Yeliz Akmaca 
Gata is an infrastructure project designed for decentralized AI inference and training. Its goal is to reduce dependency on traditional, centralized data centers and shift AI towards a global, collaborative paradigm. Gata develops technologies that efficiently aggregate distributed GPUs, enabling large-scale AI models to be trained and executed in a decentralized way.
The core mission of Gata is to make AI more accessible, transparent, and fair for everyone. It aims to achieve this by building a decentralized AI data layer that is created, validated, and owned by the community.
Project Idea
Gata seeks to solve a critical challenge in AI development: most modern AI models rely on centralized platforms that use opaque and potentially biased datasets. This creates issues of data monopolization, security risks, and misaligned AI behavior with human values.
Gata’s core project idea challenges this paradigm by introducing the DataAgent approach. Instead of relying on human labeling, Gata uses AI-driven automated data generation, combined with users contributing idle computational resources to crowdsource high-quality AI datasets.
This model offers key benefits:
- Breaking data monopolies: Prevents a few companies from controlling valuable datasets.
- User control: Gives individuals more visibility and control over their personal data.
- Higher data quality: Reduces AI errors caused by biased or low-quality data.
- Economic incentives: Rewards users who contribute to AI development.
What is Gata Token?
The Gata token is the native cryptocurrency of the ecosystem. It powers data production processes, network governance, and economic transactions within the platform. Its features and incentive mechanisms form the foundation of the project’s economy.
How Does the Project Work?
Gata is developing two main products to build a decentralized AI data layer: All-in-One Chat and GPT-to-Earn.
DataAgent and DVA (Data Validation Agent):
- DataAgent: AI tools that aggregate computational resources and automate data generation.
- DVA: The first DataAgent created by Gata. It evaluates the quality of image-caption pairs online, assigning a score between -1 and 1. These scores identify high-quality data points for advanced AI model training, reducing the need for slow and costly human labeling.
All-in-One Chat:
- A single interface combining models like ChatGPT, Claude, and Gemini.
- When users ask a question, they receive three answers from different models. By selecting the preferred answer, users provide valuable human preference data.
- This interaction naturally generates high-value data without extra effort, rewarding users with Gata points that can be redeemed for premium AI subscriptions.
GPT-to-Earn:
- A Chrome extension that allows ChatGPT users to voluntarily share conversation history in exchange for Gata points.
- These datasets, containing real-world usage and human intent, are highly valuable for AI companies.
- Unlike traditional setups where users receive no benefit, GPT-to-Earn provides fair rewards while helping AI firms access quality real-world data to narrow the gap with OpenAI.
Team, Investors, and Partnerships
Founding team:
- Xudong Shen – Co-Founder
- Leo Lee – Co-Founder
- Claire – CPO (Chief Product Officer)
Investors & Partners: Gata is backed by leading AI and Web3 investors, including:
- YZi Labs
- Gate Ventures
- IDG Blockchain
- Whirlpool
- Multicoin Capital
- MH Ventures
- Anti Capital
- Morphic Capital
- V3V Ventures
- Dewhales Capital
- 071 Laboratories
- Echo
Notably, the involvement of Multicoin Capital, a highly reputable Web3 investor, highlights the project’s strong strategic backing.
Roadmap & Governance
Roadmap:
- Current stage: Aggregating distributed computing through DataAgents and launching the first products (All-in-One Chat, GPT-to-Earn).
- Future goals: Multi-node coordination, full tokenization integration, and community-driven governance. The long-term vision is to build a permissionless ecosystem that powers safe AI systems with clean, user-supported data.
Governance:
- Gata aims to establish a community-governed ecosystem where token holders will eventually participate in decision-making.
- While governance details are not yet disclosed, decentralization will increase as the project matures.
Timeline:
- H2 2025: Launch of the decentralized inference network with optimized node performance and prototypes for large models.
- Early 2026: Launch of the decentralized AI training network, scaling globally, and introducing more decentralized governance.
Token Use Cases & Distribution
Use Cases:
- Rewards: Users earn tokens for contributing data (preference data, chat histories) or sharing computational resources.
- Payments: Used as a payment method for platform services (e.g., premium AI subscriptions).
- Governance: Future voting rights on key project decisions.
- Staking: Locking tokens for securing the network and earning additional rewards.
Token Distribution
- Airdrop: 6%
- Ecosystem Development: 39.7%
- Team & Advisors: 21%
- Exchange & Marketing: 13.5%
- Foundation: 10.01%
- Investors: 9.79%
Ecosystem & Features
Gata’s ecosystem connects users, AI developers, data providers, and node operators in a collaborative structure.
Key Features:
- Decentralized AI Infrastructure: Reduces reliance on centralized data centers.
- Crowdsourced Data Generation: Builds community-driven, high-quality datasets.
- Incentive Mechanisms: Encourages user contributions with All-in-One Chat and GPT-to-Earn.
- Transparency & Trust: Returns data ownership to users.
- Data Quality: Uses DVA and similar tools for automated data validation.
By merging decentralized finance (DeFi), Web3, and AI technologies, Gata positions itself as an ambitious project building the AI infrastructure of the future.
Official Links
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