<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>southernplaces7</author><text>Nothing about current AI models profoundly challenges the unknowns of what makes consciousness work in any mystery-resolving way. People who confuse plainly programmed algorithmic systems like GPT 4 or Midjourney with the still unresolved issues of sentience as we know it so far are drinking far too much of the current batch of AI punch. Sadly, it&amp;#x27;s a sentiment I see all too often on HN, a site in which i&amp;#x27;d assume most readers and commentators would be a bit more skeptical-minded about these things. It&amp;#x27;s almost funny, considering how much hate this site tends to throw at things like crypto, to see so much of the wide-eyed opposite with the latest AI craze.</text><parent_chain><item><author>MrScruff</author><text>Obviously AI academics are uniquely challenged by the &amp;#x27;scaling is (nearly) everything&amp;#x27; reality, but I feel like a lot of the mixed emotions being expressed towards the latest results are also because we&amp;#x27;re actually seeing the mystery of self starting to unravel. Like any good mystery, the fun was in the build up and as we move towards a resolution there&amp;#x27;s a bitter sweet aspect to the slightly mundane reality of it &amp;#x27;merely&amp;#x27; being an emergent property of large networks. Of course, any rational person might have expected this given how the one working example came into existence. In general it all looks like a pretty resounding endorsement of the David Chalmers position to me.</text></item></parent_chain></comment><story><title>Choose Your Weapon: Survival Strategies for Depressed AI Academics</title><url>https://arxiv.org/abs/2304.06035</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>hakuseki</author><text>&amp;gt; Like any good mystery, the fun was in the build up and as we move towards a resolution there&amp;#x27;s a bitter sweet aspect to the slightly mundane reality of it &amp;#x27;merely&amp;#x27; being an emergent property of large networks.&lt;p&gt;I would disagree with this description. An &amp;quot;emergent property of large networks&amp;quot; would be something that just appears when you wire together a large network.&lt;p&gt;To get intelligent behavior, it&amp;#x27;s not sufficient to wire together a large neural network. You also need to use an optimizer to train it on a large data set.</text><parent_chain><item><author>MrScruff</author><text>Obviously AI academics are uniquely challenged by the &amp;#x27;scaling is (nearly) everything&amp;#x27; reality, but I feel like a lot of the mixed emotions being expressed towards the latest results are also because we&amp;#x27;re actually seeing the mystery of self starting to unravel. Like any good mystery, the fun was in the build up and as we move towards a resolution there&amp;#x27;s a bitter sweet aspect to the slightly mundane reality of it &amp;#x27;merely&amp;#x27; being an emergent property of large networks. Of course, any rational person might have expected this given how the one working example came into existence. In general it all looks like a pretty resounding endorsement of the David Chalmers position to me.</text></item></parent_chain></comment><story><title>Choose Your Weapon: Survival Strategies for Depressed AI Academics</title><url>https://arxiv.org/abs/2304.06035</url></story>