<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>mrtksn</author><text>The bottleneck is probably the availability of lithography machines that can make ubiquitous chips for processing that much data quickly enough without heating or drawing electricity too much.&lt;p&gt;Not too far in the future every device will have some 5nm or better tech LLM chip inside and devices understanding natural language will be the norm.&lt;p&gt;By dumb machines, people will mean machines that have to be programmed by people using ancient techniques where everything the machine is supposed to do is written step by step in a low level computer language like JavaScript.&lt;p&gt;Nerds will be making demos of doing something incredibly fast by directly writing the algorithms by hand, and will be annoyed by the fact that something that can be done in 20 lines of code on few hundred MB of RAM in NodeJS now requires a terabyte of RAM.&lt;p&gt;Dumb phone will be something like iPhone 15 pro or Pixel 8 Pro where you have separate apps for each thing you do and you can&amp;#x27;t simply ask the device to do it for you.</text><parent_chain><item><author>taf2</author><text>So it’s safe to assume in the next 10 years - AI will be running locally on every device from phones, laptops and even many embedded devices.  Even robots- from street cleaning bots to helpful human assistants?</text></item></parent_chain></comment><story><title>OnnxStream: Stable Diffusion XL 1.0 Base on a Raspberry Pi Zero 2</title><url>https://github.com/vitoplantamura/OnnxStream/tree/c0cb4b3d7b419e4b10129904fbe16b850ca5d385</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>fragmede</author><text>Every Google Home device is already running an ML model to do speech recognition to recognize the &amp;quot;hey Google&amp;quot; wake word, so sooner than 10 years. The Raspberry Pi Zero is a particularly underpowered device for this. Doing it on the Coral TPU accelerator plugged into a pi zero would take less than 30 mins. Doing it on an iPhone 15 would take less time. Doing it on a Pixel 8 would be faster. Not to diminish getting it to work on a Pi Zero, but that future is already here, just as soon as we figure out what to do with them.&lt;p&gt;&lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;coral.ai&amp;#x2F;products&amp;#x2F;accelerator&amp;#x2F;&quot; rel=&quot;nofollow noreferrer&quot;&gt;https:&amp;#x2F;&amp;#x2F;coral.ai&amp;#x2F;products&amp;#x2F;accelerator&amp;#x2F;&lt;/a&gt;</text><parent_chain><item><author>taf2</author><text>So it’s safe to assume in the next 10 years - AI will be running locally on every device from phones, laptops and even many embedded devices.  Even robots- from street cleaning bots to helpful human assistants?</text></item></parent_chain></comment><story><title>OnnxStream: Stable Diffusion XL 1.0 Base on a Raspberry Pi Zero 2</title><url>https://github.com/vitoplantamura/OnnxStream/tree/c0cb4b3d7b419e4b10129904fbe16b850ca5d385</url></story>