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\"\"<\/figure>\n\n\n\n

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                  \n\n\n\n

                  \u4e86\u89e3\u5d4c\u5165\u5f0f\u6709\u52a9\u65bc\u66f4\u6709\u6548\u5730\u5229\u7528\u751f\u6210\u5f0f\u4eba\u5de5\u667a\u80fd\u3002\u6b63\u5982\u6211\u5011\u6240\u8a0e\u8ad6\u7684\uff0c\u5d4c\u5165\u5f0f\u975e\u5e38\u5f37\u5927\uff0c\u53ef\u4ee5\u5e6b\u52a9\u4f01\u696d\u6839\u64da\u8cc7\u6599\u505a\u51fa\u66f4\u660e\u667a\u7684\u6c7a\u7b56\u3002\u6211\u5e0c\u671b\u9019\u7bc7\u6587\u7ae0\u80fd\u5e6b\u52a9\u60a8\u66f4\u597d\u5730\u7406\u89e3\u751f\u6210\u5f0f\u4eba\u5de5\u667a\u80fd\u4e2d\u7684\u5d4c\u5165\u5f0f\uff01<\/p>","protected":false},"excerpt":{"rendered":"

                  Embeddings! They are ways to convert words, sentences or even full fledged documents into numerical representations (vectors) that computers can understand. You can think of embeddings as translating human language into a form that machines can easily process and analyze. To better understand embeddings, let\u2019s start with a simple analogy. Let\u2019s say you are arranging […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[21,22,18,20,23,19,11,24],"class_list":["post-90","post","type-post","status-publish","format-standard","hentry","category-ai-article","tag-bert","tag-contextual-word-representations","tag-embeddings","tag-gpt","tag-semantic-understanding","tag-transformers","tag-understanding-ai","tag-word-embeddings"],"yoast_head":"\nHow Do LLMs Understand Words with Multiple Meanings? - Business Physics AI Lab<\/title>\n<meta name=\"description\" content=\"What trick do LLMs use to differentiate between two words that have a similar meaning ? Embeddings. How do they work ? 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