Reddit seems to be highly algorithmic now, so I think it has more of the “doomscrolling effect” that does accrue a lot of engagement.

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.

Well I was thinking the opposite.

Take the existing community fragments, and unify them into a structure so they don’t wither.

The problem I see on Lemmy is that niche communities aren’t very discoverable, hence never cultivate much interaction, but “percolating” posts up would address this.

Lemmy and Piefed need a “subcommunity” structure to get that ball rolling IMO.

EG you may have an overarching “sports” community, and in layers:

sports -> basketball -> NBA -> team

• So if your team sub was kinda dead, you could browse /c/NBA or /c/basketball and get a wider feed of other teams.

• Similarly, you could mark non-spammy posts to “filter up” to the higher communities that accept it. So you make a post in your team community, and folks browsing basketball might see it, depending on their settings.

Permissions would be granular to set this up, consensual for both the “upper” and “lower” communities.

I’ve written this up as a more general proposal ti help niche communities, but have yet to put it on the development gits as a feature request.

I think the main benefit, theoretically, would be engagement with other parts of the Fediverse. It might be an introduction to many if they see an update scroll by in the feed.

Less friction is better though. And not everyone knows where else to go for E2E.

The problem to me would be development burden, but its alreast implemented so…

Thats the secret sauce of the Fediverse.

It doesnt have to compete/steal attention across apps. It can cooperate and combine it.

I have been putting off focusing on some niches too long, mostly because of IRL executive dysfunction.

Yeah.

Don’t get me wrong, I don’t want to touch projects vibe coded to this level, going solely on past experience with them.

But I am scientifically curious about its functionality.

Yeah, in that case it’s sus. I’d be scared to look at the codebase.

Does it actually work, though?

Oh yeah… yeah, it doesn’t seem like it’s client/server or anything. It’s just a CAD program?

Doesn’t fit this at all.

I dunno if it fits the “vibe coded” label though, as it appears to work well. I tend to apply that to quick hacks, or to projects where the devs clearly have no idea what they’re doing (and end up with something really bloated and janky, yet hyped a ton).

Why is a post about a CAD program being downvoted so much?

I mean… it’s an issue. OP’s system is swapping the SSD when it clearly should not be doing it. My system had horrible usability issues in some scenarios without a lot of reconfiguration, and thrashed my SSD for no benefit.

The default heuristic is not good for our systems, and OP’s situation is a pretty common scenario. That’s a fact. How is that not an issue?

And support for TRIM and whatever else was added for SSD support is not really the issue, here. That’s working fine.

I disagree with most here.

You need to reduce swappiness even more, and tweak some other variables (like the memory “threshold” Linux starts to swap, and disk cache aggressiveness) to stop Linux from swapping so opportunistically under such a light load.

IMO, Linux is configured for “old” systems by default: slow HDDs, and constrained RAM pools, where disk IO really, really needs caching, and where idle background processes take a large fraction of RAM.

You have superfluous RAM for your workload. And very fast disk IO that isn’t such a hindrance to apps anyway. And a disk you don’t want to wear. This is the opposite scenario: you don’t want Linux to swap unless it absolutely has to.

For reference, this is part of my config. It’s rather niche and you probably shouldn’t use it, but you should consider looking up the variables:

# Keep min reserve reasonable for 8GB usable space
vm.min_free_kbytes = 262144        # Lower absolute minimum to 256MB

vm.watermark_scale_factor = 10     # Lower to 0.1% (which is ~128MB on 128GB)

# Disable watermark boosting completely
vm.watermark_boost_factor = 0

# Normal-ish metadata pressure so desktop doesn't stutter on disk reads
vm.vfs_cache_pressure = 120

# Allow reasonable swapping of inactive anonymous desktop pages, could be lower
vm.swappiness = 10

# Dirty bytes limits to limit caching
vm.dirty_background_bytes = 67108864
vm.dirty_bytes = 268435456

# Disable compaction & proactive scans to stop freezing with large portions of RAM mlocked
vm.compaction_proactiveness = 0
vm.compact_unevictable_allowed = 0

vm.page-cluster = 0 # 4kb pages for SSD

My system still uses RAM as disk cache with this config, it just won’t go out of its way to swap just to keep that cache, especially I lower swappiness to 1-3.

I also have a 1GB zram pool, prioritized over ssd swap. But you should make yours even larger (maybe 4GB?). This will intercept anything that does swap first.

I also start some applications with systemd-run and specify memory caps and swap limits (often forbidding them from swapping entirely).

It makes a night-and-day difference for some workloads on my system, that would otherwise swap pointlessly, just tank performance and even de-stabilize the system.

It’s “free ram” until stuff actually goes in swap.

It depends on the scenario, of course. Maybe you have huge, totally idle processes, and active ones working from an HDD that need cache desperately, in which case this is good.

But my experience with Linux is that is waaay to aggressive with this, in most configs, and I get far better performance from configs that avoid swap until it absolutely has to be used.

Social gating, too.

This is a lovely read, a lot of interesting and compact pondering. Cheers.

Yeah, precisely.

This is exactly what I’m talking about.