So, it was time for my last yr mission—you know, that large one that everybody stresses about. At first, every part felt fairly regular—nothing too thrilling. Then one random day, I had this thought:
“How does Google know the distinction between ‘apple’ in these two searches?”
- “What number of staff work at Apple?”
- “What number of energy are in an apple?”
Each queries use the phrase apple, however Google someway understands that one is a few tech firm and the opposite is a few fruit. How does that even work? 🤯
That’s once I began digging into semantic search, embeddings, vectors, and similarity search, and belief me, it was a recreation changer.
On this weblog, I’ll stroll you thru the small mission I constructed utilizing QDrant Vector Database — a instrument that makes semantic search quick and environment friendly. Let’s dive in! 🚀
