Don't just look for the most popular AI crypto projects; seek those with strong fundamentals. Below is a detailed analysis of Viralmind, including its services, basic principles, and financial and market analysis of the VIRAL token.

Summary

Viralmind has built Large Action Models (LAMs) that can significantly enhance human-computer interactions in digital environments. LAMs can be seen as digital tools that can perform the same actions as you would using computers, websites, and documents. Viralmind is constructing a decentralized AI training ecosystem that allows for the training of 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 DEXs or earned by training LAMs on Viralmind. Viralmind is on the cusp of the AI ecosystem and market, which is expected to reach trillions of dollars. The value of manually trained AI models is over $60 million per year.

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 any digital environment in a human-like manner. Viralmind's LAMs are designed to navigate and manipulate digital environments in a human-like way. By leveraging keyboard inputs, 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 use the 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 system's overall learning capabilities. 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, making it accessible to a large number of users, even those without deep technical expertise. The system generates structured .jsonl files that capture human behavior and synthetic reasoning, providing high-quality data for model improvement.

Viralmind's LAMs aim to bridge the gap between Large Language Models (LLMs) and direct computer interactions, replacing outdated OCR-based technologies.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. Supported by its native VIRAL token, Viralmind incentivizes users to provide high-quality training data, participate in competitions, and promote the growth of its expanding AI ecosystem. Viralmind reinvests the revenue generated by 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 reflects human behavior in digital environments. As an advanced LAM, VM-1 enables AI agents to play games, complete tasks, and navigate complex interfaces with smooth, human-like interactions.

The VM-1 ecosystem will have two distinct tiers:

• Open-Source Small Models: These compact and efficient models meet the needs of developers who want to enhance existing pipelines by replacing OCR modules. They serve as plug-and-play extensions for any LLM, enhancing their capabilities without requiring comprehensive LAM training.

• Foundational LAM via API: The large VM-1 model, available via API, is trained on millions of data points and is suitable for a wide range of applications, from gaming and work automation to streaming. Its usage is supported by the VIRAL token, with fees reinvested into marketing and growth to ensure a self-sustaining 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 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 practical scenarios.

• For Developers: Developers lacking resources to train full LAMs can use 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

Possessing large datasets is fundamental to training AI models. Viralmind is at the core of this training, incentivizing user participation, effectively allowing training to occur on a broader scale while highly localizing it to individual users. AI agents and models are typically trained through centralized methods, which limit AI's ability to understand highly concentrated user needs. Moreover, centralized AI training models absorb the biases of the institutions/organizations/individuals that build them. This is where decentralized AI training models like Viralmind come into play. Viralmind is not the only project building distributed AI training.

• Flock.io is also building custom and highly concentrated AI models that can be trained by users. They have a similar community-engaged 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 to train AI models based on participating users. In return, these users receive rewards. However, unlike Viralmind, Sapien provides AI training LLMs aimed at institutions/enterprises.

• Prime Intellect is similar to bringing 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 the AI model training.

• 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 a very early stage of relying on users for decentralized AI training.

Looking at the existing small AI training landscape, it is clear that there is a demand and importance for decentralized AI training models. Even some larger LLM projects have agreements with Reddit to use its content and data to train models. These deals are worth over $60 million per year. Therefore, the market size for AI training models is enormous and growing.

Estimated Potential Market Size of Viralmind

While the entire AI market is worth trillions of dollars, Viralmind occupies a relatively small but crucial part of it—training. Its LAMs will also play a key role in shaping the future of human-AI interactions, especially with AI agents. By 2030, the AI agent market is expected to grow to $47 billion.

Even capturing just 1% of this market means $470 million. Moreover, the market cap of the decentralized AI ecosystem is only $6 billion and is expected to grow rapidly.

Financial Analysis

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

• Incentive Mechanism for LAM Training for Users: Users are incentivized to train LAMs.

• VIRAL Token Staking to Participate in Competitions: VIRAL tokens issued as part of training these models can further be used to participate in free or staked competitions. In the former, users earn rewards from the Training Gym pool, which are then distributed to users who complete tasks. In staked competitions, users can earn:

Rewards = (Total stake deposited by the user + Stake confiscated from losing users) - 5-10% protocol fee, which is 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.

Don't just look for the most popular AI crypto projects; seek those with strong fundamentals. Below is a detailed analysis of Viralmind, including its services, basic principles, and financial and market analysis of the VIRAL token.

Summary

Viralmind has built Large Action Models (LAMs) that can significantly enhance human-computer interactions in digital environments. LAMs can be seen as digital tools that can perform the same actions as you would using computers, websites, and documents. Viralmind is constructing a decentralized AI training ecosystem that allows for the training of 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 DEXs or earned by training LAMs on Viralmind. Viralmind is on the cusp of the AI ecosystem and market, which is expected to reach trillions of dollars. The value of manually trained AI models is over $60 million per year.

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 any digital environment in a human-like manner. Viralmind's LAMs are designed to navigate and manipulate digital environments in a human-like way. By leveraging keyboard inputs, 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 use the 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 system's overall learning capabilities. 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, making it accessible to a large number of users, even those without deep technical expertise. The system generates structured .jsonl files that capture human behavior and synthetic reasoning, providing high-quality data for model improvement.

Viralmind's LAMs aim to bridge the gap between Large Language Models (LLMs) and direct computer interactions, 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. Supported by its native VIRAL token, Viralmind incentivizes users to provide high-quality training data, participate in competitions, and promote the growth of its expanding AI ecosystem. Viralmind reinvests the revenue generated by 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 reflects human behavior in digital environments. As an advanced LAM, VM-1 enables AI agents to play games, complete tasks, and navigate complex interfaces with smooth, human-like interactions.

The VM-1 ecosystem will have two distinct tiers:

• Open-Source Small Models: These compact and efficient models meet the needs of developers who want to enhance existing pipelines by replacing OCR modules. They serve as plug-and-play extensions for any LLM, enhancing their capabilities without requiring comprehensive LAM training.

• Foundational LAM via API: The large VM-1 model, available via API, is trained on millions of data points and is suitable for a wide range of applications, from gaming and work automation to streaming. Its usage is supported by the VIRAL token, with fees reinvested into marketing and growth to ensure a self-sustaining 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 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 practical scenarios.

• For Developers: Developers lacking resources to train full LAMs can use 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

Possessing large datasets is fundamental to training AI models. Viralmind is at the core of this training, incentivizing user participation, effectively allowing training to occur on a broader scale while highly localizing it to individual users. AI agents and models are typically trained through centralized methods, which limit AI's ability to understand highly concentrated user needs. Moreover, centralized AI training models absorb the biases of the institutions/organizations/individuals that build them. This is where decentralized AI training models like Viralmind come into play. Viralmind is not the only project building distributed AI training.

• Flock.io is also building custom and highly concentrated AI models that can be trained by users. They have a similar community-engaged 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 to train AI models based on participating users. In return, these users receive rewards. However, unlike Viralmind, Sapien provides AI training LLMs aimed at institutions/enterprises.

• Prime Intellect is similar to bringing 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 the AI model training.

• 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 a very early stage of relying on users for decentralized AI training.

Looking at the existing small AI training landscape, it is clear that there is a demand and importance for decentralized AI training models. Even some larger LLM projects have agreements with Reddit to use its content and data to train models. These deals are worth over $60 million per year. Therefore, the market size for AI training models is enormous and growing.

Estimated Potential Market Size of Viralmind

While the entire AI market is worth trillions of dollars, Viralmind occupies a relatively small but crucial part of it—training. Its LAMs will also play a key role in shaping the future of human-AI interactions, especially with AI agents. By 2030, the AI agent market is expected to grow to $47 billion.

Even capturing just 1% of this market means $470 million. Moreover, the market cap of the decentralized AI ecosystem is only $6 billion and is expected to grow rapidly.

Financial Analysis

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

• Incentive Mechanism for LAM Training for Users: Users are incentivized to train LAMs.

• VIRAL Token Staking to Participate in Competitions: VIRAL tokens issued as part of training these models can further be used to participate in free or staked competitions. In the former, users earn rewards from the Training Gym pool, which are then distributed to users who complete tasks. In staked competitions, users can earn:

Rewards = (Total stake deposited by the user + Stake confiscated from losing users) - 5-10% protocol fee, which is 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.