At the Ai4 conference in Las Vegas last week, Nobel laureate Geoffrey Hinton, World Labs CEO Fei-Fei Li, and Coursera co-founder Andrew Ng defended openness in AI development while disagreeing on risk management specifics. Andrew Ng warned against gatekeepers controlling AI access, advocating for a competitive landscape with multiple providers, and highlighted a geopolitical dimension: if China’s open-weight models gain widespread adoption in developing regions, they could shape how billions of people encounter ideas about democracy and human rights. Geoffrey Hinton distinguished open-source software from open-weight models, noting open weights release a trained model’s parameters, making it easier for malicious actors to fine-tune them for harmful purposes like cyberattacks. He conceded the battle over open weights is already lost, saying, “I think that battle’s been lost. We now have open-weight models, so the barrier to lots of people getting these big models, which was the cost of training foundation models, that barrier has disappeared.” Fei-Fei Li rejected a binary framing of the debate, drawing an analogy to nuclear physics where scientific papers are published openly, uranium is regulated, and laboratory work falls in between. She cited the Human Genome Project as an example where open knowledge served as a platform for both scientific progress and commercial innovation, saying, “We need some levels of openness, both in scientific discovery, in education, in global partnership, as well as lucrative business models for entrepreneurs. But we also will accept closed-source systems.”