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In the track where AI and blockchain converge, SAPIEN, a new project established in 2024, focuses on "data labeling gamification + blockchain incentives." Can it differentiate itself in the "essential track" of data labeling?

AI model training relies on high-quality data, and data labeling is a core link, but the traditional model has three major pain points: low efficiency - poor trust - weak participation.

What SAPIEN aims to do is to transform this link using blockchain + gamification:

Break down labeling tasks into "game levels," where users earn token rewards for completing labels; blockchain certification ensures data traceability and transparent rewards, solving trust issues.

The core logic of SAPIEN is "using tokens to incentivize and make data labeling more fun."

Package the tedious labeling tasks into "levels to conquer"; label data gets certified on the blockchain, ensuring quality traceability; token rewards are automatically settled by smart contracts to avoid defaults; labelers earn tokens, and demand-side (AI companies) use tokens to purchase labeling services, creating a "labeling - consumption - reward" cycle.

However, the challenges are also clear: initial ecosystem is hard to build; risk of becoming a "hollow coin"; potential regulatory issues.

The "data labeling gamification" that Sapien aims for is an essential direction of AI + blockchain, but it is currently in the concept verification stage, making implementation difficult.

In the short term, due to lack of actual progress support, price fluctuations are large, making it unsuitable for heavy investment.

In the long term, if the team can successfully establish the model, it could become a dark horse in the track, allowing for small position tracking.

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