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<!-- ============================================================ -->
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<!-- ============================================================ -->
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<!-- SLIDE 9: Models — Can answer / Can't answer -->
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<!-- SLIDE 9: How LLMs Generate Text — Autoregressive Loop -->
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<!-- ============================================================ -->
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<!-- ============================================================ -->
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<div class="slide" data-slide="9">
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<div class="slide" data-slide="9">
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<div style="display: flex; flex-direction: column; align-items: center; justify-content: center; min-height: calc(100vh - 120px); text-align: center; gap: 0;">
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<!-- Title -->
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<h1 style="border-bottom: none; padding-bottom: 0; font-size: 2.6rem; margin-bottom: 28px;">One token at a time</h1>
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<!-- Animated SVG -->
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<figure style="max-width: 860px; width: 100%; margin: 0 auto;">
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<img
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src="../assets/llm/llm-basic.svg"
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alt="Animated diagram showing autoregressive generation: prompt feeds into LLM, which predicts one token, feeds it back, and repeats until the full answer is produced."
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style="width: 100%; border-radius: 12px; box-shadow: 0 4px 24px rgba(0,0,0,0.10);"
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/>
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<figcaption style="margin-top: 20px; font-size: 1rem; color: #555; font-style: italic; line-height: 1.5;">
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<strong style="font-style: normal; color: #1a1a1a;">The model produces one token per inference, feeding each result back as new input.</strong><br/>
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This is why streaming feels gradual — and why longer outputs cost more in both latency and API spend.
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</figcaption>
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</figure>
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</div>
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</div>
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<!-- ============================================================ -->
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<!-- SLIDE 10: What's a Token? -->
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<!-- ============================================================ -->
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<div class="slide" data-slide="10">
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<div style="display: flex; flex-direction: column; align-items: center; justify-content: center; min-height: calc(100vh - 120px); text-align: center; gap: 0;">
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<!-- Title -->
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<h1 style="border-bottom: none; padding-bottom: 0; font-size: 2.6rem; margin-bottom: 28px;">Tokens, not words</h1>
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<!-- Screenshot image -->
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<figure style="max-width: 860px; width: 100%; margin: 0 auto;">
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<img
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src="../assets/llm/tokens.jpg"
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alt="Screenshot of the OpenAI tokenizer showing the sentence about BPE split into 32 tokens across 105 characters, with tabs for GPT-5.x, GPT-4, and GPT-3 tokenizers."
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style="width: 100%; border-radius: 12px; box-shadow: 0 4px 24px rgba(0,0,0,0.10);"
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/>
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<figcaption style="margin-top: 20px; font-size: 1rem; color: #555; font-style: italic; line-height: 1.5;">
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<strong style="font-style: normal; color: #1a1a1a;">105 characters → 32 tokens. Rule of thumb: ~4 chars per token in English.</strong><br/>
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Each model generation uses a different tokenizer — same text, different token count, different cost.
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</figcaption>
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</figure>
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</div>
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</div>
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<!-- ============================================================ -->
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<!-- SLIDE 11: Tokens In, Tokens Out — Full Picture -->
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<!-- ============================================================ -->
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<div class="slide" data-slide="11">
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<div style="display: flex; flex-direction: column; align-items: center; justify-content: center; min-height: calc(100vh - 120px); text-align: center; gap: 0;">
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<!-- Title -->
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<h1 style="border-bottom: none; padding-bottom: 0; font-size: 2.6rem; margin-bottom: 28px;">Tokens in, tokens out</h1>
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<!-- Animated SVG -->
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<figure style="max-width: 860px; width: 100%; margin: 0 auto;">
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<img
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src="../assets/llm/llm-advanced.svg"
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alt="Animated diagram combining tokenization and autoregressive generation: the BPE-tokenized prompt feeds into the LLM, which generates the answer token-by-token using the same shared vocabulary."
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style="width: 100%; border-radius: 12px; box-shadow: 0 4px 24px rgba(0,0,0,0.10);"
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/>
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<figcaption style="margin-top: 20px; font-size: 1rem; color: #555; font-style: italic; line-height: 1.5;">
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<strong style="font-style: normal; color: #1a1a1a;">Input and output share the same vocabulary — tokenization shapes what the model even “sees”.</strong><br/>
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“Anthropic” becomes “Anth” + “ropic” because that’s how it appears most often in training data.
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</figcaption>
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</figure>
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</div>
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</div>
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<!-- ============================================================ -->
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<!-- SLIDE 12: What the Model Actually Sees — Integer Token IDs -->
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<!-- ============================================================ -->
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<div class="slide" data-slide="12">
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<div style="display: flex; flex-direction: column; align-items: center; justify-content: center; min-height: calc(100vh - 120px); text-align: center; gap: 0;">
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<!-- Title -->
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<h1 style="border-bottom: none; padding-bottom: 0; font-size: 2.6rem; margin-bottom: 28px;">What the model actually sees</h1>
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<!-- Animated SVG — wider asset (1360×600 viewBox); use max-width 960px to fill the slide without overcrowding -->
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<figure style="max-width: 960px; width: 100%; margin: 0 auto;">
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<img
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src="../assets/llm/llm-animation-tokenids.svg"
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alt="Animated diagram showing the 32 integer token IDs the model receives: e.g. 28133 for 'Does', 17554 for ' Chat', 162016 for 'GPT', 97481 for ' Claude'. Generated tokens are also shown as IDs. Vocab size V ≈ 200,000."
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style="width: 100%; border-radius: 12px; box-shadow: 0 4px 24px rgba(0,0,0,0.10);"
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/>
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<figcaption style="margin-top: 20px; font-size: 1rem; color: #555; font-style: italic; line-height: 1.5;">
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<strong style="font-style: normal; color: #1a1a1a;">The model never reads text — it reads a sequence of integers, each one an index into a vocabulary of ~200,000 entries.</strong><br/>
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Notice the comma is always ID 11 — the same punctuation mark maps to the same integer, everywhere, every time.
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</figcaption>
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</figure>
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</div>
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</div>
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<!-- ============================================================ -->
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<!-- SLIDE 13: Models are stateless -->
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<!-- ============================================================ -->
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<div class="slide" data-slide="13">
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<div style="display: flex; flex-direction: column; align-items: center; justify-content: center; min-height: calc(100vh - 120px); text-align: center; gap: 0;">
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<!-- Title -->
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<h1 style="border-bottom: none; padding-bottom: 0; font-size: 2.4rem; margin-bottom: 32px;">💬 Models are stateless</h1>
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<!-- Dialog diagram — two-column conversation -->
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<div style="max-width: 700px; width: 100%; margin: 0 auto 28px;">
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<!-- Column headers -->
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<div style="display: flex; justify-content: space-between; margin-bottom: 14px; padding: 0 24px;">
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<span style="font-size: 0.85rem; font-weight: 700; text-transform: uppercase; letter-spacing: 0.08em; color: #1565c0; background: rgba(21,101,192,0.08); border: 1px solid rgba(21,101,192,0.2); padding: 4px 16px; border-radius: 999px;">User</span>
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<span style="font-size: 0.85rem; font-weight: 700; text-transform: uppercase; letter-spacing: 0.08em; color: #7b1fa2; background: rgba(123,31,162,0.08); border: 1px solid rgba(123,31,162,0.2); padding: 4px 16px; border-radius: 999px;">Model</span>
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</div>
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<!-- Turn 1: User → Model -->
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<div style="display: flex; justify-content: flex-start; margin-bottom: 10px;">
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<div style="background: #e3f2fd; border: 1px solid #90caf9; border-radius: 18px 18px 18px 4px; padding: 12px 18px; max-width: 62%; text-align: left; position: relative;">
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<span style="font-size: 1rem; color: #1a1a1a;">“My name is Shayan.”</span>
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<span style="display: block; font-size: 0.7rem; color: #888; margin-top: 4px; text-align: right;">➜ to model</span>
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</div>
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</div>
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<!-- Turn 2: Model → User -->
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<div style="display: flex; justify-content: flex-end; margin-bottom: 10px;">
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<div style="background: #f3e5f5; border: 1px solid #ce93d8; border-radius: 18px 18px 4px 18px; padding: 12px 18px; max-width: 62%; text-align: left; position: relative;">
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<span style="font-size: 1rem; color: #1a1a1a;">“Okay, your name is Shayan.”</span>
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<span style="display: block; font-size: 0.7rem; color: #888; margin-top: 4px;">➜ to user</span>
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</div>
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</div>
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<!-- Turn 3: User → Model -->
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<div style="display: flex; justify-content: flex-start; margin-bottom: 10px;">
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<div style="background: #e3f2fd; border: 1px solid #90caf9; border-radius: 18px 18px 18px 4px; padding: 12px 18px; max-width: 62%; text-align: left;">
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<span style="font-size: 1rem; color: #1a1a1a;">“What is my name?”</span>
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<span style="display: block; font-size: 0.7rem; color: #888; margin-top: 4px; text-align: right;">➜ to model</span>
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</div>
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</div>
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<!-- Turn 4: Model → User (can't remember) -->
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<div style="display: flex; justify-content: flex-end; margin-bottom: 0;">
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<div style="background: #fce4ec; border: 1px solid #f48fb1; border-radius: 18px 18px 4px 18px; padding: 12px 18px; max-width: 72%; text-align: left;">
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<span style="font-size: 1rem; color: #1a1a1a;">“I don’t know your name — I have no memory of what you just said.”</span>
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<span style="display: block; font-size: 0.7rem; color: #888; margin-top: 4px;">➜ to user</span>
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</div>
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</div>
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</div>
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<!-- Caption strip — mirrors slide-12 pattern -->
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<p style="font-size: 1.6rem; font-weight: 700; color: #1a1a1a; margin: 8px 0 4px; letter-spacing: -0.02em; line-height: 1.2;">Every turn is a fresh API call.</p>
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<p style="font-size: 1.1rem; font-weight: 400; color: #C0392B; margin: 0; letter-spacing: 0.01em;">Memory only exists if the harness replays the transcript.</p>
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</div>
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</div>
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<!-- ============================================================ -->
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<!-- SLIDE 14: "Stochastic Parrots" -->
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<div class="slide" data-slide="14">
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<!-- Headline -->
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<!-- Headline -->
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<div style="text-align: center; margin-bottom: 36px;">
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<div style="text-align: center; margin-bottom: 36px;">
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@@ -489,9 +648,9 @@
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</div>
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</div>
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<!-- ============================================================ -->
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<!-- ============================================================ -->
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<!-- SLIDE 10: Temperature = 0 ≠ Deterministic -->
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<!-- SLIDE 15: Temperature = 0 ≠ Deterministic -->
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<!-- ============================================================ -->
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<div class="slide" data-slide="10">
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<div class="slide" data-slide="15">
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<!-- Headline -->
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<div style="text-align: center; margin-bottom: 32px;">
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<div style="text-align: center; margin-bottom: 32px;">
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@@ -559,165 +718,6 @@
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</div>
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</div>
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<!-- ============================================================ -->
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<!-- SLIDE 11: How LLMs Generate Text — Autoregressive Loop -->
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<div class="slide" data-slide="11">
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<div style="display: flex; flex-direction: column; align-items: center; justify-content: center; min-height: calc(100vh - 120px); text-align: center; gap: 0;">
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<!-- Title -->
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<h1 style="border-bottom: none; padding-bottom: 0; font-size: 2.6rem; margin-bottom: 28px;">One token at a time</h1>
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<!-- Animated SVG -->
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<figure style="max-width: 860px; width: 100%; margin: 0 auto;">
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<img
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src="../assets/llm/llm-basic.svg"
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alt="Animated diagram showing autoregressive generation: prompt feeds into LLM, which predicts one token, feeds it back, and repeats until the full answer is produced."
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style="width: 100%; border-radius: 12px; box-shadow: 0 4px 24px rgba(0,0,0,0.10);"
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/>
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<figcaption style="margin-top: 20px; font-size: 1rem; color: #555; font-style: italic; line-height: 1.5;">
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<strong style="font-style: normal; color: #1a1a1a;">The model produces one token per inference, feeding each result back as new input.</strong><br/>
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This is why streaming feels gradual — and why longer outputs cost more in both latency and API spend.
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</figcaption>
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</figure>
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</div>
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</div>
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<!-- ============================================================ -->
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<!-- SLIDE 12: What's a Token? -->
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<div class="slide" data-slide="12">
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<div style="display: flex; flex-direction: column; align-items: center; justify-content: center; min-height: calc(100vh - 120px); text-align: center; gap: 0;">
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<!-- Title -->
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<h1 style="border-bottom: none; padding-bottom: 0; font-size: 2.6rem; margin-bottom: 28px;">Tokens, not words</h1>
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<!-- Screenshot image -->
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<figure style="max-width: 860px; width: 100%; margin: 0 auto;">
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<img
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src="../assets/llm/tokens.jpg"
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alt="Screenshot of the OpenAI tokenizer showing the sentence about BPE split into 32 tokens across 105 characters, with tabs for GPT-5.x, GPT-4, and GPT-3 tokenizers."
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style="width: 100%; border-radius: 12px; box-shadow: 0 4px 24px rgba(0,0,0,0.10);"
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/>
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<figcaption style="margin-top: 20px; font-size: 1rem; color: #555; font-style: italic; line-height: 1.5;">
|
|
||||||
<strong style="font-style: normal; color: #1a1a1a;">105 characters → 32 tokens. Rule of thumb: ~4 chars per token in English.</strong><br/>
|
|
||||||
Each model generation uses a different tokenizer — same text, different token count, different cost.
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</figcaption>
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</figure>
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</div>
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</div>
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<!-- ============================================================ -->
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<!-- SLIDE 13: Tokens In, Tokens Out — Full Picture -->
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<!-- ============================================================ -->
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<div class="slide" data-slide="13">
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<div style="display: flex; flex-direction: column; align-items: center; justify-content: center; min-height: calc(100vh - 120px); text-align: center; gap: 0;">
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||||||
<!-- Title -->
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<h1 style="border-bottom: none; padding-bottom: 0; font-size: 2.6rem; margin-bottom: 28px;">Tokens in, tokens out</h1>
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<!-- Animated SVG -->
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<figure style="max-width: 860px; width: 100%; margin: 0 auto;">
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<img
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||||||
src="../assets/llm/llm-advanced.svg"
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alt="Animated diagram combining tokenization and autoregressive generation: the BPE-tokenized prompt feeds into the LLM, which generates the answer token-by-token using the same shared vocabulary."
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style="width: 100%; border-radius: 12px; box-shadow: 0 4px 24px rgba(0,0,0,0.10);"
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/>
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<figcaption style="margin-top: 20px; font-size: 1rem; color: #555; font-style: italic; line-height: 1.5;">
|
|
||||||
<strong style="font-style: normal; color: #1a1a1a;">Input and output share the same vocabulary — tokenization shapes what the model even “sees”.</strong><br/>
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“Anthropic” becomes “Anth” + “ropic” because that’s how it appears most often in training data.
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</figcaption>
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</figure>
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</div>
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</div>
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<!-- ============================================================ -->
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<!-- SLIDE 14: What the Model Actually Sees — Integer Token IDs -->
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<!-- ============================================================ -->
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<div class="slide" data-slide="14">
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<div style="display: flex; flex-direction: column; align-items: center; justify-content: center; min-height: calc(100vh - 120px); text-align: center; gap: 0;">
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||||||
<!-- Title -->
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||||||
<h1 style="border-bottom: none; padding-bottom: 0; font-size: 2.6rem; margin-bottom: 28px;">What the model actually sees</h1>
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||||||
<!-- Animated SVG — wider asset (1360×600 viewBox); use max-width 960px to fill the slide without overcrowding -->
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<figure style="max-width: 960px; width: 100%; margin: 0 auto;">
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||||||
<img
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||||||
src="../assets/llm/llm-animation-tokenids.svg"
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alt="Animated diagram showing the 32 integer token IDs the model receives: e.g. 28133 for 'Does', 17554 for ' Chat', 162016 for 'GPT', 97481 for ' Claude'. Generated tokens are also shown as IDs. Vocab size V ≈ 200,000."
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style="width: 100%; border-radius: 12px; box-shadow: 0 4px 24px rgba(0,0,0,0.10);"
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/>
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<figcaption style="margin-top: 20px; font-size: 1rem; color: #555; font-style: italic; line-height: 1.5;">
|
|
||||||
<strong style="font-style: normal; color: #1a1a1a;">The model never reads text — it reads a sequence of integers, each one an index into a vocabulary of ~200,000 entries.</strong><br/>
|
|
||||||
Notice the comma is always ID 11 — the same punctuation mark maps to the same integer, everywhere, every time.
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</figcaption>
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</figure>
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</div>
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</div>
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<!-- ============================================================ -->
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<!-- SLIDE 15: Models are stateless -->
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<!-- ============================================================ -->
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|
||||||
<div class="slide" data-slide="15">
|
|
||||||
<div style="display: flex; flex-direction: column; align-items: center; justify-content: center; min-height: calc(100vh - 120px); text-align: center; gap: 0;">
|
|
||||||
|
|
||||||
<!-- Title -->
|
|
||||||
<h1 style="border-bottom: none; padding-bottom: 0; font-size: 2.4rem; margin-bottom: 32px;">💬 Models are stateless</h1>
|
|
||||||
|
|
||||||
<!-- Dialog diagram — two-column conversation -->
|
|
||||||
<div style="max-width: 700px; width: 100%; margin: 0 auto 28px;">
|
|
||||||
|
|
||||||
<!-- Column headers -->
|
|
||||||
<div style="display: flex; justify-content: space-between; margin-bottom: 14px; padding: 0 24px;">
|
|
||||||
<span style="font-size: 0.85rem; font-weight: 700; text-transform: uppercase; letter-spacing: 0.08em; color: #1565c0; background: rgba(21,101,192,0.08); border: 1px solid rgba(21,101,192,0.2); padding: 4px 16px; border-radius: 999px;">User</span>
|
|
||||||
<span style="font-size: 0.85rem; font-weight: 700; text-transform: uppercase; letter-spacing: 0.08em; color: #7b1fa2; background: rgba(123,31,162,0.08); border: 1px solid rgba(123,31,162,0.2); padding: 4px 16px; border-radius: 999px;">Model</span>
|
|
||||||
</div>
|
|
||||||
|
|
||||||
<!-- Turn 1: User → Model -->
|
|
||||||
<div style="display: flex; justify-content: flex-start; margin-bottom: 10px;">
|
|
||||||
<div style="background: #e3f2fd; border: 1px solid #90caf9; border-radius: 18px 18px 18px 4px; padding: 12px 18px; max-width: 62%; text-align: left; position: relative;">
|
|
||||||
<span style="font-size: 1rem; color: #1a1a1a;">“My name is Shayan.”</span>
|
|
||||||
<span style="display: block; font-size: 0.7rem; color: #888; margin-top: 4px; text-align: right;">➜ to model</span>
|
|
||||||
</div>
|
|
||||||
</div>
|
|
||||||
|
|
||||||
<!-- Turn 2: Model → User -->
|
|
||||||
<div style="display: flex; justify-content: flex-end; margin-bottom: 10px;">
|
|
||||||
<div style="background: #f3e5f5; border: 1px solid #ce93d8; border-radius: 18px 18px 4px 18px; padding: 12px 18px; max-width: 62%; text-align: left; position: relative;">
|
|
||||||
<span style="font-size: 1rem; color: #1a1a1a;">“Okay, your name is Shayan.”</span>
|
|
||||||
<span style="display: block; font-size: 0.7rem; color: #888; margin-top: 4px;">➜ to user</span>
|
|
||||||
</div>
|
|
||||||
</div>
|
|
||||||
|
|
||||||
<!-- Turn 3: User → Model -->
|
|
||||||
<div style="display: flex; justify-content: flex-start; margin-bottom: 10px;">
|
|
||||||
<div style="background: #e3f2fd; border: 1px solid #90caf9; border-radius: 18px 18px 18px 4px; padding: 12px 18px; max-width: 62%; text-align: left;">
|
|
||||||
<span style="font-size: 1rem; color: #1a1a1a;">“What is my name?”</span>
|
|
||||||
<span style="display: block; font-size: 0.7rem; color: #888; margin-top: 4px; text-align: right;">➜ to model</span>
|
|
||||||
</div>
|
|
||||||
</div>
|
|
||||||
|
|
||||||
<!-- Turn 4: Model → User (can't remember) -->
|
|
||||||
<div style="display: flex; justify-content: flex-end; margin-bottom: 0;">
|
|
||||||
<div style="background: #fce4ec; border: 1px solid #f48fb1; border-radius: 18px 18px 4px 18px; padding: 12px 18px; max-width: 72%; text-align: left;">
|
|
||||||
<span style="font-size: 1rem; color: #1a1a1a;">“I don’t know your name — I have no memory of what you just said.”</span>
|
|
||||||
<span style="display: block; font-size: 0.7rem; color: #888; margin-top: 4px;">➜ to user</span>
|
|
||||||
</div>
|
|
||||||
</div>
|
|
||||||
|
|
||||||
</div>
|
|
||||||
|
|
||||||
<!-- Caption strip — mirrors slide-12 pattern -->
|
|
||||||
<p style="font-size: 1.6rem; font-weight: 700; color: #1a1a1a; margin: 8px 0 4px; letter-spacing: -0.02em; line-height: 1.2;">Every turn is a fresh API call.</p>
|
|
||||||
<p style="font-size: 1.1rem; font-weight: 400; color: #C0392B; margin: 0; letter-spacing: 0.01em;">Memory only exists if the harness replays the transcript.</p>
|
|
||||||
|
|
||||||
</div>
|
|
||||||
</div>
|
|
||||||
|
|
||||||
<!-- ============================================================ -->
|
<!-- ============================================================ -->
|
||||||
<!-- SLIDE 16: Model Limitations — Real-time access -->
|
<!-- SLIDE 16: Model Limitations — Real-time access -->
|
||||||
<!-- ============================================================ -->
|
<!-- ============================================================ -->
|
||||||
|
|||||||
Reference in New Issue
Block a user