Discover how Transformers work in this engaging breakdown of the key math concepts that power them:
Matrix Multiplication (Self-Attention): Learn how words are transformed into vectors (Query, Key, Value) and compared to compute attention scores, ensuring each word focuses on the most relevant context.
Multi-Head Attention: See how multiple attention heads analyze different aspects of a sentence, enhancing the model's understanding.
Gradient Descent: Understand how the model learns from its mistakes by adjusting its parameters to improve predictions.
Probability Distributions: Watch how the Transformer predicts the next word by assigning probabilities to the entire vocabulary.
Real-World Example: Follow a step-by-step example showing how Transformers process and predict sentences.
This concise, visually-rich explanation demystifies the tech behind language models. Watch now and grasp the math that makes AI smarter!
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