Detailed Explanation of Viralmind: Decentralized AI Training Protocol Utilizing Large Action Models

Original 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; also seek those with fundamental support. Here is a detailed analysis of Viralmind, including the services it offers, the underlying principles, and a financial and market analysis of the VIRAL token.

Summary

• Viralmind has built Large Action Models (LAMs) that can effectively enhance human-computer interaction in digital environments. LAMs can be seen as digital tools that can perform the same actions as you using computers, websites, and documents.
• Viralmind is constructing 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.
• At the core of Viralmind is the VIRAL token, which can be obtained through DEX or earned while training LAMs on Viralmind.
• Viralmind is on the brink of an AI ecosystem and market expected to reach trillions of dollars. The value of manually trained AI models is estimated at $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 an agent that can operate in a human-like manner in any digital environment. Viralmind's LAM is designed to navigate and operate in digital environments in a human-like way. By utilizing keyboard input, mouse movements, and clicks, these AI agents can perform a wide range of tasks in gaming, productivity, and other creative fields.

To train AI agents, users can train through Trading Gym, which effectively captures on-screen actions as training data. This information is then converted into detailed trajectories, allowing 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, enabling 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 comprehensive reasoning, providing high-quality data for model improvement.

Viralmind's LAM aims to bridge the gap between LLMs (Large Language Models) and direct computer interaction, replacing outdated OCR-based technologies. Viralmind plans to deploy agents on-chain and on desktops, aiming for seamless integration into gaming, enterprise software, and blockchain applications. Viralmind is supported by its native token, VIRAL, which incentivizes users to provide high-quality training data, participate in competitions, and foster the growth of Viralmind's expanding AI ecosystem.

Viralmind reinvests the revenue generated from large models into marketing and development, creating an efficient and self-sustaining economy that rewards contributors and supports the platform's long-term growth.

Products/Services

Viralmind's main product is VM-1, a LAM that reacts 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 distinct tiers:

Open-source small models: These models are compact and efficient, catering to developers looking to enhance existing pipelines by replacing OCR modules. They can serve as plug-and-play extensions for any LLM, enhancing functionality without the need for extensive LAM training.

Base LAM via API: The large VM-1 model provided through API has been trained on millions of data points, suitable for a variety of applications ranging from gaming and work automation to streaming. Its usage is powered by the VIRAL token, with fees reinvested into marketing and growth, ensuring the ecosystem's self-sustainability.

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 VM-1's capabilities 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 alongside users, engaging in cooperative, competitive, or creative gameplay. Users can train their agents with personalized data to master specific games, genres, or strategies.
• 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 lacking resources to train a full LAM can leverage VM-1's smaller models to upgrade 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 interactions.

Community Sentiment

Viralmind has not achieved viral marketing like other projects. It does not have a Discord but 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 fundamental to training AI models. Viralmind is at the core of this training while incentivizing user participation, effectively allowing training to occur on a broader scale while also highly personalizing it for individual users. AI agents and models can typically be trained through centralized methods, but this limits AI's ability to understand users' highly concentrated needs. Furthermore, centralized AI training models absorb the biases of the institutions/organizations/individuals that build them. This is where decentralized AI training models like Viralmind are needed. Viralmind is not the only project building distributed AI training.

FLock.io is also building customizable and highly centralized AI models that can be trained by users. They have a similar community-involved 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 offers the ability for participating users to train AI models. In return, these users receive rewards. However, unlike Viralmind, Sapien provides AI training LLMs aimed at institutions/enterprises.

Prime Intellect is similar in that it brings together researchers, users, and anyone interested in training AI models. It allows anyone to contribute capital, computation, or code to build these models. However, unlike Viralmind, Prime Intellect seems to limit the users who can join in training AI models.

DecentrAI also offers decentralized training. Users can take on responsibilities such as training models and quality checking. DecentrAI is still in the development stage.

Prometheus-X also contributes to decentralized AI training. However, this solution is not based on blockchain technology. They are still in the very early stages of relying on users for decentralized AI training.

Across the existing landscape of small AI training projects, the demand and importance of decentralized AI training models can be understood. Even some larger LLM projects have reached agreements with Reddit to use its content and data to train models. These transactions amount to over $60 million annually. Therefore, the market size for AI training models is immense, with growing demand.

Estimated Potential Market Size for Viralmind:

While the entire AI market is valued at trillions of dollars, Viralmind occupies a relatively small but very important part of it—training. Its LAM will also play a key role in shaping how humans interact with AI in the future, especially in interactions with AI agents. By 2030, the AI agent market is expected to grow to $47 billion.

Even capturing just 1% of that market would mean $470 million. Additionally, the market cap of the decentralized AI ecosystem is only $6 billion, expected to grow rapidly.

Financial Analysis

The core of the Viralmind protocol is the VIRAL token. Here are its two main functions:

• User-facing LAM training incentive mechanism
• Staking VIRAL tokens to participate in competitions

As part of training these models, issued VIRAL tokens can further be used to participate in free or staked competitions. In the former, users receive rewards from the Training Gym pool. These rewards are then distributed to users who complete tasks. In staking competitions, users can earn:

Reward = (Total staked by the user + Staked amount forfeited by losing users) - 5-10% protocol fee, which will be sent to their treasury.

Additionally, users must hold a certain amount of VIRAL tokens in their wallets 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 cap: $14 million

• Total holders: 3,000

• Smart wallet holders: 5

• KOL/VC wallet holders: 22

• Whales: 86 AI market leader AIXBT token details:

• Market cap: $573 million

• Circulating supply: 855,612,732

• Maximum supply: 1,000,000,000

VIRAL / AIXBT market cap ratio ⇒ 2.4%

Considering its limited share in the broader AI ecosystem and the project's early stage, a 2.4% market ratio is "healthy." Furthermore, 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.