Gartner estimates that by 2030, the use of synthetic data will completely surpass the use of real data in training artificial intelligence models, highlighting a significant paradigm shift.
Synthetic data is artificially generated data designed to mimic real-world data, created using algorithms and statistical models that replicate the patterns and characteristics of actual data.
As algorithms transition from being primarily fueled by human-generated data to being trained by other algorithms using synthetic data, it raises essential questions for designers.
This emerging $2.1 billion market indicates that new design roles are needed to address the complexities and opportunities presented by synthetic data.
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