AI is running short on more than just GPUs—electricity is becoming an increasingly real bottleneck. Google just signed a long-term power agreement with Constellation for a total of 3.59GW, equivalent to 3.59 million kilowatts. Of this, 890MW comes from additional capacity added through upgrades to existing nuclear power units, while the remaining 2.7GW comes from long-term power supply arrangements. Constellation will invest over $4.3 billion to upgrade its nuclear facilities, with the first batch of additional capacity expected to be delivered in 2028. This shows that tech companies, in order to expand their data centers, now need to lock in electricity supplies for the next 10, 20 years or more, using long-term contracts to support power companies in expanding their generation capacity. Meanwhile, the U.S. Energy Information Administration predicts that total U.S. electricity consumption will reach approximately 4.288 trillion kWh in 2026 and 4.356 trillion kWh in 2027, setting new historical records. The expansion of data centers, combined with electrification in industries, transportation, and other sectors, is continuously increasing the pressure on power supply. You can build the data centers and buy the GPUs, but you still need a stable flow of electricity to power them. Generation capacity, grid integration progress, transformers, and transmission lines—any bottleneck in these areas can slow down the deployment of computing power. The speed of AI's expansion is increasingly dependent on how quickly these infrastructures can catch up. A @Gate, trading more markets