Read more at source.
Read more at source.
The new AI diffusion rule focuses on clusters of high-performance computing and puts controls on proprietary model weights for the most advanced frontier models. However, the rule's complexity and unclear compliance conditions inject considerable uncertainty into the long-term plans of both medium and major US and western hyperscalers. The rule introduces critical issues for hyperscalers like Google, Microsoft, AWS, and Oracle, including slowed or more complex international expansion, new compliance and legal costs, impact on global R&D, and uncertain enforcement requirements.
While US export controls have slowed China's progress in AI, they have also unified the will and efforts of the Chinese government to become more self-reliant. The government has invested tens of billions in helping local players catch up technologically or scale capacity in core areas. This has resulted in significant changes within the semiconductor industry and its ability to support the advanced hardware for developing frontier AI models.
The ongoing US-China AI competition has sparked concerns about the dangers of viewing global AI as a zero-sum game. The rhetoric around 'beating' China in AI risks escalating tensions and could potentially stifle global cooperation in AI research and development. The current approach also overlooks the potential benefits of international collaboration in tackling global challenges through AI.
US export controls have slowed China, but at a high level the sanctions have unified the will and efforts of the Chinese government to become more self-reliant. It has plowed tens of billions into helping local players catch up technologically or scale capacity in core areas, resulting in significant changes within the semiconductor industry and its ability to support the advanced hardware for developing frontier AI models.
