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A transformer model that reads text in both directions at once, pretrained on a masked-language-modeling objective. Released by Google in 2018, BERT redefined natural language understanding and remains a strong baseline for classification, search, and question answering when generative output is not required.
Many production NLP systems still run BERT variants because they are fast, cheap, and accurate for fixed tasks. Knowing when BERT beats a frontier LLM is an interview question and a real engineering decision.
A transformer model that reads text in both directions at once, pretrained on a masked-language-modeling objective. Released by Google in 2018, BERT redefined natural language understanding and remains a strong baseline for classification, search, and question answering when generative output is not required.
Many production NLP systems still run BERT variants because they are fast, cheap, and accurate for fixed tasks. Knowing when BERT beats a frontier LLM is an interview question and a real engineering decision.
Definitions are original explanations written for career development purposes. For authoritative technical definitions, refer to NIST, ISO, or the relevant standards body.
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