Always in the middle of something.
Chasing ideas across ML, AI, and data. Building tools when the rabbit hole gets interesting enough.
Editor's picks
AI 寫 code 為什麼又搬回終端機了
這兩年 AI 寫 code 的重心，悄悄從嵌在 IDE 裡的補全，搬回了終端機（Claude Code、Codex CLI 那一類）。我覺得這不是復古，是因為 agent 變成一個「你不盯著看的 process」，而終端機本來就是為這種東西設計的。
Why coding agents are moving back to the terminal
The coding agents developers reach for now — Claude Code, Codex CLI, Aider — are terminal programs, not IDE plugins. The reason isn't nostalgia: an IDE is built around a human at the keyboard, the terminal around processes you don't babysit. When AI coding became a job instead of a keystroke, it moved home.
Why Does AI Forget What You Said Earlier?
Chat with an AI long enough and it ignores the rules you set up top; open a new chat and it's blank. It isn't 'forgetting' — it has no memory. Every reply, it re-reads the whole conversation from scratch. Here's what the context window is, and how it differs from ChatGPT's 'memory' feature.
為什麼 AI 會忘記我前面說過的話？
跟 AI 聊久了，它就忘記你開頭交代的事；開新對話更是整個忘光。其實它不是「忘記」，是它根本沒有記憶——每次回你都是把整段對話重讀一遍。用一個失憶但讀很快的人的畫面，聊聊 context window 是什麼，還有它跟 ChatGPT 那個「記憶」功能差在哪。
把 temperature 設成 0，AI 就會每次都一樣嗎？
網路上常說：要 AI 每次給一樣的答案，把 temperature 設成 0 就好。但有人拿同一個 prompt、temperature 0 連跑 1000 次，還是冒出 80 種不同輸出。原因不是浮點誤差這麼簡單，而是它在 GPU 上跟多少別的請求湊成一批一起算。聊聊為什麼『最確定』不等於『可重現』。
Why Does AI Give a Different Answer Every Time You Ask?
Ask an AI the same thing three times and you often get three different answers. It isn't being flaky — it never picks the single most-likely word, it draws one by probability. Here's the dial behind it, why even temperature 0 isn't fully repeatable, and why 'varies' isn't the same as 'making things up'.
為什麼同一個問題問 AI，每次答案都不一樣？
同一個問題問 AI 三次，常常拿到三個不一樣的答案。不是它在亂講——它本來就不是每次都挑機率最高的那個字，而是照機率抽一個。用一個加權抽籤的畫面，聊聊它為什麼會飄，還有飄跟唬爛其實是兩回事。
When an AI says "done," ask it to show you
An AI's 'done' sounds the same whether the work happened or not. The fix is one small habit: don't take its word for it, ask it to show you a result you can check yourself, sized to the task.
AI 說「完成了」，怎麼確認它真的做完？
AI 回報「完成了」的時候，真的做完、做一半繞過去、方向整個誤會，那段話讀起來幾乎一樣。與其判斷那句話可不可信，不如養成一個反射：給我看一個我自己查得到的東西，commit、測試輸出、diff。
Claude Fable 5: First Public Mythos-Class Model, One Day In
Anthropic released Claude Fable 5 on June 9 — the first publicly available Mythos-class model, one tier above Opus. What it is, what it costs, the June 22 deadline on the subscription window, and what changed when I pointed three real projects at it for a day.