Point 1: The rapid growth of AI has already surpassed Moore's Law
Moore's Law states that the number of transistors on a microchip doubles approximately every two years. However, the growth rate of AI models has exceeded the pace of hardware improvements, leading to an increasing gap between computational demand and supply.
Point 2: Major industry giants are increasing their investments in edge AI and adopting different strategies
Major industry giants are heavily investing in edge AI, recognizing its potential to revolutionize fields such as healthcare, autonomous driving, robotics, and virtual assistants by providing instant, personalized, and reliable AI experiences. For example, Meta recently released models optimized for edge devices, and Apple Intelligence will also launch its edge AI technology at the end of October.
Point 3: Blockchain provides a secure, decentralized trust mechanism for edge AI networks
Blockchain ensures data integrity and tamper resistance through its immutable ledger, which is particularly critical in decentralized networks composed of edge devices. By recording transactions and data exchanges on the blockchain, edge devices can securely authenticate and authorize operations without relying on centralized authorities.
Point 4: Crypto economic incentive mechanisms promote resource sharing and capital expenditure
Deploying and maintaining edge networks requires significant resources. Crypto economic models or token incentives can encourage individuals and organizations to contribute computing power, data, and other resources by providing token rewards, thus supporting the construction and operation of the network.
Point 5: DeFi models promote efficient allocation of resources
By introducing concepts such as staking, lending, and liquidity pools in DeFi, edge AI networks can establish a marketplace for computing resources. Participants can provide computing power by staking tokens, lend excess resources, or contribute to shared pools in exchange for corresponding rewards. Smart contracts automatically execute these processes, ensuring that resources are allocated fairly and efficiently based on supply and demand, and implementing a dynamic pricing mechanism within the network.
Point 6: Decentralization of Trust
In a decentralized network of edge devices, establishing trust without central oversight is a challenge. In crypto networks, trust is established through mathematical means; this mathematically-based trust is key to facilitating trustless interactions, which is currently a characteristic that AI does not possess.
Future Outlook
Looking to the future, there are still plenty of innovative opportunities in the edge AI field. We will see edge AI become an indispensable part of our lives in various application scenarios, such as hyper-personalized learning assistants, digital twins, autonomous vehicles, collective intelligence networks, and emotional AI companions. We are excited about the future!
