Title: "Viralmind and $VIRAL: Pioneering Decentralized AI Training with Large Action Models"
Author: Emperor Osmo
Compiled by: Felix, PANews
Don't just look for the most popular AI crypto projects, but also look for those with fundamental support. The following is a detailed analysis of Viralmind, including the services it provides, the basic principles, and the financial and market analysis of the VIRAL token.
Abstract
- Viralmind has built Large Action Models (LAMs) that can effectively enhance human-computer interaction in digital environments. LAMs can be seen as a kind of digital tool that can actually use computers, websites, and documents to perform the same operations as you.
- Viralmind is building a decentralized AI training ecosystem that allows training of its AI agents. This can eliminate the inherent biases of centralized AI training models and provide these agents with highly native and highly concentrated datasets for training.
- The core of Viralmind is the VIRAL token, which can be obtained through DEX and by training LAMs on Viralmind.
- Viralmind is on the edge of an AI ecosystem and market that is expected to reach a trillion dollars. The value of AI models trained by humans is over $60 million per year or more.
Overview
Viralmind is an open-source, decentralized collective intelligence platform aimed at truly transforming AI agents into human assistants. In short, it is a kind of agent that can operate in any digital environment in a human-like way. Viralmind's LAMs are designed to navigate and operate digital environments in a human-like manner. By leveraging keyboard input, mouse movement, and clicks, these AI agents can perform a wide range of tasks in gaming, productivity, and other creative domains.
To train the AI agents, users can train through the Trading Gym, which can effectively capture screen actions as training data. This information is then converted into detailed trajectories, allowing the AI agents to learn and improve over time. Viralmind also introduces a data marketplace where users can trade these datasets to further enhance the overall learning capability of the system. A key innovation of Viralmind is the one-click fine-tuning feature, which allows users to customize models like GPT-4o using small datasets. This approach simplifies AI training, allowing a large number of users (even those without deep technical expertise) to benefit. The system generates structured .jsonl files that capture human behavior and synthetic reasoning, providing high-quality data for model improvement.
Viralmind's LAMs are designed to bridge the gap between LLMs (large language models) and direct computer interaction, replacing outdated OCR-based approaches. Viralmind plans to deploy agents on-chain and on desktops, aiming to seamlessly integrate into games, enterprise software, and blockchain applications. Viralmind is supported by its native VIRAL token, which incentivizes users to provide high-quality training data, participate in competitions, and drive the growth of Viralmind's expanding AI ecosystem.
Viralmind reinvests the revenue generated by its large models into marketing and development, creating an efficient and self-sustaining economy that rewards contributors and supports the long-term growth of the platform.
Products/Services
Viralmind's main product is VM-1, which is a LAM that can respond to human behavior in digital environments. As an advanced LAM, VM-1 enables AI agents to play games, complete tasks, and navigate complex interfaces through smooth, human-like interactions.
The VM-1 ecosystem will have two different tiers:
Open-source small models: These compact and efficient models can meet the needs of developers who want to enhance their existing pipelines by replacing OCR modules. They can serve as plug-and-play extensions to any LLM, enhancing its functionality without the need for comprehensive LAM training.
Large VM-1 models through API: The large VM-1 models provided through the API have been trained on hundreds of millions of samples and are suitable for a wide range of applications, from gaming and work automation to streaming. Their use is supported by VIRAL tokens, with fees reinvested in marketing and growth to ensure the self-sustainability of the ecosystem.
Viralmind has also established strategic partnerships with game studios, enterprise software providers, and crypto platforms to expand the reach of VM-1. These collaborations will integrate the functionality of VM-1 into a broader AI ecosystem, enhancing the adoption and potential of the agent framework.
Why choose VM-1?
- For gamers: VM-1 agents can seamlessly play games with users, engaging in cooperative, competitive, or creative gameplay. Users can train their agents to master specific games, genres, or strategies using personalized data.
- For professionals: VM-1 can replace repetitive manual tasks, such as form filling and document processing, streamlining workflows in real-world scenarios.
- For developers: Developers who lack the resources to train a full LAM can leverage the smaller VM-1 models to upgrade their existing tools and frameworks. Additionally, Viralmind allows users to train their own AI agents, bridging the gap between text-based LLMs and real-world computer interaction.
Community Sentiment
Viralmind has not achieved viral marketing like other projects. Viralmind does not have a Discord, but it has a Telegram channel with over 1.1K members. The existing community has a deep understanding of Viralmind's products. Viralmind is currently not listed on GoatIndex, but is listed on Cookie.fun.
Market Analysis
Having large datasets is the foundation for training AI models. Viralmind is at the core of this training, while incentivizing user participation, effectively allowing training to be done on a broader scale, while also highly nativizing it to individual users. AI agents and models can typically be trained through a centralized approach, but this limits the ability of AI to understand the highly concentrated needs of users. Additionally, centralized AI training models also absorb the biases of the institutions/organizations/individuals that built them. This is where the need for a decentralized AI training model like Viralmind comes in. Viralmind is not the only project building distributed AI training.
FLock.io is also building customizable and highly concentrated AI models that can be trained by users. They have a similar, community-participatory AI training model where users can help train AI models on Flock. These models can then be commissioned by individuals or organizations. In this case, the FLOCK token has similar utility to the VIRAL token.
Sapien AI also provides the ability to train AI models based on the participation of users. In return, these users are able to receive rewards. But unlike Viralmind, Sapien offers institution/enterprise-focused AI training LLMs.
Prime Intellect is similar in bringing together researchers, users, and anyone interested in training AI models. It allows anyone to contribute capital, compute, or code to build these models. However, unlike Viralmind, Prime Intellect seems to restrict who can join the training of AI models.
DecentrAI also provides decentralized training. Users can take on responsibilities like model training, quality checking, etc. DecentrAI is still in the development stage.
Prometheus-X also contributes to decentralized AI training. But this solution is not based on blockchain technology. They are also in a very early stage of relying on users for decentralized AI training.
Looking at the existing landscape of small-scale AI training, one can understand the demand and importance of decentralized AI training models. Even some larger-scale LLM projects have reached agreements with Reddit to use their content and data to train models. These transactions are worth over $60 million per year. Therefore, the market size for AI training models is huge and the demand is growing.
Estimated potential market size for Viralmind:
While the entire AI market is worth trillions of dollars, Viralmind only occupies a relatively small but very important part of it - training. Its LAMs will also play a key role in shaping the way humans interact with AI agents in the future, especially with AI agent interactions. By 2030, the AI agent market is expected to grow to $47 billion.
Even if it only has a 1% market share, it means $470 million. In addition, the market capitalization of the decentralized AI ecosystem is only $6 billion, and it is expected to grow rapidly.
Financial Analysis
The core of the Viralmind protocol is the VIRAL token. Here are its two main functions:
- User-oriented LAM training incentive mechanism
- VIRAL token staking to participate in competitions
As part of training these models, the issued VIRAL tokens can be further used to participate in free or staking competitions. In the former, users receive rewards from the Training Gym library. Then, these rewards will be distributed to users who complete the tasks. In staking competitions, users can receive:
Reward = (Total staking of the user + Forfeited staking of the losing user) - 5-10% protocol fee, which will be sent to their treasury.
Additionally, users must hold a certain amount of VIRAL tokens in their wallet to participate in free competitions. This adds another layer of utility to the VIRAL token.
VIRAL token details:
- Circulating supply: 965,888,531
- Maximum supply: 1,000,000,000
- Market capitalization: $14 million
- Total number of holders: 3,000
- Smart wallet holders: 5
- KOL/VC wallet holders: 22
- Whales: 86
AI market leader AIXBT token details:
- Market capitalization: $573 million
- Circulating supply: 855,612,732
- Maximum supply: 1,000,000,000
VIRAL / AIXBT market capitalization ratio ⇒ 2.4%
Considering its limited share in the broader AI ecosystem, a 2.4% market share ratio is "healthy" given the project is just starting. Additionally, the selling pressure from non-circulating tokens accounts for only 3-4% of the total selling pressure. This highlights the strong fundamentals of the VIRAL token, further enhancing its performance in the coming weeks/months.
