- 提示词的结构Structuring the prompt
- 最小可玩原型Minimal playable prototype
- 美术风格的一致性Keeping the art style consistent
- 音频素材的来源与授权Audio sources and their licences