Better than that

Mitosis, if cells classify as mechanical

And even if they publish the model it’s almost always just open weights

According to artificialanalysis.ai’s latest benchmarks, it scores better than Opus 4.8 set to max, despite costing half as much per task.

It also beats the top models of some of the largest US tech companies such as xAi, Meta, Google, and Nvidia.

I wonder what the US tech investors will think of this, and what this will mean for the financial AI bubble.

You can use it through openrouter

AFAIK, their open models are distributed as weights, not executables and are therefore not able to start network connections / run code. There is of course tool-calling functionality but that just works by having the model output a special pattern and having something external run predetermined commands based on that.

Nuclear landmines?

What about the dopper?

Haven’t used Claude code myself, so I wouldn’t know, but a commit to delete only a comment is indeed pretty weird, also most of the commit messages are the GitHub default like “Update gui.h” which is also a bit odd.

Looking at the GitHub repo it seems like the first commit was actually just 2 weeks ago and contained 12k lines. I can’t spot any AGENT.md files, but it does feel like the author quite new to this. That could be explained by them being 16 though like they say on their profile.

I agree. The worst part about GitHub training LLM’s on my FOSS code without permission for me is that they then keep the models to themselves. Like if you’re going to use all my code without permission, at least allow me to run the model locally.

My personal opinion is that all models trained on copyleft code should be open-weights, most FOSS licenses didn’t account for this specific possibility, but this is the only way to follow them in spirit.

Deepseek recently published a paper in which they describe that vision tokens contain more information than text tokens and that this can be used to compress context.

We present DeepSeek-OCR as an initial investigation into the feasibility of compressing long contexts via optical 2D mapping.

Experiments show that when the number of text tokens is within 10 times that of vision tokens (i.e., a compression ratio < 10×), the model can achieve decoding (OCR) precision of 97%. Even at a compression ratio of 20×, the OCR accuracy still remains at about 60%. This shows considerable promise for research areas such as historical long-context compression and memory forgetting mechanisms in LLMs.

It reminds me of LLM caveman speak, it used to have another option to use Chinese instead of English. A language like Chinese is seemingly better at encoding information in fewer tokens and I think this is the same mechanism why OCR tokens work so well.

That said, I also doubt that voice messages are more efficient than text prompts, but it’s best not to waste too much time engaging with these sorts of LinkedIn posts (and LinkedIn in general).

It’s being downvoted with relatively little discourse because it’s an insult with no relevance to the topic, in addition to supporting a comment from someone who is either trolling or has no idea what they’re talking about

but it should’ve been clear to them

How clear was it?

This does not seem convenient at all, from the bash script to get relative links, to the file tags which are not synced across devices by standard git or file sync.

I think the latter

Exactly, my last laptop was around €750 but I remember looking for a similar (in terms of performance) Framework laptop and it was around €1200 if I remember correctly, not an insignificant difference for a student.

It’s interesting that the people who claim to avoid politics being prioritized over technical merit in a project, usually end up doing so themselves. Nobody else cares about whether their Linux Distribution is “woke” (whatever that means) or not. NixOS is innovating with declarative configuration, Bazzite makes itself accessible to a whole new demographic, Debian continues casually maintaining global digital infrastructure and meanwhile in contrast, some are hunting for rainbows.

The thing is that people don’t want to get that new game that that seems so fun to find out that it doesn’t actually work. Other games not working is seen as a sign of potential future trouble.

I had a conversation with a colleague of mine about this. He believed that Musk’s decision to merge xAI and SpaceX was truly because of the potential of datacenters in space. I was unable to convince him that the logistics of this would be a nightmare and that this was just a way to make the Twitter buyout SpaceX’s problem.