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Joined 3 years ago
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Cake day: June 9th, 2023

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  • Having read the compared stories now, I have to say I’m deeply offended at the results. The AI stories are quicker to read because they are chains of cliches which state and restate the theme of the story (as stated in the prompt) outright instead of demonstrating it through the charged and personal perspectives of the characters. The LLM generated text is meaningless word sausage formatted to be easier to read for people who don’t read much. I have never read something more cynical, and I have read plenty of trash by authors who hate their audience and consider them all to be idiots.









  • I think doors. Most people on Earth reside in a domicile, and many domiciles on Earth have doors. Far fewer people have vehicles and wheels for other purposes have limited use in environments with lots of inclines. I’m caught up in the proportion of housing which has doors versus other housing with doorways or otherwise no room separation.

    Edit: Come to think of it, most vehicles on the road have four wheels and four doors. Two door sedans are generally luxury and semi-trucks with many wheels and only two doors are far less common proportionally than standard passenger vehicles.



  • I wonder how she feels being a grand marshal of an all-white march supporting a colonial genocide? It is an all-white march, by the way. The staffers are there because it’s their job. The Zionists marching in the parade, and all Zionists I’ve ever seen at any of these marches, have the same racial caste demographics as the unite the right rally. I can’t think of any other movement in the US other than white nationalism which has so exclusively white supporters.



  • It’s weird that I’ve spent most of my time living in a post-economic world of abundance which I’m not allowed to acknowledge or encourage others to acknowledge because the pretend economy of valuation and confidence depends on exclusively on showmanship and nothing else. The LLM bubble may persist because the work being “saved” never needed to be done in the first place, so it not being done makes no difference to investors being told what got done as usual.



  • It’s marketing. Nintendo deliberately under stocks new hardware to make the value of the device explode on the secondary market. Scalpers know this and usually buy out most of the first run. When you can’t get the new Nintendo device because it’s unavailable and scalpers are selling it for 2-3x retail price, you are far more likely to buy is asap when it comes back in stock. They make less money initially but in a way that makes the value of the product extremely high, giving people extremely high motivation to buy while they can. Also, a sale to a scalper is worth as much to Nintendo as sale to a consumer. Nintendo is notorious for doing this every time.




  • Thanks for specifying a legitimate use-case for this tool. I understand that google search has been the most valuable programming tool for a very long time so it makes sense LLMs would be more helpful in the same kind of way. Search engine technology is quite a bit different than blockchain or VR in terms of consumer and business demand.

    For my purposes of news and history research, the unreliability of LLMs making me have to check all its claims every single time negates its usefulness as an assistant because I will have to examine its references anyway so it’s more time effective for me to skip the questionable output I would get and do the research myself in the first place. How have you been able to manage the issue of unreliability with the volumes of data you’re dealing with? Is the kind of data which you’re dealing with less likely to be unreliable since it is of a kind the LLM is more likely to process correctly?