DeepSeek’s cost-saving AI may lead to inaccuracy in model performance: research
In one example, adding irrelevant text before the same piece of computer code impaired DeepSeek’s ability to choose the correct answer
New research has exposed a potential flaw in the memory-saving technology underpinning DeepSeek’s models, marking a rare challenge to a breakthrough that has helped the Chinese artificial intelligence lab close the gap with US rivals OpenAI and Anthropic with its low-cost approach.
The study, which has not been peer-reviewed, said that DeepSeek’s efforts to reduce the memory needed to process lengthy inputs may come at the expense of reliability, as the models were more likely to miss the same information when it appeared in certain positions in a document.
“The phenomenon appears in DeepSeek-V4, V4.1, and all compressed models we pretrained,” the paper said.
