Good thing about LLMs is that they can't put the genie back in the bottle, and long after OpenAI and Anthropic bite the dust (not wishing that but just saying given their trajectories), there will continue to be people, engineers and startups working on open source LLMs.

My hope is that we're able to somehow repurpose all of the GPU chiplets currently sitting in warehouses and in massive datacenters for broader consumer, academic, educational and non-profit consumption. It will create such great value and ripple effect creating and spreading hardware + computing literacy far and wide. Ugh, hope that happens.

We've tried to take a first-principles approach to our end goal of 'legal superintelligence' that has involved identifying the areas of our domain most in need of improvement and releasing models that raise the bar on quality in those areas.

We've been around for a couple months now and ended up starting with retrieval and enrichment. The models we've released to tackle those problems have indeed been smaller in size than their competitors, yet they still rank ahead on open-source benchmarks.

Them being so small also helps with their accessibility — as I mention in our posts, our models can be deployed on ordinary hardware, not a supercomputer.

Next on our roadmap is reasoning and research, which will require more infrastructure to support, but again, we aim to be judged by performance at the time of release.

> As much as I agree with the message, this reads like marketing copy trying to make a big deal out of a tiny model being hosted privately.

The point of this point is really just to reaffirm our commitment to sovereignty and accessibility and contrast our approach with that of major AI labs. It _is_ possible to commercialize LLMs while still keeping them accessible. A customer using a self-hosted deployment today does not need to worry about our models no longer being available tomorrow. We think that's a good thing. And moving forward, we want to keep that option available for anything we do, instead of trying to pull up the ladder while we're ahead.

When it took years and years of training to learn how to master something enough to use it with great impact, that effort was strongly correlated with the discipline and lifestyle to not misuse those abilities.

Completely gate-free LLMs would have very "useful" answers to a nutjob prompting "How do I cause as much destruction as possible with only what I can find at the hardware store" or similar. Sophisticated guards are still very hard to do to avoid giving a whole lot of power to someone not very friendly and not very disciplined.