Here is the Joke and it may help to understand how vector embedding works.

I performed vector embedding on my name, and it placed me closest to 'sugar' in the latent vector space. This makes sense because my name, Seenivasa, means 'sweet smell.' 'Seeni' in my mother tongue (Tamil) means 'sugar.'

Here's a joke that illustrates how chunking helps in understanding semantic or contextual meaning:

"Ever since I started working on the GenAI RAG framework, my eating style has become quite different. Now, I eat my food in small chunks and savor each byte, byte by byte."