Synthetic data seen as AI’s future
As AI models consume more real-world data, experts like Elon Musk warn that the industry is running out of fresh training material. Companies are now turning to synthetic data to sustain AI development.
Elon Musk has echoed concerns from AI researchers that the industry is running out of new, real-world data to train advanced models. Speaking during a livestream with Stagwell’s Mark Penn, Musk noted that AI systems have already processed most of the available human knowledge. He described this data plateau as having been reached last year.
To address the issue, AI developers are increasingly turning to synthetic data, information generated by the AI itself, to continue training models. Musk argued that self-generated data will allow AI systems to improve through self-learning, with major players like Microsoft, Google, and Meta already incorporating this approach in their AI models.
While synthetic data offers cost-saving advantages, it also poses risks. Some experts warn it could cause “model collapse,” reducing creativity and reinforcing biases if the AI reproduces flawed patterns from earlier training data. As the AI sector pivots towards self-generated training material, the challenge lies in balancing innovation with reliability.
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