How Transformers Actually Think: Query, Key & Value (Q, K, V) | AI Fundamentals Decoded | MIK
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How Transformers Actually Think: Query, Key & Value (Q, K, V) | AI Fundamentals Decoded | MIK
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Hi Everyone, welcome to the 7th video of our brand new Playlist: "AI Fundamentals Decoded" by codestorywithMIK.
In the last video, we learned that modern LLMs use the Transformer architecture and that Attention is its core superpower. But how does an AI actually decide which words matter to each other? What are Query, Key, and Value? In this video, we break down the entire math pipeline behind Self-Attention—from Dot Products and Softmax without getting lost in scary formulas.
Video Title : How Transformers Actually Think: Query, Key & Value (Q, K, V) | AI Fundamentals Decoded | codestorywithMIK
Topic : What are Query, Key, and Value (Q, K, V) in Self-Attention?
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Video Summary :
In this episode, we unpack the mathematical engine of Transformers: Query (Q), Key (K), and Value (V). Using the library search and juice blend analogies, we walk through how a token formulates a question (Query), matches with other tokens (Keys) via dot products, normalizes relevance using Softmax, and weights the actual content (Values) to create a brand new contextual representation. This complete Self-Attention loop demystifies how modern LLMs understand sentence context, setting up our next discussion on Context Windows.
✨ Timelines✨
00:00 Introduction
00:55 Recap
01:39 Q K V
02:07 Why Q K V ?
03:25 Attention Scores
06:17 Attention Weights Softmax
10:00 Complete Flow
11:13 Ending Notes
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