The recent crazy suggestion from @ 0G_labs is to work hard and join in August. August is a month to showcase your skills, hold your ground, and exert influence. @0G_labs laboratory will lead the era of decentralized AI, and the official is working with our evangelists to promote this process. It seems that TGE is not far away. What do you guys think? Introduce how @ 0G_labs uses a decentralized architecture to promote AI fairness and address the privacy, fairness, and value alignment issues of traditional centralized AI platforms. Solution 0G has designed a decentralized AI operating system that adopts a modular+layered architecture, with a core consisting of four networks and an innovative sharding mechanism for infinite horizontal expansion: 1. Storage Network Nodes connect through P2P networks and record the submission and order of each data block in the consensus network. Organized by partition, supporting multiple parallel independent consensus networks to ensure equal security. Nodes receive rewards (incentivizing contributions rather than punishing mistakes) by submitting proof of data accessibility. Equipped with a log layer (archiving unstructured data) and a key value layer (managing structured data), it facilitates AI data processing and indexing. 2. Data availability network (DA Network) Used in Layer2 or decentralized AI verification scenarios (such as ORA/OPML providing AI task fraud proof). Divide data availability into data publishing channels and data storage channels: Storage channel: Use erasure code slicing to horizontally expand nodes and transmit massive data. Release channel: Confirm data availability through node signature aggregation, reducing the burden of consensus broadcasting. DA nodes need to be both consensus network stakers, forming a randomly selected secure arbitration group (based on VRF to ensure honest distribution). Provide GPU accelerated erasure code computation, significantly improving throughput. 3. Service Network A universal framework that supports data retrieval, AI inference, and even training tasks. Service providers can register types, prices, and verification methods, and users can discover and prepay fees to directly call the service. Request/response records are settled by smart contracts and used to evaluate service quality and allocate rewards. The workload can be perfectly sharded, minimizing blockchain overhead. 4. Consensus Network Responsible for recording the submission and sequence of each network, supporting multiple consensus parallelism, and eliminating single bottlenecks. Solved the problems of privacy leakage and value misalignment caused by centralized AI platforms, where data and algorithms are handled by a few institutions despite their power, Decentralized AI can improve transparency and achieve alignment of diverse values, but there are challenges in terms of performance and infrastructure. 0G has achieved an infinitely scalable decentralized AI infrastructure through storage network+data availability network+service network+multi consensus mechanism, combined with sharding and GPU acceleration, allowing AI computing, storage, and verification to run efficiently in an open network, thereby promoting true fairness of AI. At present, there is still time until the end of August. If you haven't participated yet, remember to join us.