Deep Dive
1. Aristotle Mainnet Launch (22 September 2025)
Overview: The Aristotle Mainnet went live as a modular Layer-1 blockchain tailored for AI workloads, unifying decentralized storage, compute, and data availability (DA) layers. It achieved 11,000 TPS in testing, supported by RPC providers like QuickNode and Ankr.
This architecture separates execution, consensus, and settlement layers, allowing developers to customize components for AI applications. The DA layer uses probabilistic sampling to verify data availability efficiently, reducing costs for large-scale AI models.
What this means: This is bullish for 0G because it enables scalable, cost-effective AI model training and inference on-chain, appealing to developers building decentralized AI agents or high-throughput dApps. (Source)
2. EVM + CometBFT Consensus (22 September 2025)
Overview: 0G’s chain combines EVM compatibility with a CometBFT-derived Byzantine Fault Tolerance (BFT) consensus, enhancing transaction finality and interoperability. Storage nodes use erasure coding and Proof of Random Access (PoRA) to validate data integrity.
The hybrid design allows seamless integration with Ethereum-based tools while optimizing for AI-specific workloads like low-latency data retrieval.
What this means: This is neutral for 0G as it balances familiarity for Ethereum developers with novel infrastructure for AI, though adoption depends on ecosystem traction. (Source)
3. ERC-7857 iNFT Standard (Q3 2025)
Overview: 0G introduced the ERC-7857 standard for "intelligent NFTs" (iNFTs), enabling AI agents to be governed as NFTs. This allows users to own, trade, and delegate AI behavior rules on-chain.
The standard integrates with 0G’s AI Alignment Nodes, which audit agent actions for compliance with predefined objectives.
What this means: This is bullish for 0G because it pioneers a new use case for NFTs in AI governance, potentially attracting gaming and DeFi projects seeking verifiable AI agents. (Source)
Conclusion
0G’s codebase updates reflect a strategic push to position itself as the infrastructure layer for decentralized AI, combining modular design with EVM compatibility. While technical milestones like the Aristotle Mainnet demonstrate execution capability, long-term success hinges on developer adoption. How will 0G balance its ambitious AI focus with the practical needs of existing Web3 developers?