The market is too hellish, so it's better for the losing troops to continue their losses! Recently, Sahara AI @ SaharaLabsAI's Siwa testing network and incubator have been launched simultaneously. UUs who missed Season 1 and Season 2 can take advantage of this and introduce the testing network and data situation here 🚩 Highlights of the first two quarters: Sahara produces high-quality 'AI oil' Sahara does not engage in short-sighted AI and always fulfills its commitment to effective data for AI. Sahara has very high requirements for the professionalism and purity of AI data, so the node activities in the first two seasons did not fully release opportunities, but were more concerned about the quality of data generated by nodes -Nearly 800000 people applied for S1, but only 10000 were ultimately selected; -The number of S2 candidates skyrocketed to 2.2 million, but only 100000 were ultimately selected as contributors; -Currently, Sahara has approved approximately 1.94 million data points, making it the world's largest decentralized AI data service platform So overall, it shouldn't be very convoluted 🚩 L1 AI narrative, strong data capability Speaking of technical aspects, Sahara AI is the L1 that supports the development of Web 3 and AI innovation projects: -There is a self-developed EVM compatible, AI native Layer 1 blockchain, namely Sahara Blockchain; -Sahara AI Studio is a one-stop toolchain that covers dataset management, model training, and computing power support; -Sahara AI Data Service Platform, the world's largest user contributed data (collection, refinement, annotation) platform; -The feasibility and efficiency of Sahara's large-scale data collection and annotation have undergone decentralized peer review and internal QA, with an accuracy rate of 92%. Only 83% of simple research tasks and 67% of in-depth research tasks have passed peer review, which precisely reflects the system's ability to effectively screen out low-quality submissions and maintain the accuracy and reliability of the dataset After expanding the number of nodes in the second season, Sahara AI was able to maintain data quality, which also demonstrates its data strength. ⭐ Participation Method - Siwa Test Network Opportunity: The final sprint before the main network goes live For Sahara AI, the Siwa testnet is highly likely to be the last round of comprehensive testing before the mainnet goes live and TGE releases its coins, and may be the last chance to get on board The simultaneous launch of Siwa testnet and incubator also visually demonstrates Sahara's determination to build an AI ecosystem well. From the perspective of an incubator, it focuses on the two core tracks of AI infrastructure and AI applications, in order to screen out high potential and high growth Web3 AI projects For the Sahara AI ecosystem, the collaborative operation of testnets and incubators can form a virtuous cycle. On the testing website, project operation data and user feedback can provide reference for other projects in the incubator, promoting communication and cooperation between projects Previously, Sahara invited the three AI giants DeepSeek, OpenAI, and Anthropic from web2 for their first AMA, and wrote an article specifically discussing it, Portal 👉🏻 https://(x.com)/yuyue_chris/status/1871220122054176966