<story><title>The auction that set off the race for AI supremacy</title><url>https://www.wired.com/story/secret-auction-race-ai-supremacy-google-microsoft-baidu/</url></story><parent_chain></parent_chain><comment><author>kortilla</author><text>&amp;gt; As Google and other tech giants adopted the technology, no one quite realized it was learning the biases of the researchers who built it.&lt;p&gt;Woah, this came out of nowhere and it’s completely wrong. The problem isn’t that deep learning is picking up biases of the researchers, it’s that it picks up biases from the training data.</text></comment>
<story><title>The auction that set off the race for AI supremacy</title><url>https://www.wired.com/story/secret-auction-race-ai-supremacy-google-microsoft-baidu/</url></story><parent_chain></parent_chain><comment><author>dfox</author><text>&amp;quot;The idea of a neural network dated back to the 1950s, but the early pioneers had never gotten it working as well as they’d hoped. By the new millennium, most researchers had given up on the idea, convinced it was a technological dead end and bewildered by the 50- year- old conceit that these mathematical systems somehow mimicked the human brain.&amp;quot;&lt;p&gt;This is not only false, but in the context actually intentional misrepresentation. Most of the issues with the model was solved by introduction of hidden layers and backpropagation learning, which is at least in my opinion required knowledge in CS since at least early 90&amp;#x27;s and probably earlier (it is not clear when the idea was formulated in usable form, put the most cited publications are from late 80&amp;#x27;s, eg. Rumelhart, D., Hinton, G. &amp;amp; Williams, R. Learning representations by back-propagating errors. Nature 323, 533–536 (1986). &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;doi.org&amp;#x2F;10.1038&amp;#x2F;323533a0&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;doi.org&amp;#x2F;10.1038&amp;#x2F;323533a0&lt;/a&gt;).&lt;p&gt;On the other hand obviously more complex modern approaches to the &amp;quot;throw bunch of poorly understood linear algebra at he problem&amp;quot; problem have value and there is definitive generational shift in the current &amp;quot;AI-anti-winter&amp;quot; (for lack of better word), but still...</text></comment>