Network3’s decentralized EdgeAI framework solves legacy AI Infra risks

AI Infra is one of the most critical components or layers of the AI stack. Like PaaS in Cloud Computing, it connects the foundational AI Computing layer with the user-facing App layer. Thus AI systems cannot function without efficient Infra. Yet currently, a few Big Tech firms like OpenAI, IBM, Amazon, and Google have a monopoly over this layer (alongside every other). AI access for millions of users and 72% of global enterprises depends on these firms as a result. Decentralized EdgeAI can fix this, offsetting centralized dominance to improve democratization and accessibility. Network3 , for example, combines Decentralized Physical Infrastructure (DePIN), EdgeAI, and AI Infra to enable privacy-preserving, community-led AI that runs on any device. AI that runs anywhere Besides security and privacy concerns, extensive resource usage is a key downside of BigAI systems. Training LLMs like GPT-3 costs anywhere between $500K to $4.6 million for example. This raises the barrier to high for smaller entities, further consolidating Big Tech’s monopoly. With EdgeAI, however, devs can train and deploy models on smaller devices—anything from smartphones to IoT appliances. One, it reduces dependence on big servers and data centers owned by giants. And two, it broadens accessibility. However, unless devices running EdgeAI can communicate or share resources, AI systems only have access to limited computation and storage. This impedes their growth and efficiency. Towards collaborative AI Moving beyond existing model development methods like Federated Learning, Distributed Deep Learning, etc., Network3’s innovative Decentralized Federated Learning framework fosters collaborative AI training. DePIN and EdgeAI meet in this new paradigm, enabling multiple devices or ‘nodes’ to pool compute and other resources. Moreover, Anonymous Certificateless Signcryption (CLSC) facilitates private data sharing secured with strong homomorphic encryption. The framework also uses Reed-Solomon coding for optimal data accuracy coupled with anti-tracking features. Edge devices in the Network3 ecosystem perform local analysis, resulting in low latency and real-time response systems. They also transmit only model updates, reducing bandwidth requirements and making devices functional with limited bandwidth. Decentralized EdgeAI Infra thus marks a major shift in community-led AI, tackling centralized monopoly and resource crunch in one fell swoop. Moreover, the integration of crypto assets and blockchain economics unlocks novel revenue streams for devs and users. Besides monetizing excess compute and storage on personal devices, they get ‘Prompt-to-Earn’ and other income-generation models. Last but not least, Network3’s Local LLM is free to use across the globe, without any regional barriers. This reflects the degree to which decentralized Infra improves AI access. AI is one of the most powerful and groundbreaking technologies since the Internet. Everyone, from the smallest individual to the biggest corporation must reap its benefits, without any single party extracting outsized gains. The future lies in AI systems that everyone owns, without being owned by anyone. That’s the only way AI can benefit humanity as a whole—the ideal purpose of a technology this powerful. Disclaimer: This article is provided for informational purposes only. It is not offered or intended to be used as legal, tax, investment, financial, or other advice.