Trading Kilowatts for Qubits
It had been in the news in the United States all week, the federal government is moving to a policy that will require the power-hungry data centers to get out of the public energy pool and go swim in a plasma of their own making. Big Tech companies are building and investing in their own energy supplies as they race to meet the huge energy demands of AI computing in 21st century datacenters. It's estimated that a "traditional" (non-AI producing) datacenter rack can consume somewhere between 5 and 15 kilowatts of power --think central A/C units, commercial clothes dryers, banks of EV car chargers. That same rack, running AI-capable hardware and processing power will consume 10 times as much -- up to around 100 kilowatts.
As robust as the United Stated power grid is, the demand for electricity to power these clustered artificial intelligence entities will exceed the current ability to support that demand. To feed this need for power, Amazon has begun developing small nuclear reactors (SMRs), Oracle and OpenAI are working on half trillion-dollar natural gas fueled electrical plants. These solutions have their obvious drawbacks: Amazon's quest for contemporary electricity using the nuclear option will produce the most-toxic waste ever thrown away, and it will last for thousands of years. Oracle and OpenAI's investment in huge natural gas energy sources risks not only accelerating climate rot, but it risks exhausting energy supplies at scale. The risks of expanding the electricity supply on a 20th century grid are substantial. If the demand for electricity was reduced, those risks would subside.
The development of quantum computing has quietly been on the rise. These computing instances, in total, consume about 25kilowatts for super computers that require extreme refrigeration to drive their super-conductor-based processors at temperatures near absolute zero. The warmer weather loving neutral-atom computers operate around room temperature and use 7 kilowatts (or less) of power. When optimization tasks or simulations are sent to their quantum algorithms, these computers produce solutions at orders of magnitude faster and use a tiny fraction of the energy that a traditional datacenter would require.
Quantum computing, now, can significantly enhance AI (Generative AI) by its speed. Quantum computers are faster and deeper in data analysis and have now led to a new class of Generative AI called GenQAI (Generative Quantum AI) that can use quantum hardware to iterate complex problems and generate more human-like reasoning and intuition in AI.
Quantinuum, which is reported to be one of the world leaders in quantum technology, in November unveiled its Helios system, which has been described as the world's most accurate quantum computer. That quantum instance requires a less then 40 kilowatts of power, about the same as a single data center rack average AI Generative load and configuration. The company announced last week it was going public and would issue an IPO sometime in the first half of 2026.
With some clairvoyant disruption and a little bit of luck, we'll have quantum computing cottages humming their 4-dimensional power frugal song before we have natural gas caverns and poisonous landfill dirges to endure
