About this Event
Hosted by Red Hat (via Fara 26, 7th floor)
Abstract
As AI floods the digital landscape with content, what happens when it starts repeating itself?
This talk explores model collapse, a progressive erosion where LLMs and image generators loop on their own results, hindering the creation of novel output.
We will show how self-training leads to bias and loss of diversity, examine the causes of this degradation, and quantify its impact on model creativity.
Finally, we will also present concrete strategies to safeguard the future of generative AI, emphasizing the critical need to preserve innovation and originality.
By the end of this talk, attendees will gain insights into the practical implications of model collapse, understanding its impact on content diversity and the long-term viability of AI.
Bio: Statistician by education, Valeria is an AI Scientist specializing in real-time models for complex, challenging scenarios. Driven by a deep curiosity for the latest research, she applies advanced analytical techniques to deliver effective solutions in high-impact domains, such as video-surveillance and satellite operations.
Event venue & nearby stays
Red Hat Spa, Via Gustavo Fara, 26, Milano, Italy
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