The open source AI community is facing significant challenges, not just in computing power but in the post-training processes that create usable models from large language models.
Contrary to popular belief, fully trained foundation language models need extensive post-training to become useful, which is where real value is created.
AI2 aims to enhance transparency in AI training processes, exposing its data curation and training methods, unlike private companies that closely guard their post-training methods.
While many open source models are available, the lack of clarity in their training processes calls into question the true openness of these supposedly 'open' AI projects.
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