The downturn has also hit employment in construction and related industries, weighing on incomes and consumer confidence more broadly.
The process of improving open-source data began by manually reviewing samples from each dataset. Typically, 5 to 10 minutes were sufficient to classify data as excellent-quality, good questions with wrong answers, low-quality questions or images, or high-quality with formatting errors. Excellent data was kept largely unchanged. For data with incorrect answers or poor-quality captions, we re-generated responses using GPT-4o and o4-mini, excluding datasets where error rates remained too high. Low-quality questions proved difficult to salvage, but when the images themselves were high quality, we repurposed them as seeds for new caption or visual question answering (VQA) data. Datasets with fundamentally flawed images were excluded entirely. We also fixed a surprisingly large number of formatting and logical errors across widely used open-source datasets.
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Несмотря на это, она смогла дожить до подросткового возраста в древнем обществе. Это, по мнению исследователей, доказывает, что даже 13 тысяч лет назад люди заботились о тех, кто слабее.
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00:01, 10 марта 2026Ценности