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AI's transparency problem: Tech leaders advocate for new insights into training data
GeekWire
Quality Training Data is Key in AI
The success of AI models heavily relies on quality training data. Machine learning depends on curated training data to provide the correct answers for the machine to learn from, ultimately determining whether an outcome is fraud or not. In contrast, generative AI often lacks this curation, using a wide range of data sources, including personal information and fake news, which can lead to less accurate results. The three main inputs to AI are compute power, model, and training data, with the latter being crucial for effective AI outcomes.
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