Most AI models today learn from "anonymous" data, basically whatever they can find on the web. As AI starts making bigger decisions, like diagnosing a patient in a hospital or driving a self-driving car, we can't afford for that data to be a "mystery." If the data is bad (what experts call "data poisoning"), the AI's decisions become dangerous. 𝐇𝐨𝐰 𝐏𝐞𝐫𝐥𝐞 𝐋𝐚𝐛𝐬 𝐅𝐢𝐱𝐞𝐬 𝐈𝐭 Think of @PerleLabs as a digital notary for AI data. Instead of using random crowds to label data, they use vetted experts (like real doctors or lawyers). 𝐇𝐞𝐫𝐞 𝐢𝐬 𝐡𝐨𝐰 𝐢𝐭 𝐰𝐨𝐫𝐤𝐬 𝐢𝐧 𝐭𝐡𝐫𝐞𝐞 𝐬𝐢𝐦𝐩𝐥𝐞 𝐬𝐭𝐞𝐩𝐬: 𝗘𝘅𝗽𝗲𝗿𝘁 𝗧𝗲𝗮𝗰𝗵𝗲𝗿𝘀: Only people who actually know the subject are allowed to teach the AI. A radiologist checks the medical images, not a random person with a smartphone. 𝗧𝗵𝗲 𝗨𝗻𝗰𝗵𝗮𝗻𝗴𝗲𝗮𝗯𝗹𝗲 𝗥𝗲𝗰𝗲𝗶𝗽𝘁: Every single time an expert helps the AI, that action is recorded on a blockchain. This creates a permanent, "un-hackable" record so a company can prove exactly who trained their AI and where the information came from. 𝗥𝗲𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻 𝗠𝗮𝘁𝘁𝗲𝗿𝘀: If an expert consistently provides great information, they build a digital "resume" on the platform that earns them more rewards. This ensures quality always comes before speed. 𝐖𝐡𝐲 𝐃𝐨𝐞𝐬 𝐓𝐡𝐢𝐬 𝐌𝐚𝐭𝐭𝐞𝐫? In the near future, when an AI helps a judge or a surgeon, we won't just have to "trust" the machine. Thanks to Perle Labs, we can look at the "receipts" to see that the AI was trained by the best human experts in the world. @PerleLabs #PerleAI #ToPerle