Large Language Models
Positional Encoding
Adding position information to token embeddings so the model understands word order in sequences.
Related Concepts
- Transformer: Explore how Transformer relates to Positional Encoding
- Embedding: Explore how Embedding relates to Positional Encoding
- Sequence Order: Explore how Sequence Order relates to Positional Encoding
Why It Matters
Understanding Positional Encoding is crucial for anyone working with large language models. This concept helps build a foundation for more advanced topics in AI and machine learning.
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This term is part of the comprehensive AI/ML glossary. Explore related terms to deepen your understanding of this interconnected field.
Tags
large-language-models transformer embedding sequence-order
Related Terms
Embedding
A dense vector representation of discrete data (words, tokens) in continuous space, capturing semantic relationships.
Transformer
A neural network architecture introduced in 'Attention is All You Need' (2017) that relies entirely on self-attention mechanisms, becoming the foundation for modern LLMs.