Developing a chatbot for the Chinese market requires an understanding of cultural sensitivities and regulatory constraints. While models like Baidu's Ernie attract significant user bases, their effectiveness is constrained by the necessity to comply with local laws and societal norms. This results in limitations when addressing certain topics, reflecting a broader trend among AI systems where ethical considerations influence operational protocols. Building a successful Chinese-language chatbot involves more than just technical capabilities; it necessitates a nuanced comprehension of what 'working well' means within the specific cultural and governmental context.
AIs built on Large Language Models have wowed by producing particularly fluent text. However, their ability to do this is limited in many languages. As the data and resources used to train a model in a specific language drops, so does the performance of the model, meaning that for some languages the AIs are effectively useless.
Researchers are aware of this problem and are trying to find solutions, but the challenge extends far beyond just the technical, with moral and social questions to be answered. This podcast explores how Large Language Models could be improved in more languages and the issues that could be caused if they are not.
Watch our related video of people trying out ChatGPT in different languages.
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