Transformer 架构的伟大之处，不仅在于提出了注意力机制，更在于提供了一套 “模块化” 的设计框架 —— 通过组合编码器（Encoder）和解码器（Decoder），可以衍生出多种结构变体。从 BERT 的 “纯编码器” 到 GPT 的 “纯解码器”，从 T5 的 “编码器 - 解码器” 到 ...

Essential AI Labs Inc., a startup led by two co-inventors of the foundational Transformer neural network architecture, today announced that it has raised $56.5 million from a group of prominent ...

机床振动引起的表面质量分类中，Transformer编码器与Mamba SSM的性能比较。通过模拟和实验数据，发现Mamba SSM在保持高分类准确性的同时，计算效率提升4.7倍，实时性达0.38ms，满足数控机床亚毫秒响应需求，并验证了频谱特征的有效性。 该研究通过对比Transformer ...

Transformer-based models have rapidly spread from text to speech, vision, and other modalities. This has created challenges for the development of Neural Processing Units (NPUs). NPUs must now ...

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. (In partnership with Paperspace) In recent years, the transformer model has ...

The goal is to create a model that accepts a sequence of words such as "The man ran through the {blank} door" and then predicts most-likely words to fill in the blank. This article explains how to ...