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Jtsong.eth
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#Doodles | #Mfers | co-founder @Polariseorg | @QuaereOfficial | Building Matr1x | @arcthecommunity
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Jtsong.eth
04-01
I found it! Reality is definitely more inspiring than any movie. I was wondering where I'd seen this video before, and after finding it, I realized it was that guy with the 1000 RMB modified motorcycle who chased after the Hunan TV crew, insisting they film his old internet celebrity video. In 2006, 19-year-old Zhang Xue chased the Hunan TV crew for over 100 kilometers in the rain. He crashed, froze, and his hands were shaking so badly he couldn't keep up with the handlebars, but he still relentlessly chased them for three hours, just for a chance to show off his riding skills. Tearfully, he said in front of the camera, "If you don't do it when you're young, you'll definitely regret it when you're old; if you do it when you're young, even if you fail, you won't regret it when you're old. If you have a dream, pursue it, because courage makes my life more exciting!" On March 28-29, 2026, Zhang Xue's 820RR-RS motorcycle won two consecutive rounds of the WorldSSP category at the WSBK Portugal round! French rider Debis led by nearly 4 seconds, breaking the Ducati and Yamaha monopoly for the first time! From a car repair apprentice to a world champion creator, 20 years of relentless effort, all for this moment! 🏍️ In 2006, 19-year-old Zhang Xue chased a Hunan TV crew for over 100 km in pouring rain! Crashing, freezing, barely gripping the handlebars, he rode straight for 3 hours just for one chance to show his riding skills. Tears in his eyes, he told the camera: “If you don’t chase your dream when you’re young, you’ll regret it when you’re old. Even if you fail, you won’t regret trying. Have a dream? Go for it — because bravery makes life brilliant!” Fast forward to March 28-29, 2026: Zhang Xue’s ZXMOTO 820RR-RS wins back-to-back races in the WSBK Portugal WorldSSP round! French rider Valentin Debise beats Ducati & Yamaha by nearly 4 seconds. From motorcycle mechanic apprentice to world champion maker — 20 years of relentless grind, all for this Moment! 🏍️
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Jtsong.eth
03-24
Recently, due to the "airdrop witch" incidents at certain projects, I saw a discussion on Chinese Twitter: "APAC Leads in Web3 projects are basically scapegoats." When I saw this statement, I was actually a little taken aback 😂. Because for the past few years, I've spent most of my time in this role. Many people see APAC Leads as people who post Chinese tweets, organize events, are responsible for "generating buzz," and most importantly, are the ones who "take the blame" when problems arise. But in reality, it's not that simple. After doing it for a while, you'll find that the boundaries of this role are constantly expanding. An APAC Lead is not just a marketing position; it's more like a systemic role involving cross-regional growth and ecosystem building, and a core node for integrating Eastern and Western resources and cultures, and within the platform. When I first entered the industry, I focused more on publicity, community building, events, and media relations. My daily thought was: how to get more people to hear about the project. Later, I started becoming a bridge between headquarters and regional offices. This required repeatedly communicating about differences in understanding, coordinating resource allocation, and sometimes even pushing forward key decisions under completely uncertain circumstances. This was especially evident before TGE, highlighting the challenge of effectively integrating users, attention, funding, and platform resources in the highly fragmented Asia-Pacific market. Without experiencing this comprehensive "war-like" environment, one might not understand the sheer number of tests, immediate decisions, and trade-offs this position and the entire team face. Now, much of the work involves: collaboratively designing regional strategies, driving the implementation of ecosystem projects, and helping the team understand where the real opportunities lie in the Asia-Pacific market. A significant amount of time and energy is spent building relationships with numerous project teams and builders. Herein lies a crucial difference between Eastern and Western builders: Eastern builders excel at implementation but lack narrative skills and the ability to cultivate a market atmosphere. Western project teams often have a high-level perspective and strong storytelling abilities but weaker implementation capabilities. Top-tier APAC Leads even need to personally guide projects, identify shortcomings, and ensure continuous growth, bringing promising Eastern builders to the attention of Western investors while recommending established Western projects to suitable exchanges. This likely requires experience and resources akin to a combination of VC + incubator + marketing agency + listing advisor support. Furthermore, in the actual implementation process, it even requires connecting with local capital, government, and industry resources, finding feasible paths amidst different regulatory environments and business cultures. The difficulty of this job isn't just the sheer intensity. The real challenge lies in the daily effort to reassemble users, attention, funding, and platform resources across the Asia-Pacific region. Often, you need to understand both the logic and pace of Western teams and the realities and speed of the Eastern market. You must find the connection between two completely different systems. If you don't do well, you're likely to be the first to be questioned. So, is the APAC Lead a "scapegoat position"? To some extent, yes. But from another perspective, it's also a very real position: You stand at the forefront of globalization. You see the most authentic changes in market sentiment. You also have the opportunity to personally drive a project from regional to global. This job is exhausting, but it's also incredibly growth-oriented and fascinating.
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Jtsong.eth
03-09
AI and Crypto: It's not a question of "to add" or "to not add," but "when is it needed?" This weekend I attended the very popular OpenClaw Demo event, serving as a judge to review the projects. Another judge was a well-known investor in the Web2 space, who has made impressive investments in star companies like MiniMax during this AI wave. However, he had a very clear view: he's not optimistic about crypto. His logic is actually quite simple—if a project is inherently a great AI product, but forces blockchain into it just to issue a token, it essentially narrows its own path. Because once labeled as crypto, it immediately enters a more complex environment in terms of fundraising, regulation, and user perception. Frankly, I partially agree with this view. In the past few years, many Web3 projects have indeed made a mistake: Thinking about issuing a token first, then finding a product. The blockchain portion of many projects is actually completely redundant. If a product's core value doesn't rely on on-chain mechanisms, and it's just adding a layer of blockchain for Tokenomics, then the market has basically proven it's unworkable. Therefore, it's not surprising that some Web2 investors instinctively dislike "AI + Token" projects. However, the problem lies in this: Many people have drawn an overly simplistic conclusion—AI doesn't need crypto. I believe this conclusion is also incorrect. The relationship between AI and blockchain has never been a question of "whether it's needed," but rather a question of at what stage it will inevitably be needed. Moreover, as AI enters the Agent era, this need will become increasingly apparent. ⸻ I. AI Collaboration Requires "Verifiability" The future of AI is not a model, but an entire network of Agents. Completing a complex task may require dozens or even hundreds of AI Agents to collaborate: • Some are responsible for data acquisition • Some are responsible for reasoning • Some are responsible for execution • Some are responsible for verification In this system, a core question arises: Who did what? How to prove it? If all computation and data reside on a centralized server, ultimately, it relies solely on platform credibility. But when AI Agents begin large-scale collaboration, trusted records and verifiable execution become crucial. The value of blockchain lies here: • Verifiable records • Immutable logs • Programmable settlement In other words, AI needs a trusted collaborative underlying layer. This is why infrastructure like 0G proposes the concept of DeAIOS (Decentralized AI Operating System): Making AI data, computation, and behavior verifiable, rather than a black box. ⸻ II. AI Developers Need a New Incentive System Within the OpenClaw ecosystem, a significant problem has emerged. Many developers are developing Skills. These Skills are essentially capability modules for AI Agents. But the problem is: Developers find it difficult to gain long-term benefits from them. Today's model is roughly: • Developers contribute capabilities • The platform gains traffic • The platform controls revenue This model is common in Web2, but it's not suitable for the future AI Agent economy. If a Skill: • Can be repeatedly invoked • Can be combined into different Agents • Can be reused in different application scenarios Then it is essentially a digital asset. And the confirmation of asset ownership, trading, and revenue distribution are precisely the problems that blockchain excels at solving. The future likely to see: • Skill Marketplace • Agent Asset • Automated revenue distribution AI capabilities themselves will become tradable assets. ⸻ III. AI Data Sovereignty Issues Will Increasingly Serious The development of AI is rapidly approaching a new problem: Data Shortage. High-quality training data is becoming increasingly scarce. Meanwhile, large model companies are already using a large amount of internet content for training: • Articles • Images • Videos • Code Who are the creators of this content? Humans. But in the existing system, humans receive almost no reward. If this model continues, two things are likely to happen: 1️⃣ Data quality will continue to decline 2️⃣ Creators' motivation will disappear A more reasonable system in the future should be: • Data has a source • Data has ownership • Data can be licensed for use • Data contributions can generate revenue This is essentially data assetization. Blockchain can provide: • Data ownership confirmation • Data authorization • Data usage records • Automatic profit sharing Simply put: AI not only needs computing power, but also a new data economy system. ⸻ IV. Web3 practitioners shouldn't be ashamed to express themselves Recently, I've noticed an interesting phenomenon at many AI events. Many Web3 professionals deliberately downplay their background when introducing themselves. They're even a little embarrassed to say they come from Crypto. I think this is completely unnecessary. Web3 has indeed experienced bubbles, excessive narratives, and many failed projects. But this doesn't mean the technology itself has no value. Many technological approaches are actually ahead of their time. The current pace of AI development is reopening many possibilities: • AI Agents • Decentralized computing power • Data assets • AI collaboration networks These issues essentially require: A trustworthy digital economic infrastructure. And blockchain is precisely designed for such a system. V. The Real Question Isn't "Does AI Need Crypto?" The real question is: When is it needed? If an AI product: • Doesn't need decentralization • Doesn't need assetization • Doesn't need a collaborative network Then there's indeed no need for blockchain. But if AI enters: • Agent economy • AI collaborative network • Data asset market Then blockchain will almost inevitably become the underlying infrastructure. Therefore, I can quite understand the Web2 investor's point of view. However, from a longer-term perspective: AI and Crypto are likely not in competition, but rather complementary. AI is responsible for intelligence. Blockchain is responsible for trust and the economic system. When these two truly combine, we may see a completely different digital world. And right now, it's only just beginning.
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