2. Problem Statement

2.1 Challenges in Traditional AI

Current AI systems, like those based on GPT models, are powerful but suffer from centralization. Users do not own the AI; they rent access from providers like OpenAI or Google. This leads to issues such as:

• Data Privacy Concerns: User interactions feed proprietary datasets without compensation.

• Limited Customization: Pre-trained models lack personalization beyond basic prompts.

• Monetization Barriers: Individuals cannot easily profit from AI-generated outputs.

2.2 Limitations of NFTs

NFTs have exploded in popularity, with collections like Bored Ape Yacht Club demonstrating community value. However, many projects focus on art or collectibles, lacking real-world utility. Common problems include:

• Hype-Driven Volatility: Prices crash post-mint due to absent long-term plans.

• Underutilization: NFTs often sit idle in wallets, missing opportunities for active engagement.

• Scalability Issues: High gas fees on Ethereum deter mass adoption.

2.3 The Gap in Web3 AI Integration

While projects like Fetch.ai and Virtuals.io explore AI agents on blockchain, 30 few combine true AI uniqueness with NFT ownership. Users seek AI that can evolve, collaborate, and generate revenue, but existing solutions fall short in decentralization and economic incentives.

Feeda 10k solves these by tokenizing AI agents, ensuring ownership, uniqueness via ANA, and monetization through task execution and knowledge sharing.