Problem & Challenges

As the global AI industry is projected to grow to $407 billion by 2027, the path to achieving Artificial General Intelligence (AGI) faces significant challenges:

Computing Infrastructure Challenges

Current infrastructure is insufficient for advanced AI development, with limited computational power and no unified platform that integrates both Decentralized (DePIN) and Centralized (CePIN) Physical Infrastructure Networks. This leaves users without a solution that balances cost, scalability, privacy, and security, all critical for AGI.

Barriers to AI Model Development

The AI industry is dominated by large corporations like IBM, Microsoft, and Google, creating obstacles for individual developers and startups. These barriers limit access to essential tools, computing power, and platforms, stifling innovation and diversity in AI development.

AI Commercialization Obstacles

Commercializing AI remains difficult due to the lack of AI-as-a-Service (AIaaS) platforms. Without these, developers struggle to deploy and monetize AI models, slowing industry adoption and progress toward AGI.