The underlying logic for ordinary people to make money: leverage hometown supply chain advantages + connect with overseas demand + start with lightweight assets + validate and iterate with data. No need to wait for perfect preparation; first run through the minimal closed loop, then gradually scale up.

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1h ago

Operational details determine success or failure: adjusting the width by 1.5cm for European and American foot shapes reduced the return rate from 15% to 5%; using TikTok to post "factory real shots" and "foreigners trying on and reacting" to drive traffic; signing unsold inventory consignment agreements with three shoe factories, clearing out end-of-season stock at 30% off for cash flow. Attention to detail naturally brings profit. Don’t just focus on the big picture; true strength is revealed in small details, and execution is the key.

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1h ago

Post-2000s college students selling Zhanjiang slippers, annual sales of 250k pairs, revenue of 3.5 million yuan. No funding, no background, the core strategy is just three points: avoid the domestic red ocean + cross-border direct connection to overseas C-end + light assets, one-piece dropshipping. Ordinary people making money, really don't need to compete with big factories or compete on education, find the right niche + execute well, small businesses can also generate huge compound interest. Understand this closed loop, just copy the homework 👇

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1h ago

I really can't help but want to complain about Tencent's WorkBuddy... 😤
It seems generous, but in reality, it can't do any work at all!
I originally wanted it to help me batch recognize screenshot content and then rename files, but it directly performed an "infinite dead loop" for me.
Read a few images -> compress context -> forget what was just read -> read again -> compress again... 🤯
In the end, I even adjusted a sub-agent, but that sub-agent couldn't understand the images at all (lacking multimodal capabilities).
It feels like they limited the context too low to save tokens, which makes

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2h ago

Next week, on May 12th, Android 17 will be officially released!🎉
I checked out the spoilers, and besides the native app lock, there’s cross-device continuity and improved screen recording. Feels like this update is packed with useful features.
Which one are you most looking forward to?👇

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2h ago

I stumbled upon this video about interpersonal relationships, and although some of the things it says are a bit painful, they’re actually pretty reasonable. 😂
For example: “Never, ever try to be a good person—be a person with real strength.” And “Don’t make excuses for yourself.” Justifying yourself is lowering your status.
The core, really, is about value exchange and setting boundaries.
It feels like I used to be too much of an overly nice person—I need to learn how to be “not someone to mess with.” 🤣

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4h ago

Doubao's 500 yuan/month membership overnight blew up the entire AI community, with a flood of criticism in the comment section. But today, let's not discuss whether it's worth it or not, and instead talk about a more painful reality: the free logic that China's internet has adhered to for over twenty years is now collapsing completely. Large models burn real computing power with every question, and the more free users there are, the more the platform loses. Understand this underlying logic, and you'll see why the era of free AI is destined to be gone forever. 👇

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4h ago

Traditional internet is free, relying on ads to make "pigs pay." But large models are completely different: every question asked, every piece of content generated, consumes massive computing power, truly burning money. Top-tier models invest billions in computing power annually, with each single conversation costing a few cents to a few dimes. The more free users there are, the more the platform loses, and this logic simply doesn't work.

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4h ago

There are only four ways for large model monetization: advertising, ToB interfaces, pay-per-use, and subscription plans. Advertising ruins the user experience and the revenue can't cover the computing costs; ToB interfaces have a low ceiling and lead to price wars, pushing profits to the extreme; pay-per-use can suppress user activity and runs counter to ByteDance's demand for high-frequency usage. ByteDance chooses the subscription plan, not out of stubbornness, but because it's the only optimal solution after calculating the costs.

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4h ago

ByteDance core chooses a monthly subscription model, with four key reasons: 1. Lock in users to increase frequency and stickiness; the more they use, the less they leave; 2. Stable cash flow to cover rigid computing power costs and plan investments precisely; 3. Filter high-value users to build a paid ecosystem and achieve full user coverage; 4. Benchmark against GPT to position in the high-end market and establish a "top-tier" brand perception. Short-term criticism, long-term positioning.

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5h ago

Paying for AI is not about cutting leeks; it's a return to business logic: good products should make money from the product itself, not from ads or harvesting privacy. When choosing tools, consider their long-term iteration capability, not just short-term free offerings. Which AI feature are you willing to pay for? Share your judgment in the comments.

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5h ago

Why is the era of free services destined to end? Large models break the iron law of "zero marginal cost," with each use incurring fixed costs. Technological iteration requires continuous investment; only when users pay can a positive cycle of "payment → R&D → product enhancement → more payments" be established. Relying on fundraising and burning money is never sustainable; product strength is the hard truth.

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5h ago

Will the free version degrade in quality? Definitely, it's just a matter of time. Model downgrades / usage limits / slower responses / ad insertions are industry common issues. GPT free version requires a paid upgrade to 4.0, while Wenxin Yiyan's free version has strict usage limits. There are no free lunches in the business world, and no business that continuously loses money. Don't be fooled by the idea of "permanent free."

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6h ago

Project URL link:

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7h ago

A tutorial on how to find a treasure!
I've always heard that multi-dimensional tables are useful, but I didn't know how to get started. This video starts from zero basics and even teaches you step-by-step how to build a fixed asset management system.
What really caught my eye is that now AI can directly write formulas🤯, no need to search for how to use functions on Baidu anymore, just tell it what result you want.
I feel like learning this will save me a lot of overtime when handling data in the future...
I recommend everyone take some time to watch it, even if you don't use DingTalk, the ide

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