ai's self-destruction: the future and challenges of machine translation

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research by dr. ilya shumelov and his team at the university of oxford shows that when using generative ai software for translation, model collapse problems gradually emerge. these ai models will eventually show a "self-destruction" phenomenon when they continue to rely on the text content they generate. the researchers found that after repeated queries, the output information of the ai ​​model gradually deviates from the truth, eventually becomes worthless, and even appears completely meaningless gibberish.

this "model collapse" phenomenon occurs because ai models are overly dependent on the content they generate. when this content is constantly polluted and updated, it will eventually lead to the erosion of training data, making the output information difficult to understand. dr. shumelov said that model collapse occurs very quickly and is difficult to detect, which makes it quietly affect various data in the early stages and gradually lead to a reduction in the diversity of output information, and even a deterioration in the performance of some data, which masks the improvement of other data.

the occurrence of this phenomenon means that ai technology is facing new challenges. if human-generated data is filtered out quickly and model collapse problems continue to occur, then ai may be "self-destructing." this will not only have a huge impact on the internet, but may also hinder the development of other fields.

to solve this problem, researchers proposed a key solution: ensuring that ai models can effectively access existing non-ai generated content and continuously introduce new artificially generated content. only in this way can ai maintain its development and progress and provide humans with more accurate and valuable translation services.

this "model collapse" phenomenon reminds us that the future of artificial intelligence technology requires balancing and coordinating the development directions of various fields. at the same time, we need to continue to study how to make ai technology more autonomous and more humane so that it can truly play its value in communication and creation.