Analysis
This article dives into the fascinating world of understanding sentence meaning within Natural Language Processing (NLP), setting the stage for grasping the inner workings of cutting-edge models like the Transformer. It skillfully explains how Recurrent Neural Networks (RNNs) previously handled the complexities of sentence structure, a crucial stepping stone to understanding current advancements. This series promises a clear and accessible exploration of complex AI concepts.
Key Takeaways
- •The article is part of a series explaining Transformer models, starting with fundamental concepts.
- •It clarifies how RNNs tackled the problem of understanding sentence meaning before Transformers.
- •The core idea is that the order of words is crucial for sentence meaning.
Reference / Citation
View Original"The main point is that sentence meaning fundamentally depends on 'order'"