Half a Million Fake Headlines, Deduplicated on Purpose

A July 9 NVIDIA guide describes producing 502,536 synthetic financial headlines across 13 categories in 82 iterations. A naive 50,000-item run lost 65 percent of its outputs as near-duplicates, so the published workflow compares each new batch with the full accumulated corpus, removes close semantic matches, selects unusually distant examples for the next prompt, and raises weights for underrepresented event types. The dataset is synthetic training material, not real market news, and its quality claims require downstream testing. Its design lesson travels: novelty has to be measured against everything already retained, not merely within today's batch.