The article also covers various tech news, including startups attracting funding for non-alcoholic beverages, Bing introducing generative AI into its results, and OpenAI launching a mini version of its latest AI model. Other topics include a UK school reprimanded for unlawful use of facial-recognition technology, a global tech outage affecting various sectors, and a study from the Federal Trade Commission on "dark patterns" in subscription apps.
Key takeaways:
- AI models are at risk of "model collapse," where the content input and output of a model converge and turn into nonsensical data, according to a research paper published in Nature.
- This phenomenon could pose a significant risk for companies using synthetic data generated by AI for training their models.
- As more AI-generated content fills the web, the risk of model collapse increases, potentially leading to a loss of understanding of the original data.
- Model collapse is likened to a snake eating its own tail, where a process that starts with diverse real-world data ends up producing identical, distorted outputs.