In the current era of rapid AI advancement, the energy requirements for large-scale models have surged to unsustainable levels, relying heavily on high-performance computing. The search for sustainable energy sources has never been more urgent. China's recent breakthroughs in nuclear fusion, particularly with its Experimental Advanced Superconducting Tokamak (EAST), have reignited global discussions on whether fusion energy is a viable long-term solution. China has made significant progress in prolonging plasma confinement, demonstrating the potential of fusion as an abundant, clean energy source. However, a critical question remains—can nuclear fusion meet the growing energy demands of AI? Although still in the experimental phase, fusion has the potential to revolutionize global energy consumption and fuel the next generation of AI-driven innovations.

Why Do We Need Fusion Energy?

As AI’s energy demand soars, nuclear fusion emerges as a transformative solution. Unlike fossil fuels, fusion generates clean, limitless energy without greenhouse gas emissions. It is inherently safer than nuclear fission, as it does not produce long-lived radioactive waste and carries no risk of catastrophic meltdowns. Given these advantages, fusion is widely seen as the key to solving future energy challenges, ensuring a stable, carbon-free power source for AI and beyond.

The Power Needs of AI Model Training

Training advanced AI models is an energy-intensive process, requiring thousands of GPUs and TPUs running for weeks or months. The power consumption of AI data centers has increased dramatically, forcing companies to rethink efficient and scalable energy solutions. For example:

• NVIDIA A100 – 400W per GPU
  
  

• NVIDIA H100 – 700W per GPU
  
  

• Google TPU v5p – ~1000W per unit

With the advancement of AI, even more powerful chips are being developed, further intensifying energy demands.

Predicted Energy Use for AI in the Future

Given the rapid advancements in generative AI, machine learning, and real-time AI processing, energy consumption could surpass 3,000 terawatt-hours (TWh) per year by 2030—equivalent to the combined energy usage of Japan and Germany. In the near future, training a single large-scale AI model like GPT-5 might require ten times the energy of today’s leading models.

Google’s Nuclear Power Initiative with Kairos

Recognizing the escalating energy demands of AI, Google has partnered with Kairos, a nuclear technology company, to develop a next-generation small modular reactor (SMR) to power its AI infrastructure. This collaboration marks one of the first direct investments by a tech giant in nuclear energy, highlighting the shift towards self-sustained, carbon-free power for data centers.

By reducing reliance on traditional power grids, which are struggling to support AI’s massive energy needs, Google’s initiative could pave the way for scalable fusion and fission hybrid models. If successful, this project could set a groundbreaking precedent, encouraging other AI-driven companies to explore nuclear power as a long-term energy solution.

The Nuclear Fusion Race: China vs. the USA

China and the United States are competing for dominance in nuclear fusion, with both nations striving for a breakthrough that could reshape global energy, technology, and AI infrastructure.

• China’s EAST reactor – Pushing the boundaries of plasma confinement and sustained fusion.
  
  

• National Ignition Facility (NIF, USA) – Achieved net energy gain in fusion for the first time in 2022.
  
  

• MIT’s SPARC Reactor (USA) – Developing high-temperature superconducting magnets for compact fusion reactors.
  
  

• Helion Energy & Microsoft Partnership – Aiming for commercial fusion power by 2028.
  
  

This fusion race is about more than just energy security—it is a battle to shape AI’s future, industrial power systems, and global technological leadership. The nation that achieves sustainable fusion first could control the next era of innovation.

Verdict

The intersection of AI and nuclear fusion represents a pivotal moment in energy history. While AI models continue to demand exponentially more power, nuclear fusion offers the promise of limitless, clean energy. However, commercial fusion remains a long and uncertain road, with fission and alternative energy sources still playing a dominant role in meeting AI’s power demands today.

Regardless of whether China or the U.S. leads the fusion breakthrough, one thing is clear: the future of AI and energy are deeply intertwined, and nuclear fusion could be the ultimate key to unlocking the next technological revolution.