Transformer 架构因其强大的通用性而备受瞩目，它能够处理文本、图像或任何类型的数据及其组合。其核心的“Attention”机制通过计算序列中每个 token 之间的自相似性，从而实现对各种类型数据的总结和生成。在 Vision Transformer 中，图像首先被分解为正方形图像块 ...

The self-attention-based transformer model was first introduced by Vaswani et al. in their paper Attention Is All You Need in 2017 and has been widely used in natural language processing. A ...

三人是紧密的合作伙伴。 最近，OpenAI 又迎来了新的人事变动，但这次不是某个技术大牛离职，而是从谷歌挖来了一些新鲜血液。 这些「新人」来自谷歌 DeepMind 的苏黎世办事处，包括资深研究科学家 Xiaohua Zhai（翟晓华）、研究科学家 Lucas Beyer 和 Alexander Kolesnikov。

In the last decade, convolutional neural networks (CNNs) have been the go-to architecture in computer vision, owing to their powerful capability in learning representations from images/videos.

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Transformer-based large language models ...

Transformers, first proposed in a Google research paper in 2017, were initially designed for natural language processing (NLP) tasks. Recently, researchers applied transformers to vision applications ...