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I don't think this is bad. I want tools that deliver what I envision. The fact that given the same input, I get similar output is something I would rather consider a positive. The imagination should come from the human at the wheel.

> he just read out something like "You're right to push back on this. If you'd like, I can reword this..." and didn't even flinch

Can you please provide sources for this? My understanding is that he used the expression "I appreciate the pushback" in a context in which it made sense (responding to criticism), and people flagged that it sounded LLM-like.

There’s some poetry seeing people complaining about how LLM provide unreliable information in a confident tone, who then go on to share incorrect information in a confident tone.


I don’t see how this market ("mostly" AI-written books) won’t get arbitraged to death with the cheaper and open-weight models that keep coming out

The problem is not about money it is that we are made massively culturally poorer by the flood of ahistorical, amoral, incoherent, rococco, contradictory yet plausible shit produced by LLMs.

Both the internet and books have been flooded with ‘content’ which appears like human content but has no coherence or intention to it and tends to fall apart completely the longer form the story.

Even our autocomplete is being infected with LLM suggestions, distorting and guiding how people write.

This is a VERY significant problem for our culture long term.


There was a case a while back now of an AI generated mushroom identification book filled with inaccuracies.

Problem is short of filtering out anything published after 2023 it’s almost impossible to find something that isn’t slop now.


> Problem is short of filtering out anything published after 2023

Is it even feasible to filter this? Such metadata can be easily faked too in a lot of contexts.


We can basically only read well known books from the past.

You don’t use metadata. You use old book reviews and historical top charts.

I don’t see any other way past this other than regulation:

We need authenticated online spaces where your account is linked to a real, government issued ID. This way, moderating content becomes feasible again. Bans will hold value, since you can’t just create new accounts all the time. I predict people will gravitate towards authenticated markets (and social media).

I for one am sick and tired of second guessing every text I‘m reading, at least give me someone to hold accountable.


> Bans will hold value, since you can’t just create new accounts all the time.

People will just flood to places that are not official and where they'll be able to express their views freely. That's how these things have always turned out to be.

In other words, let's say that I'll get banned from the likes of FB or IG as a result of me trespassing my government's ideological wishes, well, tough luck for FB and IG (and fuck them while I'm at it), I'll just make an account on a platform that won't abide by EU/Romanian (I'm Romanian myself) propaganda, where I'll still be able to share views with people thinking similar thoughts to what I think.


Well that doesn't require a regulation. You can just create this space.

A space "regulated" by id. its obvious and its going to happen

When people talk about regulation it's usually government regulation.

Sounds like everything is proceeding according to plan.

https://www.youtube.com/watch?v=-gGLvg0n-uY


Or maybe we just collectively impose severe social sanction on people trying to pass off low effort slop as their own work and stop calling it ‘artificial intelligence’?

the market they analyse is specifically self-published fiction. Most of the traditionally published books are not AI generated and they make significantly more money as a category than self publishing does. It is not really possible to flood that market in this form with 0 entry barriers.

So yes, allowing AI slop in a market where anyone can publish anything and quality is not a very strict criteria, of course it will dillute the market. But we are unlikely to see this shift in traditional publishing houses.


$2m crime novel deal collapses amid questions over AI use

https://www.theguardian.com/books/2026/jul/31/crime-novel-de...


So a book that was “stunningly good, everyone fell in love with it. It’s a book that appeals to absolutely everyone.” now won't be published because AI was used to create it?

Personally I prefer stunningly good over exclusively human created.


I'd want to read it before passing judgement on the quality of it, not trust the word of the author's agent, one Marc Gerald of 'Europa Content', who you are quoting here. It appears a lot of people in the chain up to the editor failed at their job here, probably because they are submerged in slop submitted using LLMs and maybe the first chapter was good and had work put into it.

Clearly the editor didn't think it was stunningly good, or they wouldn't have flagged it up.


Exactly my point. Self publishing does not have these entry problems or that level of money. This is the opposite of flooding the market with generative AI

GAI is also being used by prospective authors applying to publishing houses, and they are in fact flooded with dross created with it, which is a serious problem for them.

To the extent that their reviewers get lazy and are not reading entire texts, as evidenced by this slipping through and then being caught by an editor (who did read the whole thing).

So no, this does not prove your point.


It got rejected and that's the proof that these things get accepted by the system? Sure, AI can flood publishing houses with submissions but they have dedicated people and proper vetting process before they publish. That protects slop from getting published. No such safeguards exists in self publishing which is why its easier to see effects of slop there since nothing can stop you from publishing your AI work in that market.

Damn the pelican guy can’t get no sleep

> xAI is renting out their DC space. I think I read that Google is, too.

You’re probably thinking of Meta. Google renting GPUs is a less recent phenomenon, to say the least.



From HF:

> The practical lesson for defenders: have a capable model you can run on your own infrastructure vetted and ready before an incident, both to avoid guardrail lockout and to keep attacker data and credentials from leaving your environment.

This sounds like a reasonable measure. Any recommendations regarding the most suitable models for this? GLM? Kimi?


How is what you describe "YC-ish"?


Playing backward is actually a great idea for testing generalization


Hey all, happy to see this here! This was a colab between General Intuition (that I’m part of), Kyutai and Epic Games.

You can read plenty of details in the blog post and tech report but the TLDR is that we trained a multiplayer world model on 10k hours of Rocket League data. We optimized it to be playable at 20fps on a single GPU.

So what you see in the demo is fully generated: there’s no graphics or physics engine. Instead it’s a 5b neural network that takes actions in and gives pixels out.


Could a network be trained to transform physics state directly into the latent state and back?

Having a direct transformation would enable some interesting experiments.

How is the latent state different when everything else stays the same, but you change one physics value, like player one velocity? Is there a cyclical pattern of activation that correlates strongly with the seconds digit of the clock? Can you decode the latent state, give players full boost, and then re-encode it for infinite boost, without losing continuity?

Edit: There sure are a lot of papers on interpretability.


Would be a great idea to see how much we could manipulate the latent space and whether it has some internal structure w.r.t the physical state. I guess the only unknown is how the world model would show robustness to latent states that are transformed through this network


Tim Sweeney’s interviews on the uses of GenAI for game development have been some of the best takes I’ve heard. He’s mentioned how GenAI is great at filling in the gaps or treating assets, but no world simulation means no deep persistence or authoring for a whole new unique game world.

What is the conversation like within Epic now? Is this still the view? What is the future for simulations like this?


Very cool, and publishing a slice of the dataset and all of the training code is fantastic, but if reproducing the model and the video representation codec is encouraged, why not open source the models or at least some variant of them?

I'd be interested in seeing if fine-tunes that include human gameplay data would be possible.


We're happy to release MIRA, a collaboration between General Intuition, Kyutai, and Epic Games.

Mira was trained on 10k hours of Rocket League data. The model has 5B parameters and runs 4-player games at 20 fps on a single B200 GPU.

We've released a playable online demo, an in-depth technical report as well as a 1k hour dataset of 4-players gameplay:

Technical report: https://mira-wm.com/paper Repo: https://github.com/mira-wm/mira


How much compute did it take to train the model?


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