<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>daxvena</author><text>I doubt it&amp;#x27;s going to go the same way as search. You can&amp;#x27;t run Google on consumer hardware, but you can run LLMs locally.&lt;p&gt;At worse, newer models will get worse and you can just stick to older models.&lt;p&gt;You could also argue that proprietary models gated by an API are better than anything you can run locally, and yeah maybe those will get worse with time.&lt;p&gt;They&amp;#x27;re not going to get any worse than what you can run locally though. If they do, open models will overtake them, and then we&amp;#x27;d be in a better position overall.</text><parent_chain><item><author>scottbez1</author><text>Succinctly stated and something that resonates strongly with me.&lt;p&gt;In the last internet revolution (web search), results started high quality because the inputs were high quality - bloggers and others just wanted to document and share knowledge. But over time, many interests (largely commercial) figured out how to game the system with SEO, and quality of search results has decreased as search&amp;#x27;s incentive structure led to lower quality data being indexed.&lt;p&gt;We&amp;#x27;re at the start of the LLM revolution now - models are trained on high quality inputs (which may be as rare as &amp;quot;low-background steel&amp;quot; in the future). But the models allow the mass production of lower quality outputs with errors and hallucinations; once those get fed back into new models, are we doomed to decreasing effectiveness of LLMs, just as we&amp;#x27;ve seen with search? Will there be LLMO (LLM optimization) to try to get your commercial interests reflected in the next generation models?&lt;p&gt;I think we&amp;#x27;ve got a few golden years of high quality LLMs before that negative feedback loop really starts to hurt like it did in search.</text></item></parent_chain></comment><story><title>The AI bullshit singularity</title><url>https://successfulsoftware.net/2024/02/18/the-ai-bullshit-singularity/</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>__loam</author><text>We may enter into a highly ironic regime where ai companies subsidize writers and artists at scale to produce better data.</text><parent_chain><item><author>scottbez1</author><text>Succinctly stated and something that resonates strongly with me.&lt;p&gt;In the last internet revolution (web search), results started high quality because the inputs were high quality - bloggers and others just wanted to document and share knowledge. But over time, many interests (largely commercial) figured out how to game the system with SEO, and quality of search results has decreased as search&amp;#x27;s incentive structure led to lower quality data being indexed.&lt;p&gt;We&amp;#x27;re at the start of the LLM revolution now - models are trained on high quality inputs (which may be as rare as &amp;quot;low-background steel&amp;quot; in the future). But the models allow the mass production of lower quality outputs with errors and hallucinations; once those get fed back into new models, are we doomed to decreasing effectiveness of LLMs, just as we&amp;#x27;ve seen with search? Will there be LLMO (LLM optimization) to try to get your commercial interests reflected in the next generation models?&lt;p&gt;I think we&amp;#x27;ve got a few golden years of high quality LLMs before that negative feedback loop really starts to hurt like it did in search.</text></item></parent_chain></comment><story><title>The AI bullshit singularity</title><url>https://successfulsoftware.net/2024/02/18/the-ai-bullshit-singularity/</url></story>