12,000 Dimensions of Meaning: How I Finally Understood LLM Attention

Words are just points on many number lines that capture part of the meaning

Self-attention in large language models (LLMs) finally made sense when I visualized words as points in 12,000 dimensions—this mental model changed everything for me.

Here’s what you’ll learn:

• How LLMs represent words in high-dimensional space to capture nuanced meanings.

• How self-attention updates word meanings dynamically based on context.

• Why this understanding is key to grasping how AI understands language.

By the end of this video, you’ll have a clear picture of how words, context, and attention interact to make LLMs so powerful.

If you’ve struggled to understand self-attention, I hope this visual change can help make it “click” for you.