Viralmind: A decentralized AI training protocol leveraging large action models

avatar
PANews
01-29
This article is machine translated
Show original
Here is the English translation of the text, with the specified terms preserved and not translated:

Author: Emperor Osmo

Compiled by: Felix, PANews

PANews Note: This article only represents the author's views and does not constitute investment advice. DYOR.

Don't just look for the most popular AI crypto projects, but also look for projects with fundamental support. The following is a detailed analysis of Viralmind, including the services it provides, its basic 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 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 for the 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 capabilities 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 improvements.

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 fluid, human-like interactions.

The VM-1 ecosystem will have two different tiers:

Open-source Lightweight Models: These compact and efficient models cater to the needs of developers who wish to enhance their existing pipelines by replacing OCR modules. They can serve as plug-and-play extensions to any LLM, augmenting its capabilities without the need for comprehensive LAM training.

Foundational LAMs via API: The large VM-1 models provided through the API have been trained on hundreds of millions of samples, suitable for a wide range of applications from gaming and work automation to streaming. Their usage, supported by VIRAL tokens, will be reinvested into 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 capabilities 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 alongside 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 lacking 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 interactions.

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-driven 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. However, unlike Viralmind, Sapien offers LLM training for institutions/enterprises.

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 massive and the demand is growing.

Detailed Analysis of Viralmind: Decentralized AI Training Protocol Leveraging Large Action Models

Estimated Potential Market Size for Viralmind:

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

Explanation of Viralmind: Decentralized AI Training Protocol Leveraging Large-Scale Action Models

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.

Explanation of Viralmind: Decentralized AI Training Protocol Leveraging Large-Scale Action Models

VIRAL token details:

  • Circulating supply: 965,888,531
  • Maximum supply: 1,000,000,000
  • Market cap: $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 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, 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.

Related reading: The AI Agent Track Rebounds Strongly, a Look at 10 Emerging AI Agent Projects Attracting Attention

Source
Disclaimer: The content above is only the author's opinion which does not represent any position of Followin, and is not intended as, and shall not be understood or construed as, investment advice from Followin.
Like
1
Add to Favorites
Comments