🤯 Did You Know (click to read)
BERT can distinguish between different meanings of the same word by analyzing both preceding and following words.
BERT’s bidirectional transformer encodings allow it to capture context for words that have multiple meanings, such as 'pitch' in music versus sports. Self-attention mechanisms weigh relevant surrounding words to determine the appropriate sense, improving tasks like question answering, search, and machine translation.
💥 Impact (click to read)
Resolving ambiguity improves NLP applications by enhancing accuracy in search engines, chatbots, and text analysis.
For users, BERT seems to understand nuanced word meanings. The irony is that meaning is derived statistically rather than cognitively.
Source
Devlin et al., 2018, BERT: Pre-training of Deep Bidirectional Transformers
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