Jensen Huang addressed the distillation controversy in an Axios interview, framing it as a fundamental aspect of intelligence rather than plagiarism. He stated that AI is currently generating a large amount of content and that distillation will become the norm in the future. NVIDIA, as a computing power equipper, supports a broader model ecosystem, and distillation reduces inference costs, which benefits the diffusion of GPU demand. The motivation is to promote overall AI capability enhancement while avoiding simply characterizing distillation as intellectual property infringement. Huang compared the process to human education and knowledge transmission models, noting that the AI industry is transitioning from "data scarcity" to a stage of "mutual learning among models." This represents a technological substitution where the proprietary advantages of closed-source models are partially mitigated by distillation, which transforms one-time training results into sustainable, transmissible increments of intelligence. The article concludes that distillation is not theft but the default operating mode of intelligence, and when content is dominated by AI, the objects of learning inevitably become other AIs, with smarter systems often being safer systems.