A new AI language model platform called MOSS was introduced by Fudan University in Shanghai, China, with the goal of giving users a ChatGPT-like experience. However, the platform crashed a few hours after it was launched, preventing users from using its features. The Fudan University team later apologized for the trouble they had caused and promised to make things right.
Similar to OpenAI’s ChatGPT, which has become increasingly popular lately, the MOSS platform was created to offer a conversational AI experience. The platform was developed by a group of researchers from Fudan University who had been working on it for several months. The objective was to develop an intuitive and user-friendly system that could recognize and respond to natural language queries.
Users started citing problems with the platform soon after MOSS launched, according to a Reuters report. While others complained that the system was unreliable and slow, some people were unable to access it at all. The system became overloaded as more users attempted to access the platform, ultimately leading to a complete crash.
It’s interesting to note that MOSS shares a name with a superintelligent quantum computer that appears in the recent Chinese sci-fi hit Wandering Earth 2.
The Fudan University team admitted that the system had not been properly stress-tested prior to launch and that they had overestimated the platform’s demand. The team stated that “MOSS is still a very immature model and has a long way to go before reaching ChatGPT” in a statement. A model with capabilities close to ChatGPT cannot be created by an academic research lab like ours. “.
The statement continued, “We hereby express our sincere apologies to everyone for the very poor experience and first impression we have caused. Our computing resources were not enough to support such large traffic, and as an academic group we do not have sufficient engineering experience.”
The incident serves as a good example of the difficulties in creating and introducing new AI platforms, especially those that heavily rely on natural language processing. These systems need a lot of data, testing, and refinement before they can be deployed at scale, even though they have the potential to revolutionize the way we interact with technology.
