Just realized that there are basically no American open models right now ever since the Llama series was abandoned. Basically Gemma and GPT-OSS I guess?
Ah but Mira Murati's new Inkling is Apache 2.0
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
Not only are there many American open weight models as others have mentioned, but Americans are the only ones doing actual open source models [0]. Not just distributing binary blobs and calling them "open".
There are a bunch of them they just don't get the attention because China has flooded the social media channels and is exceedingly good at drowning out the discourse with their benchmaxxed models.
AllenAI and IBM are two companies that release open weight models every couple of months. There are others if you look. OpenAI releases ML models on the regular (not LLMs).
The American open weight and open source AI/ML landscape is very healthy.
Even if by “open models” you specifically restrict that to LLM or LLM-backbone models with different or additional modalities to text released by major American firms then there are still a lot of American open models being released. Many of them are small models and/or highly-specialized fine-tunes of other open models, but there are still a whole lot.
What makes more sense is to do something like deepseek at one of the major universities put those bright computer science young minds to work, in the good old days almost every major university would have done that has any major US university done that? Stanford Harvard Berkeley if the Chinese can put together a team like deep seek why can’t that be done at a major university in the United States?
Do all these models have any significant architectural differences or training data sources? What are the factors going into the diversity of their performance?
This is not the same thing, right? IIUC, the awards for what you linked have already been given out. There aren't awards for the linked initiative - I think that's just Argonne National Lab asking for volunteers to make their (ANL's) award money stretch further, right?
I've had an extremely bad experience working with Department of Energy affiliated programmers in AI. By my invitation, they are part of our workflow and act as humans in the loop, but they have extremely bad habits of gaslighting and accusing people of schizophrenia rather than getting work done.
Here's an example[1] of the difference between what a U.S. Department of Energy employee adds to a ticket versus a private industry AI completing instructions as assigned.
This isn't some cherry-picked example, it's just what I happen to be dealing with right at this moment, happened just a couple of moments ago.
I'm interested to see where they want to land performance-wise (i.e. which point they choose on the scaling curve) and the niche they want to carve. They have a decent ways to scale beyond trinity large, in paticular on posttrain/RL before they are competitive with open-weights, especially internationally.
Deepseek is explicitly banned [1] at LLNL and I wouldn't be suprised if there's a blanket ban on all Chinese models. But nowadays models like tera/luna could fill this area of the pareto front, and LANL already runs openai models on their clusters [2]. Maybe it's in custom SFT/RL, for instrument control or sensitive topics? But you'll still have to compete with frontier models + a harness.
I would have also liked to see a carrot tied to their offer. It'll be hard to get teams to contribute RL gyms or curated text. But throw in a "we'll fund a postdoc/student to do that" and I think you'd have teams scrambling to apply.
There's no mention of "LLM" nor "language". It does mention "foundation model" which includes LLMs but that also includes non-LLM architectures and non-text data. Many of the Genesis Initiative proposals answer "foundation model" call with non-LLM systems. All the FM's I know about currently in this sphere are non-LLMs. The "about gs1" page also does not mention "LLM" but does talk more about agentic harness and workflows. That description certainly sounds LLM'ish but describes a more rich system. I don't mean to suggest that LLMs will not be part of these "genesis open models" but as described, this will not result in a replacement for the "claude" or "codex" commands.
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[ 3.3 ms ] story [ 51.7 ms ] threadAh but Mira Murati's new Inkling is Apache 2.0
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
[0] https://allenai.org/
AllenAI and IBM are two companies that release open weight models every couple of months. There are others if you look. OpenAI releases ML models on the regular (not LLMs).
The American open weight and open source AI/ML landscape is very healthy.
https://www.interconnects.ai/p/the-american-deepseek-project
Here's an example[1] of the difference between what a U.S. Department of Energy employee adds to a ticket versus a private industry AI completing instructions as assigned.
This isn't some cherry-picked example, it's just what I happen to be dealing with right at this moment, happened just a couple of moments ago.
[1] https://ibb.co/vCg2G1Dn
Deepseek is explicitly banned [1] at LLNL and I wouldn't be suprised if there's a blanket ban on all Chinese models. But nowadays models like tera/luna could fill this area of the pareto front, and LANL already runs openai models on their clusters [2]. Maybe it's in custom SFT/RL, for instrument control or sensitive topics? But you'll still have to compete with frontier models + a harness.
I would have also liked to see a carrot tied to their offer. It'll be hard to get teams to contribute RL gyms or curated text. But throw in a "we'll fund a postdoc/student to do that" and I think you'd have teams scrambling to apply.
[1] https://hpc.llnl.gov/about-livermore-computing/ai-ml-lc/lc-l...
[2] https://www.energy.gov/nnsa/articles/nnsas-los-alamos-nation...