Comment on Why AutoGPT engineers ditched vector databasesparentComments−dartos2ySearching in LLM land is finding the cosine similarity of two high dimensional vectors. Vector databases try optimizing that operation.Maybe they found search by plain old dot product faster−akomtu2yCosine what? Isn't it just dot product?−dartos2yThere are a few “distance” metrics that are used.AFAIK cosine similarity or cosine distance is a common one bc it’s faster than a dot product.
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Searching in LLM land is finding the cosine similarity of two high dimensional vectors. Vector databases try optimizing that operation.
Maybe they found search by plain old dot product faster
Cosine what? Isn't it just dot product?
There are a few “distance” metrics that are used.
AFAIK cosine similarity or cosine distance is a common one bc it’s faster than a dot product.