I personally stay away from AI due to the many issues AI brings.

I am a fan of people fighting big companies.

I have had an influx of these game decomps on my Instagram recently.

I am not trying to be pedantic, but Instagram is “AI.” It was toxic AI before LLMs were a popular thing. Participating in their algorithm is basically everything dystopian about the world of machine learning, concentrated in one service. And using it helps Meta perpetuate it more than using any LLM does.

Again, I don’t mean to be hostile; maybe you use it sparingly in some cleaner way, and I’m not saying everything on Instagram is bad; quite the contrary.

But I just want to make what Instagram runs it crystal clear.

One I’ve had, that’s adjacent, is allowing communities to form “hierarchies.”

So niches could be under /c/technology, individual video games or genres could be under /c/gaming, sports, you name it. It would all require consent from the lower and upper parts of the chain.

One benefit would be “pooling” housekeeping moderation. e.g. if a troll harassed you on a niche community, one from a higher one could moderate it quicker. Or if /c/technology was overwhelmed at a point in time, smaller communities mods could step in to housekeep comments in /c/technology, with the granularity of all this being configurable.

I bring this up because I think it helps the issue of moderators not being responsive enough to your comments. And those passionate enough to run some niche community well enough to fit in a hierarchy would earn the power to moderate comments under topics they’d frequently post to anyway. But it has a lot of other benefits, like helping with discoverability of smaller communities without an algo.

Let’s perform a thought experiment.

I disagree with YOUR post. This one, right here, and I really try to politely articulate my point as to why.

You don’t like it, so you delete it. You delete any post with similar sentiment.

…Is that fair?

If you response is “well, I wouldnt do that,” think about it. That’s the power you’re asking every user on Lemmy user to be responsible with. Do you trust every user to that extent?

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Indeed. But they did get one freak tropical cyclone, in 2004!

https://en.wikipedia.org/wiki/Hurricane_Catarina

It’s the only recorded one in history, though. And I think they still do get some tropical-feeling weather in Brazil.

FYI, on that tropical island in the header image:

Living there is not all it’s cracked up to be. It’s green hell, salt eats everything, pests never get culled from freezing, I could go on and on.

And unless you’re exactly on the equator, tropical cyclones are going to make your life difficult.

On one side…

On the other…

I’m a shameless local LLM shill. I have one loaded right now, experimenting with it.

I also thought Sam Altman was a psychopath before that was the popular opinion, and have never subscribed to OpenAI or even used their free UIs. Not once. Not even the “original” GPT 3.5.

I don’t plan on ever doing it. I will rail against them.

In other words, the sides aren’t mutually exclusive.

One can hate “AI” with a burning passion, using the term AI pejoratively. And be passionate about local ML.

What I’m saying is it’s akin to writing a fanfic or making fanart of your favorite franchise. Or getting inspired by a painting you see, and making something similar yourself.

Do that for your personal enjoyment? That’s fair use, under the law.

But the moment you start trying to sell it is when you get in legal hot water, and when it’s indeed morally problematic.

The scale is different, but I’d argue a similar principle applies: if you use some model trained on public works from a protected IP, but the model and its outputs are not resold, nor profited from, it’s not theft. The point is beyond money not changing hands; there’s no profit being made from the original author’s stuff. They aren’t being taken advantage of any more than someone viewing their public stuff for free, or someone creating derivatives from private work.

But all that is off the table the moment profit and distribution is involved.

Is it really feasible to run it 100% locally? I know there’s plenty of people with very powerful rigs indeed, but still. Or are 99% of these people really saying “it would, in theory, be possible to run that locally, therefore your concerns are invalid”?

Very useful 35B models need (more or less) 8GB of VRAM and 32GB+ CPU RAM to be usable locally. 16GB RAM might work on a lean system with an RTX Nvidia card and an exl3 quantized model.

I know we are in a RAM apocalypse, but pre-apocalypse, that’s a quite reasonable requirement, IMO.

Personally, I run Deepseek V4 07-31 Flash at 19 tokens/second on a desktop with a single RTX 3090 and 128GB CPU RAM, and that’s an extremely capable model. Again, that’s expensive these days, but pre-ram apocalypse, that is not an unreasonable workstation/homelab.

If yes to the previous: the software doesn’t come from nowhere and ultimately still relies on gas-turbine-powered datacenters…

Most open weights LLMs are Chinese. And they are:

• Trained on pennies. They have to be, as they simply do not have a sea of GPUs like Big Tech. Training costs for their large models are in the millions or tens of millions; a single steel forge has used more energy than all of those training runs combined.

• China relies more on renewables, and I believe the datacenters aren’t so hastily constructed with gas turbines in the middle of cities.

• And as of now, they are transitioning away from Nvidia GPUs. Some labs already use Huawei accelerators.

…and stolen IP and stolen personal data?

Yep.

This is a huge caveat.

You can avoid this. Nvidia Nemotron models, for example, are trained on completely open datasets you can download and inspect yourself: https://huggingface.co/nvidia

They are very good, but just behind state of the art.

But in practice, the SOTA models most run use private datasets. Lord knows where the Chinese get it from, but given some common quirks between models, at least some data sources are shared (and possibly government provided?)

…However.

I would argue providing the result of the training as Apache licensed weights counts as “fair use,” in the same way non commercial fan works do.

They aren’t making a dime off releasing those weights. I’m not trying to sell anyone anything when I use them. Where is the IP theft if money isn’t changing hands?

Now, the Chinese LLM services they charge for? I have no excuse for that. Once money is on the table, it is definitely IP theft.

It’s just a tool, another piece of technology to increase efficiency with some liability.

But if such advances aren’t leading to quality of life advances for workers, that’s a societal issue sucking all the gained efficiency away, like how software uses more and more processing to do the same things as computers get faster.

It means the system is fucked up.

Ah. Good. I thought it was only available from Amazon in a few regions, but it appears that isn’t the case anymore.

Pantheon, the TV series.

One of the best shows ever, IMO, so good I can’t say much without spoiling the premise in a Outer Wilds kind of way.

Yet it was trampled by AMC and their failed streaming service. What a mess. I’m not sure it’s possible to even watch legally?

Admittedly, no, but this is slowly improving. Stepfun published their SFT dataset, smaller labs are publishing their datasets for task specific tunes. I believe there was another Chinese lab that published bulk pretraining data, but I can’t find it in my history at the moment.

And, notably, these comparatively tiny labs generally aren’t scraping the internet so abusively like OpenAI/Meta. They don’t need as much. Going by statements in their papers, they tend to use existing archives of web data, buy commercial data, or (more recently) generate a lot synthetic data.

If you run Nemotron, from open datasets.

See the dataset table here. There are sections for pretraining and for specific tasks/topics, like STEM, code and such: https://huggingface.co/nvidia

Chinese models are starting to open their pretraining datasets too, albeit slowly.

this new model, couldn’t universities rebuild it with different contexts and study it in ways you can’t reproduce in other models? like, is k2 horizons a good scientific foundation on which to study machine learning?

Not on a university budget, I don’t think.

But there is all sorts of interesting stuff that can be done with a truly open model other than replicating it.

On top of what others said, Nvidia Nemotron is truly open, with an open dataset.

There have been others (like Olmo), but Nemotron was unique in that it was reasonably useful/cutting edge, while other open models before were basically research artifacts.

…This is exactly what I am talking about.

If EU leftists adopt that way of thinking, the far right will happily sweep up all those disparaged “evil or stupid” voters, with zero shame.

It’s not theoretical. It’salready happening.

This is dismissive.

I know otherwise smart, college or post grad people who voted Trump. I know working professionals, who aren’t religious or anything, who would probably vote for him again over whatever Dem runs. And the left blanket labeling them as evil idiots is exactly what Fox News, WSJ, or their social feeds harp on.

I’m not trying to drag the US into this, I’m just positing that Europe is falling into the same trap. You can dismiss these people, but the far right won’t; they will happily take their vote.

Same thing that happened to the US.

I see a lot of blame on “brainless idiots” or similar labels when discussing this, but I think that’s dismissive of issues many parties seems to be ignoring, or exacerbating, and that the alt-right is pouncing on.

Not everyone who voted Trump is an idiot, and doubling down on that thinking will make the issue worse.

Another is that the far-right parties tend to be “modern” and very social media savvy, whereas establishment centrist parties are out of touch, and campaign in archaic ways. And (from my impression on the outside) the more leftist European parties are prone to disunity and infighting. They don’t benefit from scandal and controversy like the far right does.

Hence “Inflation” is a loaded term that has come to encapsulate other issues consumers are feeling, like wage stagnation, wealth inequity, seemingly high taxes with rising debt and borrowing costs, enshittification, supply issues, purchasing power issues, and other systemic problems like that.

I don’t like it. It’s unscientific and masks too much. But when Americans say “inflation,” I really think they’re expressing feelings for much more than that.