Research challenges DeepSeek's memory-saving AI, citing accuracy trade-offs

A study led by ByteDance researchers, with co-authors from Princeton, Stanford, and UC Berkeley, suggests that the memory-saving technology used in DeepSeek's models may lead to inaccuracies. This challenges the cost-efficiency advantage that has allowed DeepSeek to compete with US AI labs. The findings are preliminary and not yet independently replicated.