AI2, a non-profit organization, is revolutionizing the open source AI community by making post-training regimens for large language models (LLMs) accessible to everyone. This move aims to bridge the gap between open source AI projects and private companies like Meta and OpenAI, which have traditionally kept their post-training methods secret.

The post-training process is crucial in transforming "raw" LLMs into usable ones, but it's a complex and time-consuming task that requires significant expertise. AI2's Tulu 3, a significant improvement over its predecessor, offers a comprehensive and adaptable post-training regimen that can be used to create custom-trained LLMs. This democratization of post-training regimens has the potential to level the playing field for startups and researchers who want to build custom-trained LLMs without relying on private companies.

The implications of AI2's move are far-reaching, particularly for industries like medical research and service companies that require high levels of data privacy and security. With Tulu 3, these organizations can now create custom-trained LLMs on-premises, reducing the risk of data exposure and dependence on external companies. AI2's commitment to openness and transparency is a significant step forward for the AI community, and its impact will be closely watched in the coming months.