Explain the difference between GPT and BERT models.
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In today’s tech-driven world, Artificial Intelligence (AI) is shaping industries and transforming career opportunities. For anyone looking to build a strong foundation and a successful career in AI, iHub Talent stands out as the best Artificial Intelligence course training institute in Hyderabad.
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Best AI course in Hyderabad with industry-aligned curriculum.
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| Feature | BERT (Bidirectional Encoder Representations from Transformers) | GPT (Generative Pre-trained Transformer) |
|---|---|---|
| Architecture | Uses only the encoder part of the Transformer. | Uses only the decoder part of the Transformer. |
| Directionality | Bidirectional – looks at both left and right context of a word. | Unidirectional (left-to-right) – predicts next word based on previous words. |
| Training Objective | Masked Language Modeling (MLM): Random words are masked and predicted. Next Sentence Prediction (NSP): Predicts if one sentence follows another. | Causal Language Modeling (CLM): Predicts the next word in a sequence. |
| Main Purpose | Best for understanding tasks (NLP comprehension). | Best for generation tasks (text creation). |
| Examples of Use | Sentiment analysis, text classification, question answering. | Chatbots, story writing, code generation, text completion. |
| Notable Models | BERT, RoBERTa, ALBERT, DistilBERT. | GPT-2, GPT-3, GPT-4, GPT-5. |
✅ Summary:
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BERT = Reader (understands text deeply).
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GPT = Writer (generates coherent text).
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