How does Mirror World discover Alpha with the help of AI Asset Agents (AAA)?

Life feeds on negative entropy, and AI thrives on entropy reduction.

The Birth of World Store: Using AI Asset Agents (AAA) to Combat the Entropy Increase in Crypto

The current development of blockchain is rapidly heading towards a phase of entropy increase. The emergence of various Layer1/Layer2 ecosystems, accompanied by the growth of different categories of assets crossing various ecosystems, as well as the birth of various smart contracts and protocols, has brought immense complexity to the entire blockchain system. Moreover, during this process, these foundational complexities have further raised the high operational threshold for end users: cross-chain asset settlement and purchases, finding and discovering quality assets distributed across different ecosystems, fiat to crypto deposits, and so on. What we can see is that the essence of all these problems points to the keywords "disorder, chaos, and high complexity."

Generated By DALL·E

This provides us with a very interesting perspective, viewing the entire blockchain system from the standpoint of thermodynamics and system entropy increase. Of course, this is not strictly accurate in scientific terms, but it undeniably adds a perspective to reinterpret the current development of blockchain.

We all know that in an isolated system/closed system, its entropy will continuously increase, presenting a state that transitions from order to disorder. As mentioned above, we are observing such a state occurring and being experienced within the blockchain system. Currently, there are no consumer-grade applications, and no more external system users are entering; such a system will become more isolated, ultimately leading to the conclusion we all know, "heat death."

Therefore, to introduce more "external system" users to combat entropy increase, existing participants within the system have proposed and developed various tools and services to reduce the complexity of user operations, thereby lowering the entry threshold into this industry. However, it must be acknowledged that the emergence of these standalone tools has further led to the isolation of various ecosystems, bringing users the cost of filtering massive amounts of information and the high cost of switching between products.

Due to the high volume of information and overall complexity within an emerging ecosystem, existing tools have not managed to reduce the signal-to-noise ratio. Thus, even if users target a specific ecosystem, they often experience "missing out" on capturing the most direct value. For example, users in numerous EVM ecosystems or non-EVM ecosystems may still miss out on assets that align with their interests or investment preferences but have not yet been noticed. Alternatively, users may spend too much time selecting the optimal route for executing a key transaction, causing them to miss some of the best trading times.

The aforementioned problems actually have increasingly simple solutions, as the development and maturation of AI Agents serve primarily to help users process dimensionality reduction amid massive information, find optimal solutions, and assist users in capturing the core value. The existence of AI itself brings rational order to chaotic systems, providing entropy reduction for the system.

Mirror World has deeply recognized the necessity of implementing this path by creating AI Asset Agents, which discover quality assets centered around users' core goals and interests, recommend optimal routing based on users' on-chain behavior data, and reduce users' purchasing and trading costs. AAA provides personalized optimal recommendations from a vast array of asset categories while helping users settle from any currency to any asset across any ecosystem.

The above conclusions and visions are summaries we have derived from profound reflections during our actual participation in "asset distribution" and "asset settlement" over the past two years, which have also given rise to the new product, World Store, that Mirror World will launch on December 18.

World Store Alpha Version

1/ The Logical Brain of World Store: AI Asset Agents (AAA)

As mentioned above, the birth of World Store is a direct response to the aforementioned problems. World Store will leverage the capabilities of AI Asset Agents to effectively address the issues of information overload and transaction complexity faced by users, providing a more intuitive and efficient asset issuance and trading experience.

In World Store, users can find various assets recommended based on their interests and preferences, and they can purchase and settle these assets using their familiar fiat or crypto payment methods.

Assets recommended based on users' on-chain assets and interactions

AI Asset Agents, as the logical brain of World Store, will utilize natural language processing (NLP) and machine learning to understand users' needs and preferences, recommending relevant assets and digital content based on their on-chain interaction records and asset holdings. Furthermore, by integrating LLMs, we aim to further build and enrich the recommendation system to achieve specific effects that traditional recommendation systems cannot quickly realize.

TALLRec Framework

In comparison with traditional recommendation algorithms, LLMs contain rich knowledge mined from large-scale web corpora, enabling them to supplement the user behavior data that traditional recommendation systems rely on. Traditional algorithms primarily depend on user behavior data for recommendations, while LLMs can combine world knowledge and user interaction data for more comprehensive recommendations. Additionally, LLMs can adapt to new domains with zero or only a few examples, allowing them to recommend based on limited task-specific data (such as wallet transaction data), whereas traditional algorithms typically require a large amount of domain-specific data for recommendations.

Moreover, LLMs can be used for various recommendation tasks, such as sequential recommendations, rating predictions, and explanation generation, thereby achieving a unified recommendation framework, while traditional algorithms often require different models for different tasks. Furthermore, LLMs possess interactivity and feedback mechanisms, enhancing user experience and improving model interpretability. AI Asset Agents can gain deeper insights into users' needs through conversational interactions, even continuously adjusting recommendation strategies during the interaction. Users can make specific requests or provide feedback through dialogue, and AI Asset Agents will optimize recommendation results based on this information.

User Profile Generated with AI Asset Agents (AAA)

AI Asset Agents can continuously learn from user interactions through machine learning, thereby improving their recommendation algorithms. This means that over time, the recommendation system will become increasingly attuned to users' personal preferences.

2/ The Execution Engine of World Store: AI Asset Settlement Center

In terms of executing asset transactions and settlements, World Store provides users with a unified payment and settlement center by integrating various deposit payment service providers, cross-chain service providers, and DEXs: World Store. All operations related to payment and asset settlement can be completed in one place within World Store, and during the process, AI Asset Agents will recommend the optimal execution route based on users' choices, thereby reducing the complexity of user interactions and the execution costs during transactions.

Currently, World Store supports over 150 countries, more than 50 different local payment methods, and over 10 mainstream blockchain networks for fiat deposits. It has also integrated 23 blockchains, 15 bridges, and 28 DEXs to support users in exchanging any token across any network.

Global Asset Checkout

Let us envision a scenario: game NFTs are deployed on Polygon, and as a player, although you log into the game through a wallet in the Polygon network environment, the tokens are spread across other blockchain networks, leading to an inability to directly purchase game assets within the application due to the complexity of cross-chain operations. However, it is foreseeable that after integrating World Store, users or players can easily purchase and settle game items using their assets from any network.

Additionally, as users interact with World Store, their interaction data will be further fed into AI Asset Agents to improve the quality of algorithm recommendations. As a reward for users' asset interaction behaviors and algorithm training, we have introduced a Points System to incentivize users.

All of the above functionalities can be experienced directly in the asset purchasing process within World Store. Mirror World will also provide open APIs and widget integration services to all application developers, aiming to help more application projects solve the complexities of asset settlement and commercialization challenges.

Get Supported List of Fiat

3/ The Reward Center of World Store: Points System

As mentioned above, to further support users' trading behaviors and provide data training for the algorithm, we will offer corresponding incentive measures to all users participating in product interactions to encourage their asset interaction behaviors, thus we have launched the Points System.

Through Raffle Tickets, users can redeem for a Lucky Draw when World Store launches on December 18.

In the design of the Points System, users can potentially earn rewards simply by trading assets through World Store. Similar to a credit card points mechanism, every time users make a corresponding asset purchase or exchange, they can earn corresponding points rewards.

These points will serve as an important basis for Mirror World to assess user activity, participation, and contribution during subsequent operations, and will directly distribute corresponding rights and rewards during future product launches, tokenomics design, and community airdrops.

In Conclusion

The combination of World Store and AI Asset Agents aims to bring a new interactive experience to more users, lower the interaction threshold for blockchain assets, enhance asset usage and the discovery of quality assets, and ultimately bring entropy reduction to the entire blockchain system.

With the development and maturation of LLMs and blockchain, we are inevitably entering this train of technological acceleration, and this rapidly accelerating train will lead everyone to discover Alpha in the upcoming crypto bull market.