DeepSeek found that it could improve the reasoning and outputs of its model simply by incentivizing it to perform a trial-and ...

DeepSeek says its R1 model did not learn by copying examples generated by other LLMs. Credit: David Talukdar/ZUMA via Alamy ...

When researchers are building large language models (LLMs), they aim to maximize performance under a particular computational ...

Demis Hassabis says AI hasn't hit PhD-level intelligence because it lacks key capabilities like continued learning.

Abstract Dynamic MRI reconstruction, one of inverse problems, has seen a surge by the use of deep learning techniques. Especially, the practical ...

Current large language models perform excellently in many tasks but still exhibit significant deficiencies in complex reasoning. The ability to perform complex reasoning is crucial for applications ...

However, a study published in December 2024 by researchers Wang Qun, Liu Yang, Lin Qingquan, Qu Zhijiu, Jiang Ling, and others from the Xiaoduo AI Lab has challenged this notion. The Xmodel-2 they ...

Abstract: The communication overhead in distributed deep learning caused by the synchronization of model parameters across multiple devices can significantly impact training time. Although powerful ...

Abstract: Diagnosis of brain tumors remains a significant problem in the field of neuro-oncology, especially when there are limited resources since the automated MRI analysis requires considerable ...