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title: Scale — deep learning to foundation models
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description: A short video explanation of Scale — deep learning to foundation models.
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    <div class="s5-video-watch__crumbs"><a href="https://5sigmas.com/en/videos/">All videos</a><span>History of AI</span><span>1:03</span></div>
    <h1>Scale — deep learning to foundation models</h1><p>A short video explanation of Scale — deep learning to foundation models.</p>
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    <div class="s5-video-watch__section-head"><span class="s5-eyebrow">Video summary</span><h2 id="video-summary-title">The ideas to retain</h2></div>
    <div class="s5-video-watch__snippet-grid"><article><span>01</span><h2>1. 2012: when scale stopped being a detail</h2><p>AlexNet won ILSVRC 2012 with a result that changed the field&#x27;s perception: 15.3% top-5 error versus 26.2% for the runner-up. The system was trained on 1.2 million images using two GTX 580…</p></article>
<article><span>02</span><h2>2. The Transformer and massive pretraining</h2><p>The next major shift arrived with Attention Is All You Need in 2017. The Transformer was not merely another language architecture. It reorganized the problem around attention mechanisms,…</p></article>
<article><span>03</span><h2>3. Scale became a methodology</h2><p>The idea that performance improves relatively predictably as parameters, data and compute increase did not originate with LLMs, but LLMs made it central. Work such as Deep Learning Scaling…</p></article></div>
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  <aside class="s5-video-watch__source"><div><span class="s5-eyebrow">Context and evidence</span><h2>Continue with the full article</h2><p>The chapter develops the mechanism, primary sources, limitations and connections to the rest of the series.</p></div><a class="s5-video-watch__source-link" href="https://5sigmas.com/en/series/from-cave-to-agi/04-escalar/">Read the article →</a></aside>
  <section class="s5-video-watch__related" aria-labelledby="related-videos-title"><div class="s5-video-watch__section-head"><span class="s5-eyebrow">Next step</span><h2 id="related-videos-title">Related videos</h2></div><div class="s5-video-watch__related-grid"><article><a href="https://5sigmas.com/en/videos/series/from-cave-to-agi/05-mas-alla/"><img src="https://5sigmas.com/en/series/from-cave-to-agi/05-mas-alla.jpg" alt="" loading="lazy" width="1280" height="720"><span>History of AI · 1:03</span><strong>Beyond the Transformer</strong></a></article>
<article><a href="https://5sigmas.com/en/videos/series/from-cave-to-agi/03-aprender/"><img src="https://5sigmas.com/en/series/from-cave-to-agi/03-aprender.jpg" alt="" loading="lazy" width="1280" height="720"><span>History of AI · 1:03</span><strong>Learn — from rules to data</strong></a></article>
<article><a href="https://5sigmas.com/en/videos/series/from-cave-to-agi/02-mecanizar/"><img src="https://5sigmas.com/en/series/from-cave-to-agi/02-mecanizar.jpg" alt="" loading="lazy" width="1280" height="720"><span>History of AI · 1:03</span><strong>Mechanize — from calculation to computing</strong></a></article></div></section>
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