Problems to Solve

The current AI industry faces several critical challenges that NeuralNet DAO aims to address through decentralization:

1️⃣ AI Resource Monopolization

• AI training and inference resources are dominated by tech giants, making it difficult for independent developers to access fair computing power.

• NeuralNet DAO introduces a decentralized computing network powered by global contributors, reducing AI computation barriers.

2️⃣ Data Control & Privacy Issues

• Many AI models rely on private datasets, leading to data monopolization and lack of transparency.

• NeuralNet DAO facilitates a decentralized data marketplace that ensures secure data sharing while protecting user privacy.

3️⃣ Centralized Decision-Making in AI Development

• AI research directions are often determined by large corporations, leaving independent developers and users with little influence.

• NeuralNet DAO adopts DAO governance, allowing the community to vote on funding AI research projects.

4️⃣ Lack of AI Transparency & Audibility

• Many AI models operate as black-box systems with little transparency.

• NeuralNet DAO utilizes blockchain to ensure AI training processes are traceable, increasing trust in AI models.

5️⃣ Insufficient Incentives for Developers & Contributors

• AI developers, data providers, and computing resource contributors often receive inadequate compensation.

• NeuralNet DAO introduces an NND token economy, rewarding all participants who contribute to the AI ecosystem fairly.

Through blockchain and DAO mechanisms, NeuralNet DAO aims to dismantle centralized barriers in the AI industry, driving fair and open AI advancements that benefit everyone. 🌎