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Learn Machine Learning·/u/Shriyadita10·3 days ago
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Most explanations of Transformers start with "attention is all you need" and then immediately throw a matrix multiplication diagram at you. That didn't work for me. Here's the intuition that finally made it click. The core problem Transformers solve Old models (RNNs) read text like you'd read a book with amnesia - word by word, forgetting earlier context by the time they reach the end. Transformers threw that out entirely. Instead they look at the entire sentence at once and ask: "for each word, which other words matter most?" What "attention" actually means Imagine you're reading: "The trophy didn't fit in the suitcase because it was too big." What does "it" refer to? The trophy. You figured that out by looking back at the whole sentence, not just the word before "it." That's exactly what attention does - for every word, it calculates a relevance score against every other word and uses that to build meaning.…

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