Key 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 outpaced the rate of hardware improvements, leading to an expanding gap between computing demand and supply.
Key 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 release its edge AI technology at the end of October.
Key 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 a decentralized network 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 entities.
Key Point 4: Cryptocurrency economic incentive mechanisms promote resource sharing and capital expenditure.
Deploying and maintaining edge networks requires significant resources. Cryptocurrency economic models or token incentives can encourage individuals and organizations to contribute computing power, data, and other resources, thereby supporting the construction and operation of the network by providing token rewards.
Key Point 5: DeFi models promote efficient resource allocation.
By introducing concepts such as staking, lending, and liquidity pools from DeFi, edge AI networks can establish a market for computing resources. Participants can provide computing power by staking tokens, lend excess resources, or contribute to a shared pool to receive corresponding rewards. Smart contracts automatically execute these processes, ensuring fair and efficient allocation of resources based on supply and demand, and enabling a dynamic pricing mechanism within the network.
Key Point 6: Decentralization of trust.
In a decentralized network of edge devices, establishing trust without central oversight is a challenge. In cryptocurrency networks, trust is achieved through mathematical means; this computation and mathematics-based trust is key to facilitating trustless interactions, which AI currently does not possess.
Future Outlook
Looking ahead, there are still many innovative opportunities in the field of edge AI. We will see edge AI become an integral 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!
