🤯 Did You Know (click to read)
BERT’s embeddings allow virtual assistants to reference previous turns in a conversation to maintain context and relevance.
BERT captures context across multi-turn conversations using bidirectional embeddings. Fine-tuning on dialogue datasets allows the model to generate responses that consider prior conversational history. This improves coherence, relevance, and user satisfaction in chatbots, virtual assistants, and interactive AI applications.
💥 Impact (click to read)
Conversational coherence enhances usability and engagement in AI-driven communication systems, improving customer service, education, and interactive experiences.
For users, BERT provides contextually aware responses. The irony is that coherence is produced statistically rather than through comprehension or intent.
Source
Devlin et al., 2018, BERT: Pre-training of Deep Bidirectional Transformers
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