Perle has been included in Coinbase's listing plan. Although AI+data annotation has been a field that many projects have rushed into and failed to do, Perle has found its unique competitive advantage in both the team itself and the business direction. The most worth mentioning is its founder @ AhmedZRashad, who was a core member of ScaleAI before founding Perle. He served as the head of growth marketing, solving data sources and quality issues for the company's supply side, managing over one million data annotators worldwide for ScaleAI. Last year, Meta acquired half of ScaleAI's shares at a valuation of $30 billion, and ScaleAI's founder Alexandre also joined Meta as Chief AI Officer. After Alexandre founded Perle, his work was fundamentally different from that of ScaleAI. ScaleAI belongs to a data annotation factory, and as mentioned earlier, Alexandre managed millions of data annotators at the time, which meant that ScaleAI's annotation work could only be the most basic type that could be done manually, such as checking traffic lights for verification codes, and annotators did not need complex knowledge reserves and reasoning. Perle mainly relies on high-quality expert data, and the annotated content requires a certain level of knowledge threshold, such as finding tumors from X-ray photos, identifying overbearing clauses in a contract, etc. These tasks must be completed by practitioners in the relevant fields. Therefore, its annotators are different from ScaleAI, which only requires manual clicking of the mouse. Perle's annotators are composed of expert networks in biology, medicine, computer science, etc. Ahmed himself is also a master's degree holder at MIT. However, in the past, ScaleAI was also able to earn meager income through part-time jobs due to its simple job content. Data annotators were also easily recruited on a large scale. If one wants to advance to work that requires professional knowledge background, although the compensation for such professional data is also very high, it is difficult to find these people. After all, they are highly educated people who already have decent jobs. More importantly, even if someone annotates data, it is difficult for the platform to verify the accuracy of their work. So Ahmed used blockchain to build a decentralized expert network, where users can receive not only bonus incentives but also reputation incentives for their work completed on the platform. Additionally, peer review can be conducted on the chain, where other validators can review their work after a label is submitted. If errors are found and arbitrated successfully, additional incentives can be obtained. As AI gradually enters various industries, especially in some professional fields, high-quality data annotation will become scarce. Ahmed probably decided to start Perle after ScaleAI realized this.