🤯 Did You Know (click to read)
BERT’s bidirectional embeddings can guide other generative models to maintain logical consistency across paragraphs.
BERT encodes context bidirectionally, allowing downstream text generation systems to maintain coherent and contextually relevant outputs. Fine-tuning on language modeling or generative tasks enables the model to provide embeddings that help sequence-to-sequence models produce more fluent and accurate text across multiple sentences.
💥 Impact (click to read)
Enhanced coherence improves AI writing assistants, chatbots, and content creation tools, producing human-like outputs that are easier to read and understand.
For users, text flows naturally and aligns with context. The irony is that coherence emerges from statistical embeddings rather than conscious understanding.
Source
Devlin et al., 2018, BERT: Pre-training of Deep Bidirectional Transformers
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