<ul data-eligibleForWebStory="true"><li>Embeddings in AI convert words or data into numerical vectors for algorithms to understand relationships and context.</li><li>Transformers use positional encoding to maintain the order and relationships between input tokens in natural language processing.</li><li>In a Transformer model, transformer blocks work together using self-attention to understand contextual relationships between words.</li><li>Transformers use linear layers and the softmax function to make predictions based on learned vector representations, turning complex patterns into clear outcomes.</li></ul>

Transformers in Artificial Inteligence?

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