
Transformers: Beyond Language, Shaping Multimodal AI
Transformer models have revolutionized the field of Natural Language Processing (NLP) and are now impacting various other domains like computer vision. Their ability to handle long-range dependencies and process data in parallel has made them the go-to architecture for tasks ranging from language translation to image recognition. This article delves into the intricacies of transformer models, exploring their architecture, applications, and impact on modern AI.
Understanding the Transformer Architecture
The transformer model, introduced in the groundbreaking paper "Attention is All You Need," departs from traditional recurrent neural networks (RNNs) by relying entirely on attention mechanisms. This innovative approach enables the model to capture relationships between words or data points, ...