由对抗样本发现的神经网络敏感性（理论背景包括决策边界的不连续性等），正是可重编程性的基础。我们不再将这种敏感性仅视为安全缺陷，而是建设性地利用它，在不重新训练的情况下将预训练模型重定向到新的任务。精心设计的 program/prompt ...

The application of neural network models to semiconductor device simulation has emerged as a transformative approach in the field of electronics. These models offer significant speed improvements over ...

New research from the University of St Andrews, the University of Copenhagen and Drexel University has developed AI ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Kimi has a standard mode and a Thinking mode that offers higher output quality. Additionally, a capability called K2.5 Agent ...

The 2024 Nobel Prize in Chemistry was recently granted to David Baker, Demis Hassabis and John M. Jumper, renowned for their pioneering works in protein design.

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.