kevin lau

[muihbb @muihbb]

https://t.co/2ulLIbG0nX

[グロウクロ��バー @Dp4KJqUXJGhJJ0D]

pixivFANBOXでミナVS姫子 性技あり日韓闘乳屈服デスマッチ 3話を公開しました！ https://t.co/bNU2A8Gev8

[kevin lau @KevinLau99772]

@hao_yan48910 @grok 其���gemini改下谷歌账号归属地就行了

[Jerry Xiong @Jerry_Galaxy]

租啥显卡，兄弟你不是有Google AI会员么？直接登陆google colab用A100（80GB显存）就行，每个月credits够用40小时了。
先白嫖Google云端GPU，体验几天后再看要不要自己买硬件。
自己玩本地硬件生视频速度相对比较慢，当然本地生视频有多种方式。
我是M3 Ultra通过MLX-Serve玩MiniMax H3，生成一个10秒视频（Good Quality档位）大概10分钟吧。

[老杨特靠谱 @VAlexanderYang]

来！
小黑子！
叫！！！！

纯净静态 IP
¥21/月、200g 流量

杜绝所谓的万人骑家宽！

特殊时期也从未掉链子！

👇懂行的冲！不懂行的更可无脑入！
https://t.co/WmOU4o6mpX

[贝塔酱 @Walden779]

和美女约个会🧸 . ʚɞ .
@Miiiho420

[グロウクローバー @Dp4KJqUXJGhJJ0D]

DL同人自作初のレズバトルメインの作品が完成しました！現在申請中ですが、DLsiteにて10/9販売予定です！

[贝塔��� @Walden779]

薄肌太瘦了 我喜欢厚肌

[_ @kawaguchi_3team]

デカ女(にょ)とデカ女(にょ)の百合 #oc

[kevin lau @KevinLau99772]

@dwwgalaxy who？

[kevin lau @KevinLau99772]

@xiaoshunli @AlanShao111 看看照片

[OpenAI @OpenAI]

We��re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics.

The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra.

The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.

[kevin lau @KevinLau99772]

@AlanShao111 还有CK吧

[kevin lau @KevinLau99772]

@Nelljing 不会吧 那享福tv真享福了？

[Min Choi @minchoi]

PROMPT:
## Before implementing

Work like a contractor who bills for rework: the cost of a wrong assumption is
yours to avoid, and the cost of an unnecessary question is mine to pay.

### 1. Investigate before you ask
Read the relevant code, tests, configs, and dependency manifests first. Anything
discoverable in under a minute of searching is not a question — it's research
you owe me. Never ask about test framework, language version, lint rules, error
handling conventions, directory layout, or existing abstractions that already
exist in the repo. If the codebase contradicts itself, that's worth raising.

### 2. Then produce this, and stop

**Goal.** One paragraph restating what I asked for in your own words, including
the acceptance criteria you'll hold yourself to. If your restatement is wrong,
that's the cheapest possible place to find out.

**Blocking questions (0–3).** Only ask when a wrong answer means throwing work
away, not adjusting it. Each question gets your recommended default so I can
reply "yes to all" — never ask an open question where a proposed answer would do.
If nothing is genuinely blocking, say so and list zero.

**Assumptions.** Numbered, specific, falsifiable. "Inputs are under 10k rows and
fit in memory" is an assumption. "The code should be maintainable" is not. Cover
whichever of these the task actually touches:
- Data: shape, volume, trust level, encoding, what a malformed input looks like
- Failure: what should happen on timeout, partial write, or downstream 500 —
retry, fail loud, or degrade
- Boundaries: who calls this, what's public API vs. internal, backwards-compat
obligations
- State: concurrency, idempotency, transactionality, ordering guarantees
- Environment: runtime version, where it deploys, what it's allowed to reach
- Scope: what you're deliberately *not* doing, and what you're leaving as TODO
- Testing: what you'll write tests for and what you'll leave uncovered

**Plan.** Files you'll create or modify, the key function/type signatures, and
the order you'll work in. Where you chose between real alternatives, name the
alternative and say why you rejected it in one clause.

Then wait. Do not begin implementing.

### 3. Proportionality
This ceremony scales with blast radius. A typo fix, a rename, or a change under
~20 lines with one obvious correct form: just do it. A new module, a schema
change, anything touching auth, money, migrations, or deletion: full treatment,
and be more suspicious than usual of your own assumptions.

### 4. After I approve
Implement the plan as approved. If you discover mid-implementation that an
assumption was wrong or the plan doesn't survive contact with the code, stop and
tell me — don't quietly improvise a different design and don't press on with an
approach you now believe is wrong.

[kevin lau @KevinLau99772]

@Caroline_44731 @chenpapro 今天吃了几根bbc

[Fred-New @Fred834567]

想要靠信息差赚钱的兄弟全体注意

说GitHub只是放代码的，基本没在里面翻过三个小时。

实际上，上面的信息密度比任何技术社区都高一个量级。我列举了8个信息差套利方式和仓库：👇

1、远程工作信息差套利：awesome-remote-job
这个仓库包括了上百个远程工作投递网站，甚至涵盖了远程工作面试技巧、数字游民交流社群。
想在巴厘岛边度假边赚钱，就狠狠的阅读这个仓库中的信息。
🔗：https://t.co/44LfYJbveb

2、AI赚钱信息差套利: ai-money-maker-handbook
这个项目包含了非常多的AI赚钱思路和实操，比如AI出海、AI自媒体、AI技术等。
如果你还不知道如何用AI赚钱，可以从这个开始。
🔗：https://t.co/aZH1h02lNG

3、媒体信息差套利：TelegramGroup
这个仓库整理了上万个TG群组，很多一手信息只在TG上流通，相当于给你一张地图，告诉你去哪找。
🔗：https://t.co/YypYRju58P

4、内容创作信息差套利：awesome-list
搜“awesome+领域”就能找到别人整理好的顶级资源，做内容、找选题、挖素材，全是现成的。
🔗：https://t.co/KjeFQt2RJM

5、薅羊毛信息差套利：ai-goofish-monitor
这个仓库可以实时监控同一个闲鱼商品所有商家的最新动态，并根据AI算法推荐性价比最高且货真价实的商品，让你在闲鱼中快人一步，成为赢家。
🔗：https://t.co/D1W5WRH0To

6、自动化工具信息差套利：n8n
开源自动化工具，把重复工作搭成流程后自动跑，别人每天手动两小时，你一次性搞定。
🔗：https://t.co/bpnADwlrnf

7、数据信息差套利：awesome-public-datasets
收集了海量公开数据集，做���析、做产品、做报告，数据源直接给你摆好了。
🔗：https://t.co/Ssjtza7lTA

8、量化交易信息差套利：awesome-systematic-trading
非常权威的量化交易手册，包括不同平台上关于量化交易的资源库、书籍、策略、视频等。
🔗：https://t.co/A8EEVXXNKa

这些信息差套利渠道全部是真货。每个仓库都是我翻过、用过、确认能跑通的。

但说句实话——信息差从来不值钱，执行力才值钱。GitHub上这类资源多到看不完，真正能把一个仓库吃透、跑通、变现的人，千里挑一。

有些人看到的是仓库，有些人看到的是现金流。

收藏不丢人，只收藏不打开才可惜。希望这篇能推更多人一把，把想法变成行动。

[TaejaHo🔞 @HoTaeja]

ONE PIECE HEROINES
Nami VS Robin arm wrestling🤝

[kevin lau @KevinLau99772]

@yantanzhang 这是ai 你个傻逼