Fudan University in Shanghai, China, launched a new AI language model platform called MOSS, which was designed to provide a ChatGPT-style experience to its users. However, just hours after its launch, the platform crashed, leaving users unable to access its features. The Fudan University team has since issued an apology for the inconvenience caused and promised to fix the issues.
The MOSS platform was designed to provide a conversational AI experience, similar to that of OpenAI's ChatGPT, which has gained widespread popularity in recent months. It was created by a team of researchers at Fudan University, who had been working on the platform for several months. The goal was to create a user-friendly and intuitive system to understand and respond to natural language queries.
Shortly after the launch of MOSS, according to a report by Reuters, users began reporting issues with the platform. Some were unable to access it at all, while others reported that the system was slow and unresponsive. As the number of users trying to access the platform increased, the system became overloaded, ultimately resulting in a complete crash.
Interestingly, MOSS’ name bears resemblance to a superintelligent quantum computer in the Chinese sci-fi blockbuster Wandering Earth 2 which was released last month.
The team at Fudan University acknowledged that the system had not been properly stress-tested before launch and that they had underestimated the demand for the platform. In a statement, the team said, "MOSS is still a very immature model, it is still has a long way to go before reaching ChatGPT. An academic research lab like us is unable to produce a model whose ability nears ChatGPT."
"Our computing resources were not enough to support such large traffic and as an academic group we do not have sufficient engineering experience, creating a very bad experience and first impression on everyone, and we hereby express our heartfelt apologies to everyone," the statement added.
The incident highlights the challenges of developing and launching new AI platforms, particularly those that rely heavily on natural language processing. While these systems have the potential to revolutionize the way we interact with technology, they also require extensive data, testing and refinement before they can be deployed at scale.
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