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Embeddings are a good starting point for the AI curious app developer

Vector embeddings have been an Overton window shifting experience for me, not because they’re sufficiently advanced technology indistinguishable from magic, but the opposite. Once I started using them, it felt obvious that this was what the search experience was always supposed to be: less “How did you do that?” and more mundanely, “Why isn’t this everywhere?”

Vector embeddings have been an Overton window shifting experience for me, not because they’re sufficiently advanced technology indistinguishable from magic, but the opposite. Embeddings are just arrays of numbers, but they contain a compressed form of a considerable amount of human knowledge and shrink features that used to be substantial specialized projects into ones that individual product engineers can take on. It doesn’t seem like any of the major players are doing anything crazy here; the significant knobs appear to be whether or not to embed keys or just values and which attributes of your records are relevant.

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