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<figure class="wp-block-image"><img src="https://buzz-caribbean.com/app/uploads/2019/07/machine-learning-demo.jpeg" alt="" class="wp-image-946" /><figcaption>Artist's impression of artificial intelligence (Photo contributed: HackerNoon.com)</figcaption></figure>
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<p>Armed with just the language of thousands of research papers, machine learning (ML) has been credited with discoveries never made by human scientists.</p>
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<figure class="wp-block-image"><img src="https://buzz-caribbean.com/app/uploads/2019/08/scientists-buzz-demo-1024x683.jpg" alt="" class="wp-image-3482" /><figcaption>A scientist hard at work in a laboratory (Photo contributed: Pexels.com)</figcaption></figure>
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<p>The discoveries were&nbsp;<a href="https://www.nature.com/articles/s41586-019-1335-8.epdf?referrer_access_token=xnIXloemAjCocfXIt9dQ49RgN0jAjWel9jnR3ZoTv0P9QxlcO86f_GXZRxwYijrqa11Mx55SgniZXv55YKOR_sn816NK2x0O46Vim16XrS-SjyP9GMXeDQinUN75ES6enlxK__J5UabR6JdgR19bZSVLL5ZsK8146qMcipEbItW65C8aSk29Q_BfrKz4Gb5-kjz3m7dIaoRxs3e1I6qW4022QZ6aZMaOPxlATK7OOqj8lrhj-yufvROMPdStMZjAEK-efja6SfW5n-6xhZuV33BrlHdxmu8yxCQg-Mpomv4_WY2o4OqyFsbpNr_j-R-9&amp;tracking_referrer=www.vice.com" target="_blank" rel="noreferrer noopener">publicised on July 3</a>,
after researchers from the Lawrence Berkeley National Laboratory in California
used an algorithm,&nbsp;<em>Word2Vec</em>, to sift through scientific papers.</p>
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<p>The researchers were hoping the ML would make connections humans had missed – and it found them!</p>
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<p>In the study, the algorithm processed&nbsp;a vocabulary of about
500,000 words related to material science&nbsp;– spitting out predictions for
possible thermoelectric materials, which convert heat to energy and are used in
many heating and cooling applications.</p>
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<figure class="wp-block-image"><img src="https://buzz-caribbean.com/app/uploads/2019/08/coding-closeup-buzz-demo-1024x683.jpg" alt="" class="wp-image-3483" /><figcaption>(Photo contributed: Pexels.com)</figcaption></figure>
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<p>The most impressive part of the study was the algorithm didn’t
know the definition of ‘thermoelectric’ and received no training in materials
science.&nbsp;<strong><em>Mind. Blown.</em></strong></p>
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<p>Using only word associations, the algorithm was able to provide
candidates for future thermoelectric materials, some of which may be better
than those humankind currently uses.</p>
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<figure class="wp-block-image"><img src="https://buzz-caribbean.com/app/uploads/2019/08/metal-sparks-buzz-demo.jpg" alt="" class="wp-image-3485" /><figcaption>(Photo contributed: Pexels.com)</figcaption></figure>
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<p>It’s a very promising prospect for the future of heating and
cooling systems as the algorithm was able to understand complex concepts such
as the periodic table and the chemical structure of molecules.</p>
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<p>According to the study, published in Nature, in some cases,
words were linked to thermoelectric concepts but had never been written about
as ‘thermoelectric’ in any abstract they surveyed.</p>
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<p><em>How cool is that!</em></p>
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<p>Okay, so not quite <strong><em>Skynet</em></strong>, but the discoveries made by the algorithm were significant, as this gap in knowledge is hard to catch with a human eye, but easy for an ML to spot.</p>
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<p>Here's to the future <strong>BUZZhive</strong>! </p>
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<p>What do you think of these latest developments? Leave your thoughts in the comments below!</p>
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