1月13日消息,今日,DeepSeek发布新论文《Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models》 (基于可扩展查找的条件记忆:大型语言模型稀疏性的新维度)。
DeepSeek于12日晚发布新论文《Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language ...
就在十几个小时前,DeepSeek 发布了一篇新论文,主题为《Conditional Memory via Scalable Lookup:A New Axis of Sparsity for Large Language ...
Open-weight LLMs can unlock significant strategic advantages, delivering customization and independence in an increasingly AI ...
Large language models have grown so vast and complex that even the people who build them no longer fully understand how they work. A single modern ...
2026年1月13日,DeepSeek与北京大学合作发布新论文《Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models》,创始人梁文锋为合著作者之一。论文提出条件记忆(conditional memory)概念,通过可扩展查找结构解决大语言模型知识检索效率低下的问题。同日,团队 ...
Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I closely explore the rapidly emerging ...
The proliferation of edge AI will require fundamental changes in language models and chip architectures to make inferencing and learning outside of AI data centers a viable option. The initial goal ...
Researchers show that LLMs can reproduce copyrighted training data almost verbatim. This means headaches for model providers.
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