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Energy consumption comparison in machine learning platforms

11 pointsby adrianomartinsover 2 years ago

2 comments

sva_over 2 years ago
Alright, so the more I&#x27;m looking into this website, the weirder it becomes. Never mind even talking about the pricing model.<p>Clicking on their blog, the first entry is<p>&gt; &quot;How are variables in the dataset for machine learning?&quot;[0]<p>That doesn&#x27;t even seem like a valid English sentence to me.<p>Searching the sentences from the text will send you to various sources from which they were taken without being given credit.<p>In fact you can find plenty of sites who are seemingly recycling the the same sentences used in this blog. It&#x27;s pretty bizarre.<p>[0] <a href="https:&#x2F;&#x2F;www.neuraldesigner.com&#x2F;blog&#x2F;type-uses-variables" rel="nofollow">https:&#x2F;&#x2F;www.neuraldesigner.com&#x2F;blog&#x2F;type-uses-variables</a>
sva_over 2 years ago
&gt; TF [...] The final mean squared error is 0.0003.<p>&gt; Neural Designer [...] reaches a mean squared error of 0.023.<p>&gt; The following table summarizes the the[sic] <i>most important metrics</i> that the two machine learning platforms yielded .<p>[omits MSE]<p>They should train both to the same loss and then compare.
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