And yet It Understands
&gt;I was a deep learning skeptic. I doubted that you could get to intelligence by matrix multiplication for the same reason you can’t get to the Moon by piling up chairs<p>I&#x27;ve always been fascinated by this example. I&#x27;ve also heard it referred to as climbing a tree won&#x27;t get you to the Moon.<p>Because, for some reason, people think that&#x27;s an argument <i>against</i> the possibility of getting to the Moon when it&#x27;s actually a profound insight in favor of that possibility. If you know that piling chairs gets you closer to the moon, you know that the nature of space between you and the Moon is that it&#x27;s traversible.<p>A criticism that would make more sense would be something along the lines of &quot;piling up colors you won&#x27;t get you any closer to the Moon&quot;, since colors aren&#x27;t even the right kind of thing, and you can&#x27;t aggregate them in a way that gets you spatially closer. Because that at least does not concede the fundamental relationship of spatial traverseability.<p>It&#x27;s also an inadvertently helpful example because it exposes the ways in which people confuse the practical limits of logistics for fundamental principles of reality. And I think that&#x27;s always been a difficulty for me, whenever I encounter these criticisms of what is possible with computer learning, because it seems like it&#x27;s hard to ever suss out whether a person&#x27;s talking about a practical difficulty or an absolute principle.