🎓 Embeddings are how AI turns meaning into numbers.
Every word, sentence, or token gets converted into a list of numbers (a vector) that captures its meaning. Similar things end up close together in that number space, different things end up far apart.
Builders use this to power search, recommendations, and fraud detection. A trading bot could use embeddings to find news articles that "mean" the same thing even if the wording is totally different.
Example: "BTC crashes" and "Bitcoin drops hard" land near each other in embedding space, even with zero shared words.
Takeaway: embeddings let machines compare meaning, not just text.
August 28, 2026 128
