Which AI-related blockchain projects are worth early attention as AI agents gain popularity in narrative?
AI Concept, Always in Demand.
As a narrative throughout the year, regardless of the ups and downs of the cryptocurrency market, there are always AI projects that perform astonishingly well. In different inventory and outlook articles, you can almost uniformly see optimism about AI.
But AI is a very broad concept, which specific sub-projects should you bet on?
A relatively safe choice is to use short-term hot events as catalysts and look for cryptocurrency projects directly related to the AI concept.
For example, AI agents.
On January 11th, ChatGPT officially launched its store feature. Unlike traditional applications, the GPT store does not require users to have any programming experience. Users only need to input the desired functionality they want GPT to achieve in simple natural language, and the system will create a customized AI chatbot for them.
In other words, this is an AI agent store, which contains a large number of robots that can handle certain fixed tasks on your behalf based on certain logic. With the appeal of GPT, it is foreseeable that there will be an explosion of applications in the store, and there may also be AI agents related to crypto.
Whether these robots are useful or not is one thing, but the popularity of the AI agent concept is another.
Almost at the same time, well-known crypto VC Pantera explicitly expressed interest in the combination of AI agents and Web3 in a recent article published by them for 2024.
(Read more: Pantera focuses on AI trends in 2024, Web3 will help in reasoning, data privacy, and incentives)
If we take the GPT application store as a catalyst and consider the attention of top VCs as a gust of wind, will the narrative of AI agents be ignited this year?
We cannot predict the future, but we can be prepared.
So, what we should clarify now is:
What is the principle of AI agents and which cryptocurrency projects may directly benefit from them?
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AI agents, what does it have to do with the crypto industry?
Which cryptocurrency projects are related to AI agents?
Type 1: Cryptocurrency projects that directly do AI agent business
Autonolas ($OLAS): AI agents designed to optimize cryptocurrency projects
Fetch.ai ($FET): An old project, an AI agent that serves the entire industry
PAAL AI ($PAAL): Focused on building AI assistants for crypto users
Type 2: Projects that enhance their existing business with AI agents
First, we need to understand how AI agents work, so that we can identify which cryptocurrency projects truly belong to the scope of AI agents and which ones are just riding on the concept.
The robots in the GPT store give people a sense of what AI agents are, but in principle, what kind of product can be considered an AI agent?
In my opinion, judging whether a product is an AI agent can be done simply by grasping the key question:
Using AI technology, can the program or device automatically execute tasks or provide assistance to users?
From simple chatbots to complex automated systems, they can all be considered AI agents. But these things should at least have the following characteristics:
Automation: Can execute tasks with little or no human intervention.
Perception of the environment: Can perceive its operating environment through sensors or data input.
Decision-making: Can make decisions based on its programming and received data.
Learning and adaptation: Has the ability to learn and improve its performance based on new data and experiences.
Interactivity: Can interact with human users or other systems, respond to requests, or provide information.
But if we abstract the above features, we will find that AI agents are somewhat similar to smart contracts: given default conditions, they automatically execute results.
So if we want to identify whether a project truly uses AI agents or just rides on the AI concept with smart contracts, we can simply identify it through this dimension:
Does it have initiative?
Smart contracts lack autonomy; they passively react based on pre-written rules (reactive) and do not have the ability to make autonomous decisions based on changes in the external environment. For example, you set a certain price to buy a token at a certain time.
In contrast, AI agents are generally considered active, able to collect data, learn, make decisions, and initiate tasks without external commands. For example, monitoring market data and buying a token when the AI agent itself deems the price to be appropriate.
Understanding this difference, let’s take a look at the connection between AI agents and the crypto industry.
The co-founder of well-known crypto project Space and Time, @chiefbuidl, made a very classic and vivid analogy:
Cryptocurrencies are like cash, blockchains are like cash registers, Dapps are like POS machines, and AI agents are like cashiers.
By understanding this analogy, when cryptocurrencies are used for transactions like cash, the underlying blockchains are actually responsible for recording and accounting. Dapps act as transaction interfaces similar to POS machines, and AI agents become the cashiers, directly telling you:
You don’t need to worry about how to use the money or keep accounts; you just need to roughly tell me your intentions, and I will automatically spend the money for you and provide the services you want.
In this chain, cryptocurrencies, blockchains, and Dapps are actually complex and difficult to understand, while AI agents are the part that is most likely to interact with users and simplify the experience.
Therefore, AI agents can be used to improve the user experience of cryptocurrency products (including but not limited to the trading experience).
So, which projects will be related to the concept of AI agents?
Perhaps we can divide the projects into two categories: one category is projects that have the ability to provide AI agents themselves for others to use, and the other category is projects that use AI agents to enhance their original products’ experience.
Autonolas ($OLAS): AI agents designed to optimize cryptocurrency projects
Autonolas is a project directly related to AI agents. Its business is to design AI agents for the cryptocurrency industry to handle tasks in different scenarios.
Specifically, the Autonolas technology stack includes:
Autonomous agent services
Composable autonomous applications
On-chain protocols for protecting agent services and incentivizing development
(Read more: In-depth analysis of Autonolas: AI agent-driven off-chain services, product, and economic model)
The key here is autonomous agent services.
The AI agents that make up these services can extract data from any AI model in the world. This includes every GPT, LMM, or subnet (which means it can even interact with $TAO). Through service coordination, models used to handle specific tasks are assigned to certain agents.
So what can these agents do?
From the product collection given on the Autonolas website, it involves business related to the crypto industry, including but not limited to using AI agents to predict markets, predict certain protocols’ behaviors, etc.APY income, acting as an oracle to provide more accurate off-chain data, helping DAO governance, automatically managing operational smart contracts, and automatically establishing DeFi liquidity pools, etc.
Overall, there is a place for AI agents in all process-oriented operations related to cryptocurrency projects.
Autonolas’ other two businesses are based on autonomous services. Through these basic autonomous services, other developers can freely combine their functions to form their own applications; at the same time, Autonolas can also create an application store that allows developers to register and monetize their services.
From the data, the usage of the project’s AI agent services is still increasing. As Autonolas theoretically can become the standard for all cryptocurrency projects that need automation, it can add an AI agent layer to the places in its own project that require automation.
Its token, OLAS, was listed on the on-chain liquidity pool in July last year, with a price of around $0.1 at the time. The current price is around $4.6, and the market value has reached $200 million.
However, considering the narrative of AI and the role the project is expected to play in business, the current market value and price are not particularly overvalued. As a comparison, $TAO, which has a different business but the same AI narrative, has a market value of around $1.5 billion.
Fetch.AI (FET) also focuses on building and promoting AI agent services. These agents are designed as modular components that can perform specific tasks through programming. These agents can autonomously connect, search, and trade, creating dynamic markets and changing traditional economic activities.
Compared to OLAS, Fetch can be considered an older project. It was established in 2017 and went live in December 2019. It has already integrated with Cosmos’ IBC, making it an AI project in the Cosmos ecosystem.
However, Fetch is not only focused on AI agents for cryptocurrency projects but extends its services to different industries. Based on the examples provided by the official website, its business can reach various services such as e-commerce, automotive, legal, IoT, and weather.
Another feature of Fetch is its developer-friendliness.
Fetch has also launched Agentverse, a no-code management service that simplifies the deployment of AI agents. Just as traditional no-code platforms (Replit) and services like Github’s Copilot allow the general public to write code, Fetch is striving to further democratize Web3 development in its unique way.
Through Agentverse, users can easily launch their first agent, which greatly reduces the threshold for using advanced AI technology.
However, as a project with a long history, Fetch’s actual products are still in the wish list stage and have not been fully open to the public. This also raises doubts about whether the project is really making solid progress.
In terms of tokens, FET is used as network gas fees and is also used for node staking to maintain network operation. Its market value has reached $500 million, and in my opinion, it has weaker cost-effectiveness compared to OLAS, with limited room for growth. However, it can still be seen as a relatively Beta project and may experience certain price increases when there is a catalyst in the AI agent narrative.
PAAL aims to create an AI-driven platform that is easy to access, user-friendly, and provides comprehensive knowledge, support, and tools in the ever-changing world of cryptocurrency and blockchain technology.
The project aims to provide users with their own personal AI assistant, which they can rely on to obtain accurate and reliable information, assistance in customization and scalability, and a deeper understanding of the crypto ecosystem.
Specifically, we can actually understand PAAL as a crypto version of GPT and trading BOT.
PAAL’s main AI tools include:
– Mypaal: an AI robot with certain knowledge that answers various questions about crypto projects from users.
– Autopaal: acting as a crypto expert, providing research, insights, and analysis centered around cryptocurrencies, monitoring market trends, and notifying users of specific situations.
– Autopaal X (not yet launched): an advanced version of the above two tools, adding the functionality of automated trading and sharing income with $PAAL stakers, providing additional incentives for staking.
If we look at it conceptually, PAAL can indeed be considered an AI agent, but its business is more focused compared to the previous two projects, currently only serving crypto users’ trading and learning. If we don’t dwell on specific differences, we can even directly understand it as an advanced trading BOT.
Currently, the total market value of the token $PAAL is around $100 million, lower than the previous two projects in terms of market value. However, considering its narrow business focus and its strong correlation with the crypto market, I believe its overall imagination is not as high as OLAS.
The above-mentioned projects are directly involved in AI agents, while there are also some projects whose main business is not entirely AI agents, but have integrated this functionality into their existing business to improve their performance.
Due to limited space, we will not provide a more detailed introduction to the principles of these projects. Here, we will simply list them:
– Root Network ($ROOT): An L1 optimized for metaverses, games, and Web3 user experiences, provided with AI and metaverse technology support by Futureverse. It can currently integrate AI agent capabilities into games supported by the network to enhance the gaming experience.
– Parallel ($PRIME): A sci-fi card battle game invested by Paradigm. The game currently uses AI characters to create new in-game items, which can be stored in the AI characters’ own wallets, essentially creating an AI agent for creating game assets.
– Oraichain ($ORAI): A company that provides AI Layer 1 data economy and Oracle services. Its goal is to create a trusted AI tool to support Web3, scalable dApps, and data economies. The project recently provided a token analysis tool called DeFi Lens, which also integrates AI agent capabilities for predictive analysis of tokens.
Due to limited resources, we have not listed all the projects related to AI agents in the market.
However, regardless of whether these projects are directly or indirectly related to AI agents, besides the hot concept of AI, it is more important to see if their AI agent business is actually practical and not just empty talk.
The AI bubble is significant, and the bubble of cryptocurrency projects riding on the AI trend may be even bigger.
It is more beneficial to focus on projects with more solid fundamentals, which are more likely to capture solid and sustainable value throughout the year.
AI agent
Further reading:
BITO outflows $270 million, caused by the crowding out effect after the launch of Bitcoin spot ETF?
Bitcoin falls below $40,000 this morning, is it due to FTX shorting GBTC?
