LiquidAI LFM models are amazing, but very situational. IBM Granite series are also unique and interesting for trying to reduce liability and extend local context size. Nvidia ships some and there was also that Inkling model recently. Poolside just released theirs.

Meta might release something this year. X AI's Grok is still due to release a model, if Elon keeps to his word even if they only release a distilled version. Reflection AI has been quiet, but their access to compute is ramping up. Microsoft's MAI is considering releasing some open weight models which would be great to see!

Ilya's SSI is unlikely to release an open model since he's aiming for radical safety. That bet could pay off if the existing approach produces so much chaos within the next 10-20 years that some global ban is achieved and a super safe model is promoted as the compliant route.

We don't get many huge model releases though. I think it's harder and more expensive to safety align them. Even if you do, people will work around the safety and abuse the models. Plus it makes it even easier for Chinese companies to distill things that aren't as easy over filtered APIs.

There is a lot of internet propaganda to the effect that the US is simply unable to release open weight models or that China has so many more AI companies that the US is drowning in Chinese open weight models, but it's more like we're being careful and China doesn't care. If you host a model in China, it has to be censored and downloading any models requires you to provide your identity. Huggingface is banned there. When they release their open models in the west, they don't have to care whether the models are aligned in any way.

There's a bunch of American open models. Inkling, Nemotron, Trinity come to mind, but I'm sure there's others.

Also Nemotron and Arcee.

I would not be shocked if another open model eventually shakes out of Facebook (based on Zuckerberg's public remarks).

> But it makes sense that if you're a university researcher you are thinking about what's a model that will be open weight and developed over the long term and doesn't raise 'Chyna' concerns in Washington DC

Why phrase it "Chyna" when it's an actual legitimate concern?

Laguna is the most recent and capable one that comes to mind. In its size class it is not as "smart" in my experience as qwen 3.5 122 or DeepSeek v4 flash 0731 (all at q8), but it's also not terrible.

https://huggingface.co/unsloth/Laguna-S-2.1-GGUF

review of AllenAI Olmo research team and commitment to OSS -- AI2 complete transparency including training data, code, intermediate checkpoints, and detailed logs for reproducibility and scientific rigor.

I've used Inkling a lot recently, it's an American open model and is really good!

You didn't read the article because the company that worked on this has published open models before and both these things are mentioned early on.

Laguna S 2.1 is another fairly impressive-for-the-size American open model

I'd actually suggest a great starting point would be a local command reviewer LLM. Could ostensibly be a modern AV type thing. Particularly seeing this lately has driven the need home deeper to me: https://x.com/chrisbanes/status/2085341561609425230?s=20

An open weight tool call auto-reviewer, has all sorts of achievable scaling curve milestones.

That's interesting a locally hosted LLM would be banned. I'm assuming locally hosted is included. Do they think it's been trained to sabotage equipment?

The article posted is basically entirely about that.

As part of a much larger series of initiatives towards digital sovereignty, yes. [0]

[0] https://commission.europa.eu/news-and-media/news/strengtheni...

It looks like they're taking applications for training data (due August 14th), so I think it's safe to say this is just an announcement of intent and a call for involvement vs. something that is readily available. Seems almost quaint in comparison to the strategy of sucking up every piece of data you can find anywhere on the Internet and feeding it to your LLM but I suspect their intent is to be more careful in what they train their model on.

What is the FUD happening from 1 frontier lab?

Let’s distinguish a bit. There are political appointees (Trump’s government employees as you say) who are mostly upper management, and there are career civil servants (all the government scientists are under this category) who have a strong culture of apolitical dedication to the mission of their agency and to the American people and Constitution, regardless of who the current president is. And in the DOE labs in particular most (not all) of the scientists are actually employed as government contractors, but they have a similar non-partisan ethos.

That doesn’t necessarily mean there’s no need to be concerned with potential impact of policy and priority changes from the administration, but it does temper the threat model because the government employees you’re considering trusting have given oaths of office to protect and defend the Constitution.

If it’s auditable like open source code? Yes.

Mostly because it's generally a bad idea for government to try to compete with a brand new tech industry with hundreds of billions in private capital developing commercial models. If the American private industry does actually wash out vs Chinese open models there might be talent available for them to put money into, so maybe they are just preparing for that scenario in the meantime.

The Australian Liberal Party (basically our version of conservative republicans) proposed the National Energy Guarantee policy in 2017, which inevitably failed due to the media and public’s relative literacy and tendency to turn policy names into acronyms.

Can you explain the screenshot a little more? It just looks like you’re comparing the output of a chatbot and Claude Code about a log file. If it’s a metaphor, it went over my head, sorry!

Is this a joke? I don’t get it. Are you calling Rovo a DoE programmer?