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49 lines
2.4 KiB
HTML
49 lines
2.4 KiB
HTML
<!DOCTYPE html>
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<html>
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<head><style>
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html { background: #FFFFFF; }
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body { width: 720pt; height: 405pt; margin: 0; padding: 0; background: #FAFAFF; font-family: Arial, sans-serif; display: flex; }
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.bar { width: 10pt; background: #4338CA; }
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.wrap { width: 644pt; margin: 26pt 32pt 22pt 34pt; display: flex; flex-direction: column; }
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.kicker { font-size: 9.5pt; color: #7C3AED; font-weight: bold; letter-spacing: 2pt; margin: 0 0 4pt 0; }
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h1 { font-size: 23pt; color: #1A1633; margin: 0 0 8pt 0; }
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.rule { background: #F59E0B; height: 3pt; width: 60pt; margin: 0 0 16pt 0; }
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.cards { display: flex; }
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.card { width: 198pt; margin-right: 14pt; background: #4338CA; border-radius: 10pt; padding: 14pt 14pt 16pt 14pt; }
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.card p { margin: 0; }
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.ct { font-size: 13pt; color: #FFFFFF; font-weight: bold; margin: 0 0 6pt 0; }
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.cd { font-size: 9.5pt; color: #DDD6FE; line-height: 1.35; }
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ul { margin: 16pt 0 0 0; padding-left: 14pt; font-size: 11pt; color: #2A2740; line-height: 1.4; }
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li { margin-bottom: 8pt; }
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.foot { font-size: 8pt; color: #8A86A3; margin-top: auto; margin-bottom: 0; }
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</style></head>
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<body>
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<div class="bar"></div>
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<div class="wrap">
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<p class="kicker">02 · KEY IDEA</p>
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<h1>The Transformer: Attention Is All You Need</h1>
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<div class="rule"></div>
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<div class="cards">
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<div class="card">
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<p class="ct">No Recurrence</p>
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<p class="cd">Sequential RNN hidden states are removed entirely — positions are processed in parallel.</p>
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</div>
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<div class="card">
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<p class="ct">No Convolution</p>
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<p class="cd">No fixed-width kernels; every position can connect to every other position directly.</p>
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</div>
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<div class="card" style="margin-right: 0;">
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<p class="ct">Self-Attention Only</p>
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<p class="cd">Multi-headed self-attention computes all representations, in both encoder and decoder.</p>
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</div>
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</div>
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<ul>
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<li>First sequence transduction model based <b>entirely on attention</b>, replacing recurrent layers with multi-headed self-attention.</li>
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<li>Highly parallelizable — reaches a new state of the art in translation with a <b>fraction of the training cost</b>.</li>
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<li>Generalizes beyond translation (e.g., English constituency parsing) and yields interpretable attention patterns.</li>
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</ul>
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<p class="foot">Source: Vaswani et al., Abstract and §1 (paper p. 1–2).</p>
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</div>
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</body>
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</html>
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