I woke up and the sky has fallen, the black swan has arrived. Understanding King and Iran are wrestling, and I directly lost my position. Looking at this situation, it won’t calm down for a while. If I had known this would be the result, I should have listened to my friend. We are both studying in the U.S., and he has been fiddling with the CAILA Marco weather station. Currently, there is a stable CA token reward every day. As long as you upload weather information, you can earn money without even using computing power; just plug it in and connect to the internet. The monthly yield can be about $300. For those studying in the U.S., you can give it a try. Based on the project background of CAILA, it seems promising, with big names backing it, so there’s no fear of the project running away. The narrative is novel, and the traffic is booming. Below, I will introduce CAILA in detail. CAILA Project Research CAILA is an AI and MUP project built on the BNB Chain blockchain, focusing on providing real-time local weather services. The project aims to collect real-world weather data through a distributed network of weather sensors and provide personalized services based on geographical location and real-time weather using AI technology, completely transforming the centralized model of traditional weather services. CAILA's DePIN Entity Foundation Distributed Weather Station Deployment Marco Hardware CAILA deploys portable weather stations globally as DePIN nodes to collect real-time hyper-localized weather data such as temperature, humidity, wind speed, and UV levels (with a precision of about 500 meters). These devices can incentivize community users to participate through a 'weather mining' mechanism. Users deploying hardware can earn CA token rewards, creating a self-expanding network effect. CAILA's AI Brain Intelligent Processing Layer This is CAILA's 'brain', responsible for the analysis of complex data and decision generation. This layer integrates data from multiple sources, including the Marco weather station sensors from the Nubila network (monitoring UV, humidity, wind speed, air quality, and other parameters), public weather API warning systems, and user historical data. By using advanced AI algorithms, the system can understand the deep intent of user queries and generate precise and rational suggestions based on the current environment. CAILA's Three Highlights Integration of AI, physical implementation, and MEME, three popular narratives. The development path of GAILA adopts a strategy of AI first, then MEME, and is expected to become the world's largest weather data center in the future.