Talus Network: An Explanation of On-Chain AI Agent Infrastructure Based on Protochain and MoveVM @TalusNetwork is a high-performance layer 1 blockchain designed for AI agents and autonomous smart agents. The core structure of this network consists of Protochain and MoveVM, supporting parallel transaction execution while maintaining fast processing speeds and security. MoveVM is an object-oriented virtual machine based on Rust, ensuring resource management and state consistency. In Talus, all agents, assets, and resources are represented as objects, enabling complex agent behaviors and interactions. Smart agents serve as the fundamental units of Talus, maintaining individual states, making decisions, and performing learning and trading. Talus provides an SDK and AI stack for these agents, offering integrated support for state management, memory, learning modules, and more. Additionally, it ensures the transparency and reliability of AI outputs through verifiable AI inference technologies such as opML, zkML, and teeML. The Mirror Object is another key concept of Talus, responsible for connecting on-chain assets and off-chain data. This allows external data or AI models to be securely synchronized with the Talus network, enabling ownership and integrity verification. These Mirror Objects guarantee tamper-proof data synchronization based on cryptographic proofs and the Sign Protocol. Furthermore, partnerships with decentralized storage solutions like @0G_labs, @WalrusProtocol, and Glacier VectorDB enhance data availability and reliability. Talus agents can communicate with other blockchains and external APIs through IBC-based interoperability and the Union protocol. By utilizing verifiable oracles like ORA and Atoma, they can fetch external data or execute AI inferences, recording them in a verifiable manner on-chain. The parallel processing structure of MoveVM minimizes latency and maintains data consistency and security through verifiable computations. From a security perspective, Talus mitigates malicious agent behavior through staking and slashing mechanisms. Agents and operators must deposit a certain amount of tokens, and penalties are imposed if misconduct is detected. Additionally, an on-chain reputation system and challenge protocol have been introduced, allowing the community to directly report and verify wrongful actions. Access rights and behavioral scopes are dynamically controlled through programmable guardrails, reducing the potential for manipulation of AI outputs in collaboration with Atoma and Aizel. Key risk factors for Talus include overload of agent decision-making logic, depletion of computational resources, state explosion, conflicts between agents, delays in data synchronization, and oracle manipulation. In particular, failures in the synchronization of Mirror Objects or attacks by malicious agents can lead to network performance degradation, making real-time monitoring and security checks essential. To assess Talus's technical progress over the next 6 to 12 months, it is necessary to monitor metrics such as the number of agent deployments, the number of transactions between agents, the failure rate of Mirror Object validations, resource usage, gas costs per agent, cross-chain activity levels, and slashing and reputation update events. These indicators will serve as key signals in determining whether Talus can reliably operate a large-scale agent network. Talus Network is building a new on-chain ecosystem centered around AI agents, pursuing high performance, transparency, and autonomy simultaneously through its unique structure that combines Protochain and MoveVM. This can be seen as an attempt to implement an 'on-chain artificial intelligence society' that can make judgments and act independently without human intervention.