[ossa-ma]

Yes, a positive from this is those with authenticity and taste will shine. Self-expression will be a form of resistance and we'll see a lot less homogenisation across things like writing, ui/ux, animation, individual websites, blogs.

Who knows maybe the old, scattered, personable, decentralised internet will come back - things like MySpace, geocities, sites like this (a lost art): https://www.cameronsworld.net/

Also taste comes from your ability to steer a model instead of having it steer you. e.g. a model suggests a basic pill button, you push back and curse it for its blandness and use it to design something new and novel.

[bluefirebrand]

Why would anyone bother creating or publishing anything new on the internet now that we know that AI companies are just waiting to hoover it up, without compensation, to enrich their models?

Seeing how predatory these companies are in their scraping and then continuing to publish where they can scrape is the absolute height of stupidity

[pulvinar]

I'd like to see the internet return to those who aren't putting it out there for money, so AI companies (and anyone else) hoovering it up wouldn't bother them. Sharing should be the point.

Would also result in fewer sites with ads -- yay!

[cgriswald]

I’ll say a lot of information is cheap and what often matters is presentation. I still visit Wikipedia even though I ask LLMs things.

[sodapopcan]

Physical media is already making a comeback, so let's hope it does with a vengeance and with it, more and more live events.

[cgriswald]

I use LLMs in my fiction writing; and before the wolves come out to shred me to pieces: The LLM never gets to see my writing and doesn't do any of the writing for me. I use LLMs in other ways.

One of the first uses I discovered was to have it identify my own blandness. I'll give it a general scenario from my writing and ask it for ten resolutions to that scenario. If my own resolution appears, I realize at best my resolution is bland and at worst cliche.

[vunderba]

This is eerily similar to something I do with Hacker News stories that hit the front page. I run the post against a couple of LLMs (Mixtral, GPT-OSS, Qwen3, etc.) with the directive to produce a set of 20 of the most likely top-level replies.

I then wait a few days, and then use a couple of systems (embeddings, deBERTa, etc.) to rank comments by novelty against the LLM-produced replies.