Every AI project comes with a complex whitepaper.

Although there’s a growing sentiment in the market that AI tokens are becoming more like memes, quickly understanding the narrative of a hot AI project through its whitepaper remains crucial for assessing the value of its tokens.

In February of this year, the new AI project Talus Network completed its first $3 million financing round, led by Polychain Capital, with participation from dao5, Hash3, TRGC, WAGMI Ventures, and Inception Capital.

Today Talus also released white paper, further explaining both its business scope and token economy.

The following is a summary of the important contents of the white paper to help you quickly understand Talus Network.

L1 for AI agents

Talus is a platform designed to integrate AI with blockchain technology. It enables intelligent agents to live, interact and transact in the Web3 ecosystem by providing a high-throughput L1 blockchain (powered by the Move programming language), enhanced with a native AI stack.

You can think of Talus asA decentralized intelligent AI agent center, solves key issues such as data privacy, security and accessibility, and promotes transparent and efficient interactions in the AI ​​ecosystem.

AI narrative is of course a hot topic, but is it logically consistent to design an L1 specifically for AI agents?

The answer given by Talus is:

In terms of openness, the openness and composability of blockchain applications make it easier to view, track and trust the behavior of artificial intelligence agents; it is easier for users to find the most suitable artificial intelligence agent based on verifiable past performance records.

In terms of autonomy, blockchain infrastructure enables intelligent agents to interact autonomously, allowing them to execute outcome decisions.

Specifically, Talus actually allows for the native design and deployment of decentralized on-chain intelligent agents that seamlessly, trustlessly, and interoperably utilize on-chain and off-chain resources and services.

It establishes a protocol to represent, utilize, and trade these agents, resources, and services in a permissionless and verifiable manner.

A combination of existing components and new features

So, how does Talus implement it?

The answer lies in a combination of existing technologies and new capabilities. These components work together to provide a decentralized, efficient and secure intelligent agent platform. The key components, from the bottom layer to the application layer, can be summarized as:

1. Protochain Node：

• At the core of Talus is a proof-of-stake (PoS) blockchain node called Protochain Node based on the Cosmos SDK and CometBFT. This choice provides flexibility, robustness, and high performance.
• This technical architecture ensures the security and scalability of the Talus blockchain, providing a solid foundation for the operation of intelligent agents.

1. Sui Move & MoveVM：

• Talus uses Sui Move as its smart contract language. The Move language is known for its high performance, security, and programming properties.
• By using Move, Talus is able to enhance the security of on-chain logic and simplify the creation, transfer and management of digital assets, enabling more efficient smart contract execution.

1. IBC (Inter-chain communication protocol)：

• Using IBC (Inter-Blockchain Communication Protocol), Talus enables seamless interoperability between different blockchains, enabling intelligent agents to interact and utilize data or assets across multiple blockchains.
• IBC provides atomicity and scalability of cross-chain transactions, ensuring reliability and consistency of operations.

1. Mirror Objects:

• Talus introduces the concept of mirror objects for representing and validating off-chain resources on-chain, such as models, data, and computing objects.
• Mirror objects bridge the gap between the high computational demands of AI processes and the blockchain environment, ensuring the uniqueness and tradability of resources.

1. AI Stack:

• Talus provides an SDK and integration components to support the development of intelligent agents and interaction with off-chain resources.
• The AI ​​stack also includes integration with Oracles, ensuring that intelligent agents can leverage off-chain data for decision-making and reaction.

1. Onchain Smart Agents:

• At its core, Talus provides an economic system of intelligent agents that can operate autonomously, make decisions, execute transactions, and interact with on-chain and off-chain resources.
• Intelligent agents possess autonomy, social ability, reactivity, and proactiveness. Autonomy allows them to operate without human intervention, social ability enables interaction with other agents and humans, reactivity enables them to perceive changes in their environment and respond promptly, and proactiveness enables them to take action based on goals, predictions, or anticipated future states.

The figure below shows the architectural blueprint of the Talus intelligent agent and explains how the various components work together.

SDK: It is a bridge between smart agents and other components such as resources, oracles, UI and smart contracts. It provides the necessary libraries and tools to help developers build and integrate intelligent agents. The SDK simplifies the development process and provides a unified interface, allowing intelligent agents to efficiently utilize the resources and services provided by the platform.

Resources: These include AI models, GPU computing resources, and other computational resources. These resources interact with intelligent agents through SDKs, providing the necessary computational power and data support for intelligent agents. AI models can be pre-trained models that intelligent agents can use for inference and decision-making.

Oracle: Oracles provide external data to intelligent agents, enabling them to make decisions based on the latest real-world information.

UI Components: UI components allow users to interact with intelligent agents. Through user-friendly interfaces, users can configure, manage, and monitor the operational status of intelligent agents.

Through this architecture, Talus achieves the autonomy and decentralization of intelligent agents, ensuring efficient utilization of resources and transparency of the system, and driving the integration of AI and blockchain technologies.

Token Economics and Use Case

The core of the Talus ecosystem is the TAI token, which serves multiple functions on the platform. The key roles of the TAI token in the Talus ecosystem are as follows:

• Medium of Exchange: All transactions, resource purchases, and trading activities within the ecosystem are conducted using TAI tokens. This ensures that all economic activities within the ecosystem revolve around the TAI token, increasing its circulation and demand.
• Resource Purchases: Resource providers can earn TAI tokens by offering computational power, data, or models. In turn, developers and users can use TAI tokens to acquire these resources, driving the development of the ecosystem.
• Network Security: TAI token holders can participate in the Proof of Stake (PoS) mechanism of the network by staking tokens to maintain network security and consensus, while receiving corresponding rewards.
• Governance: Users holding TAI tokens can participate in platform governance by proposing and voting on decisions regarding platform improvements and development directions, ensuring community democracy and transparency.

However, the whitepaper has not yet disclosed the token economics model for TAI. The details of the token are speculated to still be under design, awaiting further information to be supplemented.

Regarding the application scenarios of AI intelligent agents, Talus provides the following functionalities that can be implemented in the Web3 domain:

• User Experience Enhancement: Intelligent wallets and analytics tools provide real-time monitoring and analysis of transactions and asset statuses, offering users personalized blockchain browsing and project management experiences.
• DeFi: Optimizing liquidity management, automating on-chain portfolio tracking and management, and enhancing the efficiency and effectiveness of DeFi applications through intelligent exchange aggregation and path optimization.
• DAOs: Supporting automated financial and asset management, AI-based governance, and decision support.
• Internet of Things (IoT): Assisting in managing IoT device ecosystems, scheduling intelligent device maintenance, ensuring the identity and security of IoT devices, and optimizing logistics and supply chain management.
• Gaming / SocialFi: Personalized on-chain storytelling, virtual economy management, intelligent NPCs, and inter-agent social networks bring new experiences and interaction methods to gaming and social applications.
• AI and Data Ecosystems: Supporting collaboration between model developers and data providers, promoting the development and monetization of specialized AI models, efficiently utilizing and monetizing data and computing resources, and supporting crowdfunding models for research and development.

From the content provided in the current whitepaper, Talus has only clarified the scope of its project and use cases. There is not much presentation regarding more technical details, economic models, and actual effects, which aligns with its release of a “Litepaper” version.

However, it is undeniable that there is fierce competition within the AI area, and projects with promising performance in the AI agent category are emerging one after another. How Talus chooses the right timing and catalysts to launch its network and incentivize users may become the key factor in the success or failure of its listing strategy.

After all, in the current market situation where VC investments are staked, FDVs are high, and low-circulation tokens are common, attracting more users to participate and impressing the community with solid products and technology are key initiatives for high-profile AI projects to capture value.

Statement:

1. This article originally titled “Talus White Paper Explained: Decentralized AI Agent Center” is reproduced from [techflow]. All copyrights belong to the original author [深潮 TechFlow]. If you have any objection to the reprint, please contact the Gate Learn team, the team will handle it as soon as possible.

2. Disclaimer: The views and opinions expressed in this article represent only the author’s personal views and do not constitute any investment advice.

3. Translations of the article into other languages are done by the Gate Learn team. Unless mentioned, copying, distributing, or plagiarizing the translated articles is prohibited.