If you break down most so-called "AI public chains," you'll find that they are mostly just doing incentive layers or fine-tuning layers on-chain, while the training data and model storage remain centralized. Strictly speaking, they can only be considered "quasi-AI Layer1" or even "pseudo-AI Layer1." The biggest difference with 0G @0G_labs is that comprehensive decentralization is not just about economic incentives and coordination, but about modularizing and breaking down data storage, model training, inference, and computing power markets, all implemented in decentralized underlying infrastructure. The highlights of 0G mainly lie in three points: 1️⃣ Modular design: From 0G Chain, Storage, DA to Compute, Marketplace, Alignment Nodes, each layer can operate independently and can be flexibly replaced and upgraded to adapt to future AI technology iterations. 2️⃣ Storage and performance advantages: 0G Storage is optimized for high-frequency read and write for AI, far superior to the slow experience of IPFS/Filecoin, and is a truly decentralized storage capable of supporting AI models and large-scale data. 3️⃣ Ecosystem construction and implementation: Collaborating with over 300 projects, the testnet has already run billions of interactions, and combined with the benchmarking logic of BitTensor+, the ecosystem potential is enormous. 0G is not just shouting the slogan "AI + blockchain," but truly completes the key puzzle of AI Layer1!