Comment by Ben Brooks

Since the launch of powerful open models like the Llama, Falcon, Mistral, and Stable Diffusion families, critics have pressed to keep other such genies in the bottle. "Open source software and open data can be an extraordinary resource for furthering science," wrote two U.S. senators to Meta (creator of Llama), but "centralized AI models can be more effectively updated and controlled to prevent and respond to abuse." Think tanks and closed-source firms have called for AI development to be regulated like nuclear research, with restrictions on who can develop the most powerful AI models. Last month, one commentator argued in IEEE Spectrum that "open-source AI is uniquely dangerous," echoing calls for the registration and licensing of AI models. However our governments choose to regulate AI, we need to promote a diverse AI ecosystem: from large companies building proprietary superintelligence to everyday tinkerers experimenting with open technology. Open models are the bedrock for grassroots innovation in AI. Eventually, these regulations may lead to limits on fundamental research and collaboration in ways that erode this culture of open development, which made AI possible in the first place and helps make it safer. Open models play a vital role in helping to drive transparency and competition in AI.[...] In this environment, open models play a vital role. If a model’s weights are released, researchers, developers, and authorities can "look under the hood" of these AI engines to understand their suitability and to mitigate their vulnerabilities before deploying them in real-world tools. Everyday developers and small businesses can adapt these open models to create new AI applications, tune safer AI models for specific tasks, train more representative AI models for diverse communities, or launch new AI ventures without spending tens of millions of dollars to build a model from scratch. AI Verified source (2024)