We all know about ๐ฆ๐ค๐ which stores structured data. ๐ก๐ผ๐ฆ๐ค๐, which takes unstructured data in the form of document. and ๐๐ฟ๐ฎ๐ฝ๐ต, which stores data in nodes.
and that's how it formulates a lot of its relationship.
Now, come with the ๐ฉ๐ฒ๐ฐ๐๐ผ๐ฟ ๐ฑ๐ฎ๐๐ฎ๐ฏ๐ฎ๐๐ฒ which is naturally all our AI applications.
๐๐ผ๐ ๐ผ๐๐ฟ ๐ฏ๐ฟ๐ฎ๐ถ๐ป๐ ๐ฎ๐น๐ฟ๐ฒ๐ฎ๐ฑ๐ ๐๐ต๐ถ๐ป๐ธ ๐ถ๐ป ๐๐ฒ๐ฐ๐๐ผ๐ฟ๐
Think of vectors as GPS coordinates for ideas. Just as GPS uses numbers to locate places, vector databases use mathematical coordinates to map concepts, meanings and relationships. When you search a vector database, youโre not just looking for exact matches โ youโre finding patterns and relationships, just as your brain does when recalling a memory.
This is exactly how vector databases work.
The future of human-AI collaboration
The parallels between human memory and vector databases go deeper than simple retrieval. Both excel at compression, reducing complex information into manageable patterns. Both organize information hierarchically, from specific instances to general concepts. And both excel at finding similarities and patterns that might not be obvious at first glance.