AI Is Going Nuclear.


AI Is Going Nuclear.

We are running out of energy production and distribution. This has been taking place for over 20 years, but only now is the decline in new available energy really showing up. This is primarily because of the increased use by data centers and, of course, Artificial Intelligence (AI) data centers. But we are also seeing increases by individual users as more daily use of computers that is entertainment-based, but also AI-based, explodes. This all spells disaster for most of the Western world. China, however, has been consistently ramping up energy production and is the largest manufacturer of solar panels and user of solar energy. China is also ramping up nuclear energy, both fusion and fission. The US and Europe are rapidly falling behind.

Elon Musk and SpaceX, as well as his X.AI, have been very vocal about the need to move to orbital solar power and orbital AI data centers. This absolutely will take place, and faster than most could imagine. Yet this will massively help X.AI with more launch opportunities than any other AI company; it will be a massive disadvantage to Earth-based AI companies that must have a solution to current energy needs. They, and as of today, X.AI will need to find ways to expand energy production rapidly.

They are going to have to go nuclear.

Currently, data centers worldwide, many of which are dedicated to AI workloads, consume approximately 415 terawatt-hours (TWh) of electricity annually, accounting for about 1.5% of global electricity use as of 2024. In the United States alone, data centers used around 183 TWh in 2024, representing over 4% of the nation’s total electricity consumption—equivalent to the annual power needs of a country like Pakistan. AI-specific servers are a major contributor, with their electricity use estimated at 53 to 76 TWh globally in recent years, reflecting a sharp rise from just 2 TWh in 2017 to 40 TWh by 2023. For context, training a single large AI model like GPT-4 requires about 30 megawatts (MW) of power, while another prominent model consumed 50 gigawatt-hours (GWh), enough to power a city like San Francisco for three days. These figures highlight how AI’s current operations already rival the energy demands of entire industries.

This is a pressing need, and there is only one rapid solution for the next few years.

They are going to have to go nuclear.

Read Multiplex Members have been following my articles about the energy demands ahead and the battery agenda that is related for almost a decade here. In this article, I will surface the best scenarios that will play out and the investment insight one can draw from this. We have surfaced some companies that show the best path forward to help meet the demands ahead, with projections we have built based on a number of metrics.

It is very early days, and the potential investment opportunities are substantial. This issue is not going away fast, and we show you what is next.

This will be presented in a member-only article so we can explore these opportunities and the future with those who take this very seriously. I explore this in detail with insights not seen anywhere else. You will be among the few to know and adjust accordingly. If you are a member, thank you. If you are not yet a member, join us by clicking below.

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