{"id":21544,"date":"2023-08-12T17:27:45","date_gmt":"2023-08-12T15:27:45","guid":{"rendered":"https:\/\/www.graviton.at\/letterswaplibrary\/what-advantages-or-disadvantages-does-synthetic-data-have-over-real-world-data\/"},"modified":"2023-08-12T17:27:45","modified_gmt":"2023-08-12T15:27:45","slug":"what-advantages-or-disadvantages-does-synthetic-data-have-over-real-world-data","status":"publish","type":"post","link":"https:\/\/www.graviton.at\/letterswaplibrary\/what-advantages-or-disadvantages-does-synthetic-data-have-over-real-world-data\/","title":{"rendered":"What Advantages Or Disadvantages Does Synthetic Data Have Over Real-world Data?"},"content":{"rendered":"

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Need to understand the perks to pivot to a synthetic data generator and whether it has a market. I work in a data annotation company by the name of Acme AI and a key bottleneck of clients is a scarcity of data (in many cases) for training ML models. Naturally, this led me to question the existence of said novel ML solution if data is scarce in the first place (i.e. no market value). Seeking responses with practical examples or experiences.<\/p>\n<\/div>\n

submitted by \/u\/SithisR <\/a>
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