加密货币
加密货币
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Why Prediction Markets Aren't Gambling In Summary: - Emerging financial markets were often referred to as gambling until their economic value became clear. - Gambling involves fixed odds, while prediction markets reward knowledge. - Prediction markets are directly tied to real events with real consequences. - Speculation exists, but it's the utility that makes prediction markets financial instruments. - They can hedge real risk, not just entertainment. 1. History of Emerging Financial Markets - Every new financial instrument has been called gambling. In 1905, grain futures were brought to the U.S. Supreme Court. - Ruling: Yes, there was speculation, but futures also manage risk and enable price discovery. This is the key difference. Gambling creates artificial risk. Prediction markets, on the other hand, price real events with real consequences. 2. Gambling vs. Prediction Markets - Roulette/Dice: Fixed odds. 50/50 for red and 50/50 for black. No matter how much you learn, your odds of winning don't change. - Prediction Markets: Odds change as new information emerges. Meteorologists can outperform random guessing on the question "Will it rain tomorrow?"; election experts can outperform casual observers. - You can improve your odds of success by studying a specific market. No matter how much you study, you can't improve your odds of correctly guessing the outcome of a dice roll. 3. Connection to the Real World - Gambling outcomes are artificial. The casino sets the rules. - Prediction market outcomes are external. They depend on real-world events: elections, inflation, sporting events, weather, wars. These events have economic consequences. Prices in these markets serve as signals for businesses, governments, and investors. 4. Speculation vs. Utility Yes, some people speculate. But so do stocks, bonds, commodities, and cryptocurrencies. The difference: prediction markets provide useful prices, while casinos don't. 5. Hedging Examples Prediction markets aren't just for speculators. They can also be used for hedging, just like futures: Farmers and the Weather A farmer worried about drought can hedge by purchasing a contract predicting the number of tornadoes. If the crop fails, market payouts offset the losses. Businesses and Elections A healthcare company worried about new regulations can hedge by purchasing a contract predicting that "Candidate X will win." If the regulations are enacted, the hedge can cushion the impact on the business. 6. Conclusion Gambling = artificial risk, no external value. Prediction markets = real events, real bets, real information. They combine speculation, hedging, and price discovery. This gives them economic utility. This is why prediction markets are financial instruments.
Edgy - The DeFi Edge 🗡️
Edgy - The DeFi Edge 🗡️
Crypto Newbie
4h ago
AI tokens. Prediction markets. DeSci. The narrative is endless, as capital is always rotating here. The market is heating up, and everyone is speculating on what the next narrative will be. Robotics is a strong candidate. Robotics has the same tailwinds and hype as AI. Yet… AI tokens have reached a market cap of around $3 billion. Robotics? That's less than $300 million combined. Nvidia is launching embedded AI GPUs, and Tesla is showing off Optimus. Robotics is hype. Cryptocurrencies are a perfect fit, as robots require coordination, sub-penny payments, and tamper-proof logs to prove their work. If the market starts to heat up, this could be where capital is rotating. Some names worth checking out: • @codecopenflow: Providing execution rails for digital and physical robots through its Operators marketplace. It's becoming the execution layer for AI workers. • @peaq: L1 for the machine economy is already powering over 50 DePIN projects. Dozens of other device/robot networks are building on top of it. • @AukiNetwork: Building a "posemesh" for spatial computing. Making the physical world navigable and navigable by AI. • @UseRobora: A VLA-powered platform that aims to standardize robotic skills and create a codec-like marketplace for bidding on tasks. • @silencioNetwork: DePIN for real-world audio: Using the world's largest crowdsourced noise dataset to train models, enabling robots to hear and interpret their environment. • @homebrewrobots: Promoting an "app store" of robot actions and runnable pre-trained skills. • @RoboStack_io: Cloud simulation + robotic context protocol. The goal is to enable large-scale collaboration between agents, humans, and robots. The good news is that it's still very early days. There's no clear alpha release yet. If you're prepared, you can ride the wave. What am I overlooking? Which products do you think will become leaders as the category matures?