AI

Visualizing How AI Thinks

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Module 01 β€’ How AI Reads Your Text

Tokens: AI Reads in Puzzle Pieces

Short words = 1 piece. Long words get chopped: mis|under|stand|ing = 4.

12
Human Words
25
AI Tokens Used
8
Long Words Chopped
Pick one:
Cut lines | 13 internal word cuts
AI Tokens
πŸ‘† Tap a piece
πŸ’‘ Why care?
You pay β€” and hit limits β€” by tokens, not words.
Module 02 β€’ Embeddings

Brain Map: Similar Words Live Close Together

Bigger or fine-tuned models = sharper map = fewer mix-ups.

β‘  Pick a brain
Pick one:
🧊
πŸ–±οΈ Drag to rotate πŸš€ Frontier 1T+ β€’ "Bank" β†’ 🌿 River & Nature
Map sharpness πŸš€ Frontier Model (1T+)
Sharpness 98% (Ultra-Sharp)

Nearest to "Bank" 🌿 River & Nature
AI reply βœ… Understands Context

Module 03 β€’ How AI Writes

Prediction: Super Autocomplete

Score every next word β†’ roll a weighted die β†’ add one word β†’ repeat.

Pick one: Step 0 of 5
0.2 β€” Safe
0 Safe 0.7 1.5 Wild
Next-word odds
πŸ’‘ A 25% word wins ~1 in 4 rolls β€” that's why answers vary.
Module 04 β€’ Context Window

Memory Limit: Old Messages Fall Off

AI only sees the last 100 tokens. Add messages β†’ your πŸ• and πŸ’Ό rules fall off the cliff.

Window 60 / 100 Tokens
πŸ• SAFE
πŸ’Ό SAFE
Pick one:
πŸ•³οΈ Forgotten 0 tokens lost
🚫 Invisible
πŸͺŸ What AI sees (100)
βœ… Both remembered
⚠️ Oldest 25t 50t 75t Newest βž”
πŸ’‘ Ask below β†’ add πŸ’Ό PDF twice β†’ ask again.
🧠 What AI sees now
🎯 Test its memory
πŸ‘† Ask a question
Module 05 β€’ Long Chats Go Bad

Drift, Pollution & Rot

Watch the 🧠 orb (AI's focus) get pulled off target.

πŸ—ΊοΈ Where AI's focus goes
🧭 Drift
🧠 AI Focus Vector: (X: -0.55, Y: -0.45, Z: +0.60)
↔ X: Work vs Fun ↕ Y: Verified vs Polluted β†— Z: Recent vs Buried
πŸ”„ Drag to rotate 3D
πŸ’¬ The chat Quality: 45%
🧭 Drift

Attention
Module 06 β€’ Training

Training: Guess β†’ Check β†’ Adjust

A model is billions of dials. Each wrong guess nudges them. Repeat trillions of times.

πŸŽ“ Train vs. Prompt
Train = permanent.
Prompt = today only.
🎬 How a model learns
πŸ“š 1. Read the internet
πŸ”„ Step 1,420 β€’ 94%
1️⃣ Show

Hide a word: πŸ’Ό "approve the Q4 ___"

2️⃣ Guess

AI guesses "pizza" ❌

3️⃣ Score

Right answer: "budget". Measure the miss.

4️⃣ Adjust

Nudge the dials. Repeat for months.

Pick one:
Compare 3 setups
🧠 Brain & memory πŸŽ“ 5,000 examples
Brain dials 100% Tuned

πŸͺŸ Memory used up-front 12 / 100 Tokens (88% Free!)

Reply Speed
⚑ 0.3 sec
Cost Per Chat
πŸ’² Very Low
Format Match
🎯 99% Exact
πŸ’¬ You type
πŸ€– AI replies βœ… Right format
🎯 Fine-tune or not?
πŸ‘† Tap one
Module 07 β€’ Speed Trick

KV Cache: Don't Re-Read, Remember

AI saves a note for every past word, so each new word is 1 step, not a full re-read.

πŸ”‘ Key = label

"Budget"

πŸ“¦ Value = meaning

"$50,000"

Pick one:
⚑ Saved notes β†’ new word
⚑ 1 step
⏱️ Latency: 25ms
Writing word #6 of 10

Saved New Redone
πŸ” Note for
πŸ”‘
πŸ“¦
πŸ‘† Tap a word
πŸ“Š Score
This word 1 word computed

Total work 6 vs 21 ops

⏱️ Latency (Response Wait Time) 25ms (Instant)
0ms (Instant) 500ms 1,000ms+ (Lag)

Latency is how long you wait before the AI types. KV Cache keeps latency flat and near-zero!

πŸ’Ύ Memory used 6 Sticky Notes Saved

Trade-off: speed costs memory.

πŸ’‘ Tip: keep the start of your prompt the same
πŸ‘† Tap one