Let's start with the basics: What are embeddings or semantic vectors?

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In the world of natural language processing , canada phone number list embeddings are mathematical representations of words, phrases, or documents. In other words, they transform poorly analyzable text into numbers that represent those ideas, and since they are numbers, they can be manipulated mathematically.

Embedding is the mathematical way of capturing the semantic meaning of things. Thus, transforming things into numbers allows machines to "understand" human language in a deeper way, going beyond simply interpreting individual words.

Imagine you want a machine to understand the difference between "bank" (where you keep your money) and "bank" (a park seat). While a traditional mathematical analysis you could do yourself using Python or JavaScript (or even Excel) would rely on keyword matching and wouldn't be able to differentiate them, embeddings allow you to represent these two words with different "vectors," capturing their distinct meanings and nuances even when they're spelled the same.

Embeddings are generated using machine learning algorithms. These algorithms analyze large amounts of text, such as books, articles, or web pages across the internet, to understand the relationships and nuances of language. During this process, the algorithm learns to predict the context of words and represent them in a multidimensional vector space (which sounds like science fiction, but we'll explain it later). In this space, words with similar meanings are located close to each other, while words with different meanings are located farther away, thus reflecting the semantic relationships between them.



It's important to realize that embeddings don't just deal with words. They capture the essence of the meaning of words and phrases, taking into account the subtleties of natural language.

The ability of a language model to perform this transformation well is one of the things that most differentiates the various generative artificial intelligences that exist, such as ChatGPT, Gemini, or