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Daphne Koller on drug discovery and AI

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Enhancing Data Rather Than Hallucinating

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Concerns exist regarding the use of synthetic data for training AI models, as generating data without real-world basis risks reinforcing existing biases. A more effective approach involves taking actual measurements and augmenting them to explore unmeasured or previously unavailable data modalities. This method enhances the quality of training data, especially in fields like biology, by using AI to create additional valuable data from already collected measurements, thereby improving model performance and insights without relying solely on artificial data generation.

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