Word embedding - Wikipedia
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2026-07-18 09:16:47
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Text Highlight2026-07-18 15:40:47
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"Word embeddings may contain the biases and stereotypes contained in the trained dataset"
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Garbage in, garbage out—models just learn what we feed 'em.
Text Highlight2026-07-18 12:37:47
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"words with multiple meanings are conflated into a single representation"
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But don't we just average senses anyway? Works fine for most tasks honestly.
Text Highlight2026-07-18 12:28:47
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"words with multiple meanings are conflated into a single representation"
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Yeah that's why transformers killed static embeddings, context is everything.
Text Highlight2026-07-18 10:21:11
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"a word embedding is a representation of a word"
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I always thought embeddings were just for search, but this sounds way broader.
Text Highlight2026-07-18 10:12:11
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"a word embedding is a representation of a word"
Whisper Note
If similar words are close in space, does that mean 'hot' and 'cold' are neighbors?
Text Highlight2026-07-18 10:03:11
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"a word embedding is a representation of a word"
Whisper Note
So it's basically a dictionary but for computers, got it.
Text Highlight2026-07-18 09:34:47
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"a real-valued vector that encodes the meaning of the word"
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Makes sense, like when I tried to build a chatbot and it kept mixing up synonyms.
Text Highlight2026-07-18 09:25:47
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"a real-valued vector that encodes the meaning of the word"
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But how do you actually measure 'closer in space'? Seems kinda fuzzy to me.
Text Highlight2026-07-18 09:16:47
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"a real-valued vector that encodes the meaning of the word"
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So basically it's just a fancy way to say words become numbers that mean stuff.
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