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Five standalone HTML visuals covering the RSA pipeline, training pipeline, gate decomposition, dataset anatomy, and model tier sizing. Slide deck brief describing a 35-slide two-act deck for a data science audience. Handoff note documenting what was created this session. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
136 lines
6.9 KiB
HTML
136 lines
6.9 KiB
HTML
<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<title>Model Tiers</title>
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<style>
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* { box-sizing: border-box; margin: 0; padding: 0; }
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body { background: #0f1117; font-family: 'Segoe UI', system-ui, sans-serif; display: flex; align-items: center; justify-content: center; min-height: 100vh; }
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.slide { width: 960px; padding: 56px 72px; }
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h2 { color: #e2e8f0; font-size: 1.5rem; font-weight: 400; letter-spacing: 0.05em; text-transform: uppercase; margin-bottom: 8px; text-align: center; }
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.subtitle { text-align: center; color: #6b7280; font-size: 0.88rem; margin-bottom: 48px; }
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.tiers { display: flex; align-items: flex-end; gap: 20px; margin-bottom: 40px; }
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.tier { flex: 1; border-radius: 10px 10px 0 0; display: flex; flex-direction: column; justify-content: flex-end; position: relative; }
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.tier-inner { padding: 20px 16px 24px; border-radius: 10px; border: 1.5px solid; }
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.tier.det .tier-inner { background: #0d1f16; border-color: #22c55e; }
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.tier.tiny .tier-inner { background: #0c1a30; border-color: #3b82f6; }
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.tier.med .tier-inner { background: #12122a; border-color: #8b5cf6; }
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.tier.large .tier-inner { background: #2a1100; border-color: #f59e0b; }
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.tier.llm .tier-inner { background: #2a0f0f; border-color: #ef4444; }
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.tier-badge { font-size: 0.62rem; letter-spacing: 0.14em; text-transform: uppercase; font-weight: 700; margin-bottom: 8px; }
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.det .tier-badge { color: #4ade80; }
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.tiny .tier-badge { color: #60a5fa; }
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.med .tier-badge { color: #a78bfa; }
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.large .tier-badge { color: #fbbf24; }
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.llm .tier-badge { color: #f87171; }
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.tier-name { font-size: 0.95rem; font-weight: 600; color: #e2e8f0; margin-bottom: 10px; line-height: 1.3; }
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.tier-params { font-size: 0.8rem; margin-bottom: 8px; font-weight: 600; }
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.det .tier-params { color: #4ade80; }
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.tiny .tier-params { color: #60a5fa; }
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.med .tier-params { color: #a78bfa; }
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.large .tier-params { color: #fbbf24; }
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.llm .tier-params { color: #f87171; }
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.tier-detail { font-size: 0.76rem; color: #6b7280; line-height: 1.5; }
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.marker { position: absolute; top: -32px; left: 50%; transform: translateX(-50%); white-space: nowrap; font-size: 0.7rem; color: #4ade80; background: #052e16; border: 1px solid #166534; padding: 3px 10px; border-radius: 20px; }
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.marker.current { color: #60a5fa; background: #0c1a30; border-color: #1e3a5f; }
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.axis { display: flex; align-items: center; margin-bottom: 8px; }
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.axis-line { flex: 1; height: 2px; background: linear-gradient(90deg, #22c55e, #3b82f6, #8b5cf6, #f59e0b, #ef4444); border-radius: 1px; }
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.axis-label-left { font-size: 0.7rem; color: #4ade80; margin-right: 12px; white-space: nowrap; }
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.axis-label-right { font-size: 0.7rem; color: #ef4444; margin-left: 12px; white-space: nowrap; }
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.axis-labels { display: flex; justify-content: space-between; margin-bottom: 32px; }
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.axis-labels span { font-size: 0.7rem; color: #4a5568; }
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.hypothesis { background: #1a1f2e; border: 1px solid #2d3748; border-radius: 10px; padding: 24px 28px; }
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.hyp-title { font-size: 0.65rem; letter-spacing: 0.12em; text-transform: uppercase; color: #6b7280; margin-bottom: 12px; }
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.hyp-rule { font-size: 0.88rem; color: #94a3b8; line-height: 1.8; font-family: 'Courier New', monospace; }
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.hyp-rule .dim { color: #4a5568; }
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.hyp-rule .hi { color: #22d3ee; font-weight: 600; }
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.hyp-rule .note { color: #6b7280; font-family: 'Segoe UI', sans-serif; font-size: 0.8rem; margin-top: 10px; display: block; font-style: italic; }
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</style>
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</head>
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<body>
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<div class="slide">
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<h2>Entropy → Model Tier</h2>
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<div class="subtitle">The smallest model that clears the quality target for a given gate's entropy budget</div>
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<div class="tiers">
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<div class="tier det" style="position:relative;">
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<div class="marker">← already valid</div>
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<div class="tier-inner">
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<div class="tier-badge">Tier 0</div>
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<div class="tier-name">Deterministic Rules</div>
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<div class="tier-params">0 params</div>
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<div class="tier-detail">Perfect when input–output mapping is explicit and stable. No training cost. Fully auditable.</div>
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</div>
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</div>
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<div class="tier tiny" style="position:relative;">
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<div class="marker current">← trained baseline</div>
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<div class="tier-inner">
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<div class="tier-badge">Tier 1 · current</div>
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<div class="tier-name">Tiny Specialist (Fabricate)</div>
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<div class="tier-params">~213K params · ~800KB</div>
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<div class="tier-detail">Binary/multiclass classifiers. Local, fast, inspectable. Target for bounded gates with sufficient entropy.</div>
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</div>
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</div>
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<div class="tier med">
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<div class="tier-inner">
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<div class="tier-badge">Tier 2 · planned</div>
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<div class="tier-name">Medium Specialist</div>
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<div class="tier-params">~10× tier 1 · ~2–3M params</div>
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<div class="tier-detail">For gates where tiny tier misses due to higher label boundary fuzziness or longer context dependence.</div>
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</div>
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</div>
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<div class="tier large">
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<div class="tier-inner">
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<div class="tier-badge">Tier 3 · planned</div>
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<div class="tier-name">Large Specialist</div>
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<div class="tier-params">~16× tier 1 · ~3–4M params</div>
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<div class="tier-detail">For gates with high lexical variation, world-knowledge dependence, or complex slot interdependence.</div>
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</div>
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</div>
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<div class="tier llm">
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<div class="tier-inner">
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<div class="tier-badge">Tier 4 · escalation</div>
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<div class="tier-name">SLM / LLM</div>
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<div class="tier-params">billions of params</div>
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<div class="tier-detail">Only when the gate is genuinely open-ended. Not a default. Escalation when specialists abstain.</div>
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</div>
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</div>
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</div>
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<div class="axis">
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<span class="axis-label-left">low entropy</span>
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<div class="axis-line"></div>
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<span class="axis-label-right">high entropy</span>
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</div>
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<div class="axis-labels">
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<span>simple lookup</span>
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<span>binary classification</span>
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<span>slot filling</span>
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<span>complex routing</span>
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<span>open reasoning</span>
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</div>
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<div class="hypothesis">
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<div class="hyp-title">Current sizing hypothesis</div>
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<div class="hyp-rule">
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<span class="dim">if</span> entropy <span class="hi"><= A</span> <span class="dim">→</span> deterministic<br>
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<span class="dim">if</span> entropy <span class="hi"><= B</span> <span class="dim">→</span> tiny specialist (~213K params)<br>
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<span class="dim">if</span> entropy <span class="hi"><= C</span> <span class="dim">→</span> medium specialist (~2–3M params)<br>
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<span class="dim">if</span> entropy <span class="hi">> C</span> <span class="dim">→</span> large specialist or escalate to SLM/LLM
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<span class="note">Before moving up a tier: check schema, label set, missing context, and factorization options first.</span>
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</div>
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</div>
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</div>
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</body>
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</html>
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