Definition ∞ Trainer Incentives are mechanisms designed to reward participants who contribute to the training and improvement of artificial intelligence or machine learning models, particularly in decentralized settings. These incentives, often distributed in the form of cryptocurrency tokens, encourage accurate data provision, computational effort, and honest participation in collaborative model development. They are crucial for motivating diverse actors to contribute to the collective intelligence of a distributed AI system. These rewards align participant actions with network goals.
Context ∞ The design of effective trainer incentives is a central challenge in building robust and scalable decentralized machine learning platforms. Properly structured incentives are essential for attracting high-quality data and computational resources while mitigating the risk of malicious or low-quality contributions. Ongoing research explores various economic models and reputation systems to optimize these incentives for long-term model health and performance.
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