They Got Lost in the Transformer, Episode 1: What Even Is an Embedding?

About this episode

This episode introduces word embeddings and Transformers through a story-driven approach, exploring how language is represented as vectors and the relationships that emerge from them.

This story was originally published on HackerNoon at: https://hackernoon.com/they-got-lost-in-the-transformer-episode-1-what-even-is-an-embedding . A story-driven intro to word embeddings and Transformers, how language becomes vectors, relationships emerge, and meaning turns into math. Check more stories related to data-science at: https://hackernoon.com/c/data-science . You can also check exclusive content about #word-embeddings , #word-embeddings-explained , #nlp-embeddings , #hackernoon-scifi , #transformer-embeddings , #word2vec-explanation , #ai-language-models-basics , #neural-networks , and more. This story was written by: @enkido . Learn more about this writer by checking @enkido's about page, and for more stories, please visit hackernoon.com . Floki struggles to understand how words become numbers—until Astrid reframes embeddings as positions in a conceptual space, where meaning comes from relationships, not labels. Through a simple equation—King minus Man plus Woman equals Queen—he realizes models don’t memorize language, they map it. The idea deepens when linked to neuroscience: our brains may represent meaning the same way. The mystery shifts from confusion to…

Topics covered

• word embeddings
• Transformers
• language vectors
• neuroscience
• AI language models

Keywords

• word embeddings
• Transformers
• language models
• neural networks
• AI

Mentioned in this episode

Organizations: HackerNoon

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