sorenjan

The neat thing about Danfoss' frequent password resets is that it's always the current date, so it's easy to remember.

https://en.wikipedia.org/wiki/2026_French_supermarket_refrig...

Some of them (Coop) got new equipment after what happened in France and where gonna upgrade them in two days.

Much of Europe is importing fossil gas because they have made themselves dependent on it, because it used to be cheap, because they didn't have to pay the external costs.

This is a political issue. Fossil fuel is cheaper because consumers doesn't pay the external costs associated with them.

The latest tech is using Bitcoin mining to heat water. If you're going to use resistive heating anyway I don't hate it, even though I'm a big crypto currency skeptic.

https://heatbit.com/

It's a specialized job but it's not difficult finding a contractor for it. When my parents did it ~30 years ago I think it cost around $10k. https://www.thermia.se/bergvarme-jordvarme/bergvarme/install...

Can this turmoil be in part because investors wanting to take home some of their profits before the US midterm elections?

They address the lower PSNR for triangles compared with gaussians in the paper, basically PSNR rewards smoothness more than visual quality and gaussians are very smooth. I hadn't seen PSGR[0] before, that looks pretty good but it looks like it's pretty close to the triangle splatting. They flatten the gaussians to flat primitives with varying opacity like the triangles, but the authors of triangle splatting specifically call out that their window function is bounded by the triangles edges which produces better details in some areas. It kind of proves my point about 3DGS getting a lot of research and incremental improvement though, while I haven't seen any follow up research on triangle splatting. They do mention that their method would need additional steps in order to produce a connected mesh, but I think at least in their example images the surfaces looks pretty decent even thought their still made up of a triangle soup.

I just checked if they had released any follow up papers themselves, and one of the lead authors has published a paper about sparse geometry[1] that looks interesting. He's also done a couple of direct follow ups to triangle splatting called Triangle Splatting+[2] and Mesh splatting[3], that produces a connected mesh. It's at least good to see that there's still research into other techniques than just gaussians.

[0] https://zju3dv.github.io/pgsr/

[1] https://lessvrong.com/cs/nexels/

[2] https://trianglesplatting2.github.io/trianglesplatting2/

[3] https://meshsplatting.github.io/

Clanker sores.

It's more than year old, that's pretty old in this fast moving space. I guess it's possible it will get more popular, but I haven't seen it get any traction at all, gaussian splats however are getting more and more development and adoption.

https://arxiv.org/abs/2505.19175

Does anyone know why triangle splatting never took off? I would think it would be much more suited to GPU rendering.

https://trianglesplatting.github.io/

Netflix has made a depth map model that can do pretty much that, although it's used for real time visualization not final production quality. https://eyeline-labs.github.io/FlashDepth/

Interesting that the only issue on CorridorKey2.0 repo is about the licensing issue, then they turned off issues.

https://github.com/nikopueringer/CorridorKey2.0/issues/2

This seems to be because of sensitive data and auditing, not just contacts.

> The risks of unregulated AI use have been noted within a number of authorities where there has also been reason to take other measures.

> Among them is the Swedish Transport Administration, where the internal audit earlier this year discovered widespread and risky use of about ten different AI services and wrote as follows:

> "We have seen several examples of problematic use of open AI services. The examples concern both the sensitivity of the information entered and how the AI-generated responses have been handled."

> Some staff will continue to have access to a dedicated platform for AI assistants—developed in-house by the Government Offices—which provides access to ChatGPT and Claude.

> Internal information also indicates that, following a review, security measures for the approved tool Copilot have been strengthened. However, the press office has declined to provide details regarding these enhancements, citing security considerations.

New version of PocketTTS is apparently censored: https://github.com/kyutai-labs/pocket-tts/issues/390

It's just like how pixelated 2D graphics is called "8-bit" now.

> I was pretty offended that they were telling me what to do on my own land.

They probably felt the same.

Who would have thought that one of the top American tech companies would boast about how their latest product is the best in class in the US, not the world, because they're behind China.

How much does the engineers at Meta make? Spend enough time together with others making $250k+ and eventually you start suggesting that two 512 GB M5s is something you can put on your desktop. I mean, it's one banana, Michael. What could it cost? 10 dollars?

So basically a coding model that can debug and recover from various errors by itself? That makes sense. I left some Qwen model chewing on some coding task a while ago, found out it got stuck in a loop writing the same paragraph of reasoning over and over again.

But Qwen3.8-27B is a known reasonably good coding model that's dense and needs more resources than the smallest local models. What about this one, would you leave a 24B-A2B model coding overnight?

I get that impression to, but why are there so many assistant models released? It must be a very small niche of people actually using them like that? Meta released Muse Glimmer recently, this model, Qwen is made for agentic workflow, Gemma 4 is agentic, all modern models are agentic. So there must be more to it than some hobbyists wanting to automate their calendars and emails.

I don't quite understand how people use these kind of local models that are specifically trained for agentic use cases. Like, what do they actually do with them? Do you use them as an assistant like with OpenClaw?

When used for coding, how do you divide the work between agents? Use a relatively fast model, like this one, as the main agent that calls out to other subagents that write the actual code? But then you'd need multiple models loaded, and why not just use the coding model to do everything? Do you use hosted cloud models for coding and code review, and this local one for orchestration? I don't see the benefit of that workflow either.

I've used local models to write some scripts etc, I like the idea of local computation instead of buying tokens from the cloud, but I don't know what the various agentic models are for, if not code generation.

Shouldn't it be possible to track who bought the esim, where the data is sent, and who owns the wallets where the stolen crypto is transferred?

I recently found a project[0] that takes a ComfyUI workflow and turns it into a simple UI. I have no affiliation with it and haven't tested it myself, but it looks like it might be handy once you have a finished workflow you want to use.

[0] https://github.com/saintbrodie/Orange

That's some local hardware.

It's not far from a skiing resort.

https://funasdalen.se/en/winter/skiing/cross-country-skiing/

Considering where it is it might be protected from logging, so the economic value of the land might be low. The seller is a paper manufacturer, so if they could get more value from it they would have charged more.

I don't know exactly where the land is, but according to media it's south of Storsjö kapell [0]. There's plenty of fell there, and he can't just build whatever he wants even if he owns the land. When a billionaire says he spent $22 million to by it for recreation, I don't see a big reason to not believe him, there's not much else he can use it for.

It's not far from Funäsdalen which is a relatively popular ski resort [1], there are also hiking trails and similar [2].

The seller SCA is Europe's biggest private forest owner and owns 2.7 million hectares by the way.

[0] https://maps.app.goo.gl/hQp2Rw9tM6kWTuTdA

[1] https://funasdalen.se/en/winter/skiing/cross-country-skiing/

[2] https://funasdalen.se/en/summer/hiking/

It depends on what you mean by lossless. If both models can perform the same tasks it can be considered lossless for those tasks. That task might be more related to language understanding rather than memorizing, they have several benchmarks in the article.