AI infrastructure is one of the most critical components or layers in the AI stack. Just like PaaS in cloud computing, it connects the basic AI computing layer with the user-facing application layer.
Therefore, AI systems cannot function without efficient infrastructure. Currently, however, a handful of large tech companies like OpenAI, IBM, Amazon, and Google (and everyone else) have a monopoly on this layer. Providing AI access to millions of users 72% of global companies The outcome depends on these companies.
Decentralized EdgeAI can solve this problem and offset the dominance of centralization, thereby increasing democratization and accessibility. Network 3For example, decentralized physical infrastructure (DePIN), EdgeAI, and AI Infra are combined to enable privacy-preserving, community-led AI running on any device.
Artificial intelligence that runs everywhere
In addition to security and privacy issues, extensive resource usage is also a major drawback of BigAI systems. LLM training fees like GPT-3 are widely available Between US$500,000 and US$4.6 million For example. This raises the bar for smaller entities and further cements the monopoly of big tech companies.
However, with EdgeAI, developers can train and deploy models on smaller devices, from smartphones to IoT devices. First, it reduces reliance on large servers and data centers owned by giants. Second, it expands accessibility.
However, unless the devices running EdgeAI can communicate or share resources, AI systems can only access limited computing and storage. This hinders their growth and effectiveness.
Towards collaborative artificial intelligence
Network3’s innovative decentralized federated learning framework goes beyond existing model development methods such as federated learning and distributed deep learning to facilitate collaborative AI training.
DePIN and EdgeAI meet in this new paradigm, enabling multiple devices, or “nodes,” to pool computing and other resources. Additionally, Anonymous Certificateless Signature Cryptography (CLSC) helps protect private data sharing with strong homomorphic encryption. The framework also uses Reed-Solomon encoding for optimal data accuracy as well as anti-tracking capabilities.
Edge devices in the Network3 ecosystem perform local analytics, enabling low-latency and real-time responsive systems. They also transmit only model updates, reducing bandwidth requirements and allowing the device to operate with limited bandwidth.
Therefore, the decentralized EdgeAI Infra marks a major shift in community-led artificial intelligence, solving the problems of centralized monopoly and resource crunch in one fell swoop.
Additionally, the integration of cryptoassets and blockchain economics unlocks new revenue streams for developers and users. In addition to monetizing excess compute and storage on personal devices, they gain access to “earn as you go” and other revenue generation models.
Last but not least, Network3’s local LL.M. is freely available worldwide without any regional barriers. This reflects the extent to which decentralized infrastructure improves access to artificial intelligence.
Artificial Intelligence is one of the most powerful and groundbreaking technologies since the Internet. Everyone, from the smallest individual to the largest company, must benefit, and no one party can capture huge profits.
The future lies in artificial intelligence systems owned by everyone and not owned by anyone. This is the only way artificial intelligence can benefit humanity as a whole—the ideal purpose of such a powerful technology.
Disclaimer: This article is for informational purposes only. It is not provided or intended to be used as legal, tax, investment, financial or other advice.
