Over the weekend, it was reported that OpenAI is experiencing a slowdown in the advancement of its new flagship models. This challenges the core belief that AI models will continue to scale at a consistent rate as long as there is more data and computing power. Data scientist Yam Peleg suggests that the focus is now on data quality rather than quantity, indicating that major players have reached the limits of training longer and collecting more data.
Key takeaways:
- OpenAI is reportedly facing challenges as it attempts to scale up its large language models (LLMs) like ChatGPT, with efforts seemingly hitting a plateau, according to cofounder Ilya Sutskever.
- Sutskever's comments suggest that AI companies, including OpenAI, may be encountering the law of diminishing returns as they continue to pour resources into AI development.
- Reports suggest that with each new flagship model, OpenAI is seeing a slowdown in the sort of "leaps" users have come to expect since the release of ChatGPT in December 2022.
- Data scientist Yam Peleg suggests that the focus in AI development is now shifting towards data quality, as companies have likely reached the limits of training longer and collecting more data.