When AI Eats Itself: On the Caveats of AI Autophagy

Understand

Generative Artificial Intelligence (AI) technologies and large models are producing realistic outputs across various domains, such as images, text, speech, and music.

• Creating these advanced generative models requires significant resources, particularly large and high-quality datasets.
• To minimise training expenses, many algorithm developers use data created by the models themselves as a cost-effective training solution.
• However, not all synthetic data effectively improve model performance, necessitating a strategic balance in the use of real versus synthetic data to optimise outcomes.