<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>userbinator</author><text>Procedural generation is something the demoscene has essentially specialised in for several decades, but I see no mention of it in the article. The demoscene has also done so using several orders of magnitude less computing resources than mentioned here, so I think everyone else has a lot to learn from them.&lt;p&gt;Here&amp;#x27;s a memorable intro, from 2009: &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;news.ycombinator.com&amp;#x2F;item?id=31636482&quot;&gt;https:&amp;#x2F;&amp;#x2F;news.ycombinator.com&amp;#x2F;item?id=31636482&lt;/a&gt;&lt;p&gt;Earlier than that, another famous 64k from 2000:&lt;p&gt;&lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;www.theproduct.de&amp;#x2F;index.html&quot; rel=&quot;nofollow noreferrer&quot;&gt;http:&amp;#x2F;&amp;#x2F;www.theproduct.de&amp;#x2F;index.html&lt;/a&gt;</text><parent_chain></parent_chain></comment><story><title>Infinite Photorealistic Worlds Using Procedural Generation</title><url>https://arxiv.org/abs/2306.09310</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>avaer</author><text>I ran this for most of today in the background and I have some thoughts:&lt;p&gt;The quality is good and it&amp;#x27;s giving you all of the maps (as well as the .blends!). It seems great for its stated goal of generating ground truth for training.&lt;p&gt;However, it&amp;#x27;s very slow&amp;#x2F;CPU bound (go get lunch) so probably doesn&amp;#x27;t make sense for applications with users behind the computer in the current state.&lt;p&gt;Additionally, the .blend files are so unoptimized that you can&amp;#x27;t even edit them on a laptop with texturing on. The larger generations will OOM a single run on a reasonably beefy server. To be fair, these warnings are in the documentation.&lt;p&gt;With some optimization (of the output) you could probably do some cool things with the resulting assets, but I would agree with the authors the best use case is where you need a full image set (diffuse, depth, segmentation) for training, where you can run this for a week on a cluster.&lt;p&gt;To hype this up as No Man&amp;#x27;s Sky is a stretch (NMS is a marvel in its own right, but has a completely different set of tradeoffs).&lt;p&gt;EDIT: Although there are configuration files you can use to create your own &amp;quot;biomes&amp;quot;, there is no easy way to control this with an LLM. Maybe you might be able to hack GPT-4 functions to get the right format for it to be accepted, but I wouldn&amp;#x27;t expect great results from that technique.</text><parent_chain></parent_chain></comment><story><title>Infinite Photorealistic Worlds Using Procedural Generation</title><url>https://arxiv.org/abs/2306.09310</url></story>