Word Embeddings Explained: How AI Turns Words Into Numbers
How does a language model know that cat and dog are similar? Every word becomes a list of numbers, a point in space, and words that keep the same company end up close together. Inside: John Firth's 1957 idea behind it all, how the dot product measures similarity (cat and dog score 0.88, cat and car 0.31), and the famous king minus man plus woman equals queen result from Tomas Mikolov's team at Google in 2013. Every position and score in this video comes from real GloVe word vectors. Made by Vizuara. #Shorts #AI #MachineLearning #NLP #Embeddings #LLM