NEW TECHNOLOGIES CAN CHANGE THE GLOBAL BALANCE OF POWER. Nuclear weapons divided the world into haves and have-nots. The Industrial Revolution allowed Europe to race ahead in economic and military power, spurring a wave of colonial expansion. A central question in the artificial intelligence revolution is who will benefit: Who will be able to access this powerful new technology, and who will be left behind?
Until recently, AI has been a diffuse technology that rapidly proliferates. Open-source AI models are readily available online. The recent shift to large models, such as OpenAI’s ChatGPT, is concentrating power in the hands of large tech companies that can afford the computing hardware needed to train these systems. The balance of global AI power will hinge on whether AI concentrates power in the hands of a few actors, as nuclear weapons did, or proliferates widely, as smartphones have.
Access to computing hardware creates haves and have-nots in this new era of AI. Frontier AI models such as ChatGPT and its successor, GPT-4, use massive amounts of computing hardware. They are trained using thousands of specialized chips running for weeks or months at a time. Production of these chips and the equipment used to manufacture them is limited to a few key countries: Taiwan, South Korea, the Netherlands, Japan, and the United States. That means these nations have veto power over who can access the most cutting-edge AI capabilities. The United States has already weaponized this dependency to cut off China’s access to the most advanced chips.
States responded to the challenge of the nuclear age by controlling access to the materials needed to make nuclear weapons. By limiting countries’ access to weapons-grade uranium and plutonium, the international community has slowed nuclear proliferation. Control over the specialized hardware needed to train large AI models will similarly shape the global balance of power.
began in 2012, and as it moves into its second decade, there are several important paradigm shifts underway. New generative AI models such as ChatGPT and GPT-4 are more general purpose than prior narrow AI systems. While they do not (yet) have the generality of human intelligence, they can perform a diverse array of tasks. GPT-4 achieves human-level performance on the SAT, GRE, and the Uniform Bar Exam. The AI agent that beat top human player Lee Sedol in the Chinese strategy game Go in 2016, AlphaGo, could only play Go. It could not hold a conversation, write a poem, analyze an image, play chess, craft recipes, or write computer software. GPT-4 can do all of these
