大胆假设Bold bets, 并行推演parallel simulation, 固化交付shipped tools.
我们用投机策略让 AI 推演一切，把结果做成人人可用的工具。 像 speculative decoding 一样：先假设多条路径，并行验证，择优兑现。
We run speculative strategies so AI can reason about everything — then ship the results as tools anyone can use. Like speculative decoding: assume many paths, verify in parallel, keep the best.
SITES · 四个站
各有一件事要做
Four sites, four jobs
同一个团队，四种交付形态：一份术语表、一张Agent 图谱、一份模型索引、一份精选目录。
One team, four delivery forms: a glossary, an agent atlas, a model index, and a curated directory.
AI 术语表
AI glossary
116 个词，分六层。有零基础入门路径，每词都能回到原始出处。
116 terms in six layers, with a zero-prerequisite path and a primary source for every entry.
AGENTAgent 图谱
Agent atlas
33 个对象分三层：自己跑的成品 agent、自己搭的运行时与 SDK、给 agent 装的 MCP 工具。不给总分排名。
33 entries in three layers: finished agents, runtimes and SDKs you build yourself, and MCP tools you install. No rankings.
MODELS本地模型索引
Local model index
7 个系列、11 种规格、846 个量化档位。按你的显存倒推该下哪一个，不做质量排名。
7series, 11 specs, 846 quantization tiers. Pick by VRAM budget. No quality rankings.
NAV硅基导航
Directory
487+ 个精选 AI 资源，按 9 个大品类归类，每条都有说明与出处。
487+ curated AI resources across 9 categories, each with notes and a source.
一个词根，两种动作
One root, two moves
Specul 来自拉丁语「观察 / 推测」。在中文里我们故意保留张力：投机是策略，推演是方法。
From Latin specula — watch, infer. In Chinese we keep the tension: speculation as strategy, simulation as method.
投机
Speculation
借用大模型里的投机策略思路：在算力与时间有限时，并行押注多条假设，用后续验证淘汰错误分支。 我们用同样的方式选赛道、选技术、选产品——不是赌运气，而是结构化地下注。
Borrowed from speculative strategies in LLMs: when compute and time are scarce, bet on multiple hypotheses in parallel and let verification kill the wrong branches. We pick markets, stacks, and products the same way — structured bets, not luck.
推演
Speculate / Simulate
用模型、数据与可运行原型把世界往前推：推演玩法手感、推演工具形态、推演分发路径。 推演不是报告，而是能点开、能玩、能改的产物。
Use models, data, and runnable prototypes to push the world forward: playtests, tool shapes, distribution paths. Simulation is not a slide deck — it is something you can open, play, and fork.
从假设到工具
From bet to tool
投机假设
Speculative bet
用最小假设锁定问题：谁需要什么、哪里有结构性机会。
Lock a minimal hypothesis: who needs what, where the structural edge is.
AI 推演
AI simulation
让大模型与工具并行展开可能性，用可运行结果替代空想。
Let models fan out possibilities in parallel; replace opinion with runnable results.
固化交付
Ship the tool
把验证过的结论做成人人可用的基座与目录。
Freeze what survived verification into tools anyone can use.
现在可用的东西
What you can use now
AI 术语表
AI glossary
116 个词分六层，配一条零基础入门路径。不按字母排，按「先学什么后学什么」排—— 因为大多数人不做本地部署，第 5 层可以先跳过。
116 terms in six layers with a zero-prerequisite path. Ordered by what to learn first, not alphabetically — most people never deploy locally, so layer 5 can be skipped.
从第一层开始Start at layer 1Agent 图谱
Agent atlas
33 个对象分三层：自己跑的成品 agent、自己搭的运行时与 SDK、给 agent 装的 MCP 工具。 每条判断挂官方源，未知就写未知——不给总分排名。
33 entries in three layers: finished agents, runtimes and SDKs you build yourself, and MCP tools you install. Every judgement links to a primary source; no rankings.
成品 AgentFinished agents 自己搭的底座Runtimes & SDKs 给 agent 装的工具MCP tools量化模型图谱
Quantized models
定了模型之后还有一关：同一模型有几十个 GGUF 量化版。 按你的显存倒推该下哪一档，体积是实测值，许可逐条标原文。
After picking a model, one more question: which GGUF quant to download? Resolved by VRAM budget, with measured sizes and per-quant licences.
Models 图谱Models atlas硅基导航
Directory
529 条精选：模型、编程、多模态、算力、机器人与开发工具，按 11 类组织。
529 curated entries across models, coding, multimodal, compute, robotics and dev tools, in 11 categories.
浏览目录Browse十一个品类，直达分类
Eleven categories, one click in
开始你的推演
Start your own simulation
从一个大胆的假设开始，让 AI 帮你并行验证。
Start with a bold hypothesis; let AI verify it in parallel.