30/04/2026
๐๐๐๐ ๐๐จ๐ฅ๐ฎ๐ฆ๐๐ข๐ ๐๐ก๐ข๐ง๐ ๐๐ฎ๐ฆ๐ฆ๐ข๐ญ | ๐๐จ๐ฐ๐๐ซ๐ข๐ง๐ ๐ญ๐ก๐ ๐๐๐ฑ๐ญ ๐๐ก๐๐ฌ๐ ๐จ๐ ๐๐ ๐๐ซ๐จ๐ฐ๐ญ๐ก
At the 2026 China Summit hosted by Columbia University in New York, Brad Li, President of Sineng Americas, participated in the AI Infrastructure & Energy panel discussion with leaders from investment, academia, and power systems.
One theme became very clear: AI is no longer constrained by compute capacityโit is increasingly constrained by power delivery.
As AI data centers scale toward hundreds of megawatts per site, the challenge is not simply generating more energy. It is about how quickly, how reliably, and how intelligently that energy can be delivered.
Key discussions centered on the critical bottlenecks shaping the next phase of infrastructure:
โข Grid capacity and interconnection timelines
โข Permitting and deployment speed
โข The gap between capital availability and power availability
A structural shift is emerging in how AI infrastructure is developed. Time-to-power is becoming the defining variableโnot just cost or location. This is also why power electronics, energy storage, and system-level integration are moving from supporting components to core infrastructure layers.
At Sineng, we see this firsthand.
Through advanced PCS, integrated energy storage, and modular โAI Power Blockโ architectures, the industry is moving toward a new model:
๐ Power that is not only available, but also deployable, controllable, and scalable.
Looking ahead, the winners in AI infrastructure will not be defined by who has access to the most energy, but by who can convert available energy into usable power capacity at the fastest rate.
