🤯 Did You Know (click to read)
BERT can identify the correct answer span in paragraphs based on context to answer user questions accurately.
By producing contextual embeddings for questions and relevant passages, BERT enables extractive question answering. Fine-tuning on datasets like SQuAD improves accuracy, allowing virtual assistants to provide precise and relevant responses within ongoing dialogues or from textual sources.
💥 Impact (click to read)
Contextual QA enhances virtual assistant functionality and user experience by providing accurate answers from documents or conversational history.
For users, AI responses feel intelligent and context-aware. The irony is that answers are statistically derived rather than understood.
Source
Devlin et al., 2018, BERT: Pre-training of Deep Bidirectional Transformers
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