MODELS
Bidirectional Encoder Representations from Transformers(BERT)
Definition
A transformer-based language model that reads text bidirectionally to better understand context and word relationships.In-Depth Explanation
BERT, introduced by Google in 2018, revolutionized NLP by training on both left and right context simultaneously. Unlike GPT which reads left-to-right, BERT uses masked language modeling where random words are hidden and the model predicts them from surrounding context. This bidirectional approach excels at understanding tasks like question answering and sentiment analysis.
Real-World Example
BERT powers Google Search to better understand the intent behind queries like "can you get medicine for someone pharmacy".
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