Challenges and ConsiderationsComputational Demands: Models like LLaMA 3.1 405B and BLOOM require significant GPU resources, limiting accessibility for smaller organizations.
Alignment and Safety: Open-source models like Zephyr-7B-alpha (not listed above but mentioned in sources) lack RLHF, risking problematic outputs, which is a critical concern for superintelligence development.
Licensing Restrictions: While Apache 2.0 (Granite, Pythia) and MIT (Phi-3) licenses are permissive, LLaMA and Gemma’s custom licenses impose restrictions, potentially slowing community-driven progress.
Global Competition: U.S. open-source LLMs face competition from international models like DeepSeek-V3 (China) and Mistral (France), which offer comparable performance with fewer restrictions.