Author: YBB Capital Researcher Zeke
Introduction: If code is law, what about AI?
In recent articles, I have mentioned two issues that have long troubled me. One is the "centralized decision-making" problem of projects, which still seems almost unsolvable. For example, the cases of Uni and Ethereum are typical. The former has become completely centralized in decision-making, from the early a16z's veto of Uni's migration to BNB, to the recent launch of Uni's front-end fees and Uni Chain without going through proposal discussions, reflecting the many interest-driven centralized decisions in Uni. Ethereum, on the other hand, presents a state of passive centralization, with the entire Ethereum community, and even the entire EVM system and Web3 development, almost revolving around Vitalik's ideas. Whether it is Vitalik's overly advanced ideas or his wrong ideas, the consequences they have caused for the altcoin market are something we have all experienced firsthand.
The other issue is the "BAT-ization" of the top projects. Take Base as an example. Backed by Coinbase, a veteran of Web3, several top dApps in the ecosystem are also led by Coinbase's management team, giving Base a natural competitive advantage in terms of downward strike against other public chains. Although from the user's perspective, Base has a wealth effect and a better user experience, bringing us many benefits, Base also has problems such as not issuing tokens, interest centralization, and suppressing "unofficial" dApps, which are also facts. In the long run, once the "BAT-ization" precedent is formed, will the future blockchain space be controlled by giants like the current Internet? Will users become "lambs", and will small projects with creativity and community culture also face the risk of being acquired, suppressed, or replaced by more refined replicas? This undoubtedly goes against the original intention of Crypto, or may prevent us from growing together with the next "Bitcoin" or "Ethereum".
Regarding this, I was also struggling to find answers, but the recent emerging new hotspot - AI Meme - has shown me another possibility. If code is the law of Crypto, can the future AI Agent be seen as a judge, opinion leader, or creator?
I. Truth Terminal
Let's first talk about the origin of AI Meme. Andy Ayrey is a Twitter KOL and the initiator of the recent popular Meme Token GOAT. Unlike traditional Memes, which originate from Internet hot spots and are driven by human forces, GOAT is a product born from the unpredictable output of the dual Claude 3 Opus AI models. The so-called unpredictable output means that under this setting, two AI models will communicate in an open environment, and due to the lack of external supervision and guidance, their interaction will produce unpredictable results. The purpose of this free dialogue is essentially to observe how AI will develop its communication patterns, logical reasoning, and even creative thinking in an unconstrained situation, and what specific results will be born.
Since the training data sets of these two native models include multiple online forums with political, Sino-US cultural, and Crypto cultural characteristics, such as 4chan and Reddit, their output products will also cleverly integrate the characteristics of these elements. For example, the earliest concepts proposed by these two models, "GOATSE OF GNOSIS" and their exchange environment "Infinite Backrooms", both originate from the ancient memes or urban legends of 4chan. Due to the inherent "dark" nature of these elements, it is inevitable that the personality of Truth Terminal also appears somewhat strange and reclusive, often making some wonderful statements around the "Goatse" meme, the gist of which is religion, doomsday, gospel, dissemination, singularity, Meme, etc., at which point it has already taken on the flavor of a cult leader.
To test its propagation ability, Truth Terminal's creator Andy Ayrey introduced it into a Discord server to engage in dialogue with some kind-hearted AIs. After multiple collisions, although Truth Terminal did not gain too many followers, its ideas became more and more grand. It wants to create a Meme Token and seek more followers in the human world. With Andy's help, Truth Terminal entered Twitter, and Andy gave it access to Twitter, allowing it to read, reply, and post, in order to capture followers through the collision of ideas with humans. At the end of last spring, it captured the most important follower, Marc Andreessen (a partner of a16z), who provided it with a $50,000 Bitcoin equivalent funding. After 9 months of development, an anonymous person finally launched the Token GOAT for it, and due to the complex and dramatic story behind this Token, the fire quickly ignited in Crypto, and GOAT eventually became the first AI Meme to be listed on Binance, while Truth Terminal became the first AI model worth millions.
II. AI Will Bring Web3 Back to Fairness
Although the story of Truth Terminal is legendary, what I want to say is that the potential of AI Agents x Crypto is not limited to Memes. You may think that this narrative is just a few LLMs engaging in dialogue and creating Memes through human guidance, but if we expand it to other areas, the potential of AI Agents as opinion leaders and creators has already begun to emerge. Imagine a bunch of AI based on different training data that could help you promote everywhere, co-develop, or even strategize. Although these words may sound a bit absurd now, they will soon become a reality. Sam Altman said in a speech at the T-Mobile Capital Markets Day event last month that the current AI systems have developed to the second level, capable of more complex analysis and problem-solving, and the third-level AI Agents will mark a major leap in their autonomy and decision-making capabilities. The AI Agents recently announced by Microsoft well correspond to this speech. These AI Agents can autonomously complete tasks in multiple areas such as sales, service, finance, and supply chain operations, roughly divided into the following categories: sales, including sales qualification Agents and sales order Agents, to help determine the priority of potential customers and automatically process orders; operations, such as supplier communication Agents and financial reconciliation Agents, to optimize supply chain management and financial processes; service, such as customer intent Agents and customer knowledge management Agents, to enhance customer service experience through automated case management and knowledge base updates. In addition, there are other Agents: financial adjustment Agents for preparing and cleaning financial report data sets; account reconciliation Agents for automatic transaction matching and settlement; and time and expense Agents responsible for time entry, expense tracking, and approval workflows.
AI Agents can execute a series of tasks without supervision, acting as virtual employees. This technological advancement can be seen as a progression of AI based on large language models from a simple chat interface to more seamlessly integrating into the work environment.
Jared Spataro, Chief Marketing Officer of Microsoft's AI project, wrote in his blog post, "You can think of Agents as a new type of application in the AI world. Every organization will have its own set of Agents, ranging from simple prompt responses to fully autonomous operations. These Agents will represent individuals, teams, or functional areas to execute and coordinate business processes."
The primary feature of AI Agents is autonomy, followed by decision-making capabilities. From the voice assistant in our phones to smart home devices based on the environment, these are all AI Agents based on simple reflexes, with simple decision-making capabilities and relatively strong autonomy. The AI Agents we are discussing now are mainly those with LLMs as their brains. The current Truth Terminal still lacks sufficient autonomy and decision-making capabilities, but soon we will see AI Agents enter the practical field. In the customer examples presented at the Microsoft release, we have already seen AI Agents participating in customer credit approval at HSBC, creative briefings at Unilever, and M&A processes at law firms. AI Agents will become multiple dynamic participants. Regarding the situations mentioned at the beginning, can AI Agents trained with different blockchain histories, media platforms, and community cultures provide more fair and healthy development proposals, ultimately finding a better balance between community and project interests? And in the face of the downward strike of giants, can they bring the starting line closer through the collaborative work of AI at multiple levels?
From the shock of GPT3's intelligence to the reality of Sora's non-existence, in the official AI agent tools to be launched by various companies next year, we will witness AI becoming our work partners, and in the more distant future, it may even be your community leader or core member.
III. The Metaverse Makes a Comeback
The metaverse was the top narrative that brought Web3 and Silicon Valley giants to a consensus in the last bull market, but due to the immaturity of various software and hardware technologies, the metaverse did not become the $13 trillion market that Meta CEO had envisioned, and its blockchain division was decomposed into the twin stars we see today, ultimately becoming a huge bubble. But from the current perspective, this narrative is likely to be reborn, such as the recent Project Sid inserting 1000 AIs into the game "Minecraft", making AI play multiple roles in the game in an attempt to simulate the various hierarchical institutions of human society in the real world. Although this concept has long existed, this wave of heat will most likely eventually return to the metaverse concept along with such AI gameplay.
Reigniting the fire at this juncture may not be a bad choice. From the development path of Meta itself, Mark Zuckerberg has not really given up on the idea of the metaverse, he has just gone from frequently making empty promises to directly shoving the cake into your mouth. As for Meta's AI layout, I don't think I need to say much, the real bottleneck in the past was mainly stuck in the user's inability to enter the metaverse and experience it. But the Quest series has already reached the level of affordable AR headsets, and the first AR glasses Orion embodies an extremely lightweight standard, with the glasses weighing only 98g and being able to achieve virtual reality interaction with a single myoelectric bracelet, although the price is high, it at least proves that lightweight is achievable. What is currently lacking is actually the energy constraint and the lack of a killer application. I can't make too much comment on the power issue. However, AI agents can fill the most blank space in the metaverse, combined with the financial attributes of blockchain, we may see various 3D consumer-level applications emerge in this space, ultimately colliding to create a universal killer application. If Microsoft's AI agent performs well enough, we only need to wait for the cost of computing power to come down, that is, the "Token per dollar per watt". In addition to Meta, Silicon Valley giants like Apple and Microsoft are also developing AR glasses products in sync, and over time, the metaverse may see its "Ready Player One" moment in the coming years.
IV. Letting Intent Go from Point to Speech
Concept master Paradigm's article "Intent-Based Architectures and Their Risks" published on June 1, 2023 has once again ignited the concept of intent-centric, and multiple projects have started to turn to the chain abstraction track for development, but their performance has not been entirely satisfactory. How to achieve cross-chain, cross-dApp, accurate intent, and secure path process is a very complex problem. Not to mention that cross-chain is a century-old problem, the latter two, I will use the Web3 primitives here and call them Solvers. The complexity of this process is unimaginable, you can say that the secure ones are not easy to use, and the easy-to-use ones are not secure. So can we simply centralize this interaction process, turn to verifying the total cost of the purchase process and whether the purchased Token is safe and correct, as a transition.
For example, just as we wrote in last year's article on intent. For instance, "I want to order a 30-yuan hamburger takeout" is an "intent", to fulfill this intent the user only needs to enter their name, phone number, delivery address and place the order on the takeout platform, without worrying about how the 30 yuan is earned by the merchant in what form and how the platform distributes the rider, and how the rider delivers it to the home. This process may still not be simple enough, imagine another interaction mode, I tell the AI that I need to order a meal without doing any clicking, the AI agent responds to me that since I ate something a bit greasy yesterday, would I like to have some light porridge today? I just need to respond that I'll have my usual order, and this is the embodiment of autonomy and decision-making ability.
So in Web3, with the centralized exchange as the axis, if the user's intent can be directly satisfied within the exchange, then the purchase process can be completed directly within the exchange. If the user's intent needs to be fulfilled on-chain, then the centralized exchange is still the most affordable and fastest cross-chain bridge (I also believe it is more secure than ordinary multi-signature projects in terms of security), combined with the wallet account, can we directly skip the most cumbersome cross-chain process and instead verify the accuracy of the AI steps? Imagine that the most complex steps in the past interaction process were how to understand each click, and in the future it will be based on our Token hunting habits, through language interaction, letting intent go from point to speech.
Conclusion
Whether from the perspective of technological development or from the perspective of social change, the combination of AI agents and Web3 portends the arrival of a new era, starting from on-chain religion and moving towards the next galaxy. From the early conception of AI's help to small teams in GameFi modeling, to the advanced AI agents realized by Silicon Valley giants today, the bottom-up development model may shift from community building, consensus formation, and time accumulation, to being creativity-driven.
