Generative AI systems rely heavily on training data to make accurate predictions.
Having access to more data can lead to better performance of AI models.
Data curation and quality are crucial for model success, sometimes more important than quantity.
High-quality annotations have shown to enhance the performance of AI models significantly.
The emphasis on large, high-quality datasets may centralize AI development among tech giants with substantial budgets.
Some companies resort to questionable methods to acquire training data, raising ethical concerns in the AI industry.
Even legitimate data deals can contribute to an inequitable AI ecosystem.
Source: https://techcrunch.com/2024/06/01/ai-training-data-has-a-price-tag-that-only-big-tech-can-afford/
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