#Port3的AI社交数据层
Participate in Binance Square's **#Port3 AI Social Data Layer** essay activity, with earnings mainly divided into direct prizes and potential opportunities, analyzed simply as follows:
### 💰 1. **Direct Prize Earnings (Share a 20,000 USDT Prize Pool)**
- **Three Levels of Awards**:
- **First Prize (10 winners)**: Views > 15,000, reward **800 USDT**;
- **Second Prize (15 winners)**: Views > 8,000, reward **400 USDT**;
- **Third Prize (25 winners)**: Views > 2,000, reward **240 USDT**.
A total of 50 slots, filtered based on content quality and views, original text and images must be published before June 1.
### 🚀 2. **Potential Opportunity Earnings**
- **Exposure and Community Influence**: High-quality content shared by Port3's official account (must be shared on Twitter and @Port3Network) can attract the attention of project parties or investors, enhancing personal brand value.
- **Project Awareness Dividend**: Port3 is a leader in the AI + Web3 data layer (backed by Jump Crypto), with a current market value of only 20 million USD. Participating in the activity allows for deeper understanding of its potential and ecosystem (such as low-cost Alpha point accumulation) to lay the groundwork for investment decisions.
### ⚠️ 3. **Notes**
- **Competition Threshold**: Must have published at least one piece of square content within the last 30 days, and the content must deeply integrate Port3 technology or ecosystem (like Rankit system, Alpha point strategy).
- **No Capital Risk**: The activity itself poses no financial risk, but if you invest in $PORT3 tokens due to participation, be cautious of market fluctuations (like point accumulation losses, token price changes).
### 💎 Summary
The core of earning is **“Zero Cost to Win Prizes + Awareness Enhancement”**, suitable for users who can produce high-quality content. If the content meets the standards, one article can earn up to 800 USDT (about 5,600 yuan), while also accumulating industry resources; even if not awarded, you can systematically learn about new opportunities in the AI data track.
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