Nils Reimers: Sentence Transformers, Search, Future of NLP | Learning from Machine Learning #3
Learning from Machine Learning
What Are the Biggest Jumps in Text Embedding?
The first big splash, which caused a lot of interest was like word to VEC. And then second big splash was in 2017, 18 like animal was contextualized for the FedEx. So those okay, hotel and motel are close by and Apple and banana and strawberry has certain nationship. But we use words in a big setting like the word apple. I can refer to the food or I can referring to the company or I can refer probably to some movie or some or some podcast series or some website says. This enables more complex understanding of how the words are used.
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