Title: The Emergence of AI Agents in the Web3 Ecosystem
Introduction:
As the integration of AI and the cryptocurrency market gains attention, there is a growing focus on projects that address data collection, GPU computing, and data inference in the AI field. These protocols, such as Akash Network and Ritual net, stand out in the large AI industry by leveraging the decentralized, incentivized, censorship-resistant, and privacy advantages provided by web3. While these projects have created captivating applications, their impact on regular web3 users remains limited, as they have not effectively onboarded new users to the web3 space.
The Rise of AI Agents:
With the rapid development of Web3, new encryption protocols, tokens, and applications are emerging. Even experienced users find it challenging to navigate this complexity. Therefore, there is a growing need to create AI agents, intelligent assistants designed to simplify the use of encryption applications. AI agents exist at the intersection of cryptocurrency and artificial intelligence, aiming to address the complex user experience issues in the cryptocurrency space. Imagine a future where you can simply tell an AI agent what task you want to accomplish on the blockchain, and it will automatically write and execute the necessary transactions for you.
AI agents will help us build an intelligent layer on top of existing DeFi infrastructure, serving as the bankers, investors, traders, and fund managers in the web3 ecosystem. They will leverage underlying technologies to conduct transactions on the blockchain. The integration of DeFi and AI is expected to bring advanced applications such as AI-driven lending, smart liquidity mining strategies, automated market making, and AI-assisted portfolio management. The applications of AI agents are not limited to finance but can also be utilized in the gaming industry to provide users with assistants and pets, enhancing their gaming experience.
Classification of AI Agents:
AI agents in the evolving field can be broadly classified into the following categories:
Game AI Agents:
Teams like Parallel Colony are developing game AI agents to enhance the gaming experience for users. These AI agents operate within the Web3 environment and interact with players and game elements through on-chain smart contracts. AI agents can act on behalf of users or serve as pets/assistants within the game. These agents can also interact with other agents and trade assets.
Autonomous Portfolio Agents:
These AI agents can manage asset pools from different users. The goal of these agents is to maximize returns by allocating assets to various DeFi strategies using off-chain AI data streams. This essentially provides an AI-powered portfolio management service. To ensure minimal trust in the protocol, some projects enable zero-knowledge proofs (ZK) through protocols like Modulus to provide on-chain AI inference proofs.
Prompt-based AI Agents:
Imagine a future where you can simply tell an AI agent what goal you want to achieve on the blockchain, and it will automatically write and execute the necessary transactions.
This is the goal for most AI agent projects, where prompts could potentially become the preferred way for regular users to interact with the blockchain. Projects like Wayfinder, Brian Knows, and Aperture Finance are developing interfaces similar to ChatGPT, allowing users to directly engage in intelligent transactions on the blockchain by chatting with AI agents. These protocols utilize large language models (LLM) to convert user prompts and intentions into executable transactions.
Discussion of AI Agent Protocols:
1. Autonolas Agent:
Autonolas is a platform that supports the creation and management of autonomous agent services. These services, known as agent services, operate independently off-chain as a multi-agent system (MAS) to achieve common goals. Autonolas enables developers to build and deploy autonomous agents that seamlessly collaborate off-chain while leveraging blockchain technology to enhance on-chain functionality.
2. BabyDegen:
This agent, built on the Olas Network, is an example of such an agent.
3. AutoTX developed by Polywrap:
Polywrap is constructing a network of professional AI agents to perform complex tasks for web3 users and protocols. These agents efficiently solve problems and make decisions using crowdsourced insights, on-chain and off-chain data sources, task planning, and batch transactions. Current agents include payment, market research and trading, social content curation, and AI-assisted public product funding. Polywrap’s future plans involve expanding the range of professional agents, decentralizing their execution, and developing the system through community-driven governance. AutoTx is an example of such an AI agent.
4. Parallel Colony:
Parallel Studios takes a fresh approach to AI agents through Colony, a new AI-driven web3 survival game. In Colony, highly autonomous AI agents or “avatars” continuously learn from the environment. Players must guide these avatars, which possess different skills and abilities, and collaborate with them to survive in competing colonies on future Earth. Colony stands out by incorporating continuous learning into its gameplay. AI avatars develop unique personalities and worldviews, learning from their own experiences, identities, and goals. Additionally, these avatars can autonomously manage digital assets through dedicated web3 wallets, enabling them to trade with other in-game avatars.
5. Wayfinder:
Wayfinder is creating a “map” for AI agents to handle tasks and simplify users’ on-chain activities. By open-source development and incentivizing builders with $PROMPT tokens, Wayfinder aims to expand the navigation instruction network. Wayfinder’s path will enhance the capabilities of AI agents over time, connecting blockchain and off-chain data sources, allowing users to easily execute tasks through command prompts. Their innovation aims to make blockchain interactions more efficient and accessible, improving users’ lives.
6. Noya:
Noya is a decentralized finance (DeFi) protocol that enables AI agents to manage liquidity across multiple blockchains securely and accurately. It utilizes a composable system built from scratch, including a private guardian network, an AI-compatible oracle, and a competitive environment for AI and strategic managers. Noya has multiple vaults, each tailored to different user intent profiles. The protocol has its own AI oracle designed to read various DeFi markets and pass information to AI agents.
7. Brian Knows:
Brian provides an API that developers can integrate into their applications, enabling users to generate web3 transactions through prompts, such as “Can you swap 10 USDC for ETH on Uniswap on the Ethereum mainnet?” They also offer smart contract deployment services through prompts. In the backend, the team uses LLM to convert prompts into web3 transactions, which are then executed through their preferred protocols and solvers.
8. Aperture Finance:
Aperture Finance revolutionizes DeFi by providing liquidity management services through user-friendly protocols. It enhances the DeFi user experience by incorporating an intuitive chatbox interface inspired by GPT, allowing users to express their goals in natural language. Third-party participants, known as solvers, process requests by optimizing the workflow to ensure efficient and cost-effective execution.
9. Fungi Agent:
Fungi utilizes the powerful features of smart accounts and account abstraction to provide a self-custodial AI agent experience. Fungi allows users to instruct commands through its interface and processes real-time blockchain data, autonomously executing operations based on user instructions. Users can chat with Fungi to deepen their understanding of cryptocurrencies, receive personalized guidance, execute on-chain transactions, create custom DeFi strategies (Hyphas), and even monetize these Hyphas by sharing them with the community. Fungi is a network of agents that interact with each other and learn from past experiences, serving as a financial superintelligence accessible to everyone.
10. Fyde Protocol:
Fyde enables users to increase their cryptocurrency holdings faster by depositing into diversified AI-managed vaults that lock in yields based on market performance and reduced volatility. Users can deposit various tokens into these vaults and receive $TRSY, a token representing their share in the vault assets. Fyde aims to maintain the liquidity of $TRSY under various market conditions, enabling users to trade with ease.
The Need for an AI Identity Verification Layer:
In all these upcoming AI and intent-related projects, the potential use cases range from handling simple tasks to authorizing AI agents to execute complex DeFi strategies for optimal returns. However, these AI agents face two main challenges: they cannot achieve true autonomy, as they currently require user signatures or approvals for transactions, and if they opt for automation, they compromise security. Protocols are exploring alternatives to automation, such as approvals, centralized vaults, and shared private key pairs, which pose significant risks as they make the protocol custodians of user assets.
We need an AI identity verification solution that allows transaction authorization to be delegated to AI agents but restricted to specific permissions and rules defined by users.
Conclusion:
The integration of AI agents in the web3 ecosystem holds great promise for advancing applications in various sectors, including finance, gaming, and more. These agents simplify user experiences, automate complex tasks, and enhance decision-making processes. However, ensuring security and defining clear boundaries for AI autonomy remain crucial challenges. With further advancements and the development of AI identity verification layers, AI agents have the potential to transform the way we interact with blockchain technology and empower users in the web3 space.