kaal:claim:4755632-008

The quality and quantity of labeled datasets directly governs the performance of the neural network's learning algorithm during supervised training, so the evolution of AI is correlated with the evolution of micro task work.

The higher the quality and quantity of such labeled datasets the better the AI neural network's learning algorithm during the supervised training process.

Wulf A. Kaal, AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning (2024), Shortcomings in Legacy Micro Task Market, p. 21
https://ssrn.com/abstract=4755632 · source PDF

Wulf A. Kaal, AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning (2024). SSRN: https://ssrn.com/abstract=4755632

• applies to the supervised learning training phase

mechanismsupport: arguededucation-and-practice

• restates kaal:claim:3128900-003 The performance of an AI neural network's learning algorithm during supervised training rises with the quality...

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