Securing $6.30 million in funding, can Inference Labs' decentralized AI inference network Sertn address concerns about "data abuse" and "AI malfeasance"?

AI is becoming an important part of the global digital economy. This is because AI can automatically perform a large number of repetitive tasks by imitating human cognitive functions and learning abilities, participate in data analysis, prediction, and decision-making, and solve complex problems at extremely high speeds with significantly reduced human intervention.

However, if there is a lack of effective guidance, AI may also output "manipulated" results due to algorithmic biases, which may have negative impacts.

At the same time, the privacy breaches, data abuse, and compliance issues in data collection that AI may cause have also raised concerns.

Meanwhile, in the blockchain space, traditional blockchains such as Bitcoin and Ethereum are facing a series of problems due to performance limitations.

To change this situation, developers have proposed a "modular" approach to improve the scalability of blockchain architecture.

The original "monolithic" blockchain structure is separated according to different functions such as execution, consensus, and data availability. In this way, developers can carry out more targeted optimizations for different functions and achieve more flexible combinations. This "modular" construction model has gradually expanded to more fields such as DeFi (such as the modular lending protocol Morpho), privacy protocols (such as the modular privacy layer Inco), and smart accounts (such as the modular smart account Rhinestone).

This actually reflects a technological development trend from "integration" to "professional division of labor."

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