• All these predictions are taken from Forbes/Rob Toews' "10 AI Predictions For 2025".

• For the 2024 predictions you can find them here, and their resolution here.

• You can find all the markets under the tag [2025 Forbes AI predictions].

• Note that I will resolve to whatever Forbes/Rob Toews say in their resolution article for 2025's predictions, even if I or others disagree with his decision.

• I might bet in this market, as I have no power over the resolution.

Description of this prediction from the article:
In 2023, the critical physical resource that bottlenecked AI growth was GPU chips. In 2024, it has become power and data centers.

Few storylines have gotten more play in 2024 than AI’s enormous and fast-growing energy needs amid the rush to build more AI data centers. After remaining flat for decades, global power demand from data centers is projected to double between 2023 and 2026 thanks to the AI boom. In the U.S., data centers are projected to consume close to 10% of all power by 2030, up from just 3% in 2022.

The demand for energy to power AI data centers is skyrocketing. Our energy systems are not prepared.

Image source: Semianalysis

Today’s energy system is simply not equipped to handle the tremendous surge in demand coming from artificial intelligence workloads. A historic collision between these two multi-trillion-dollar systems—our energy grid and our computing infrastructure—is looming.

Nuclear power has gained momentum this year as a possible solution to this Gordian knot. Nuclear represents an ideal energy source for AI in many ways: it is zero-carbon, available 24/7 and effectively inexhaustible. But realistically, new nuclear energy sources won’t be able to make a dent in this problem until the 2030s, given long research, project development and regulatory timelines. This goes for traditional nuclear fission power plants, for next-generation “small modular reactors” (SMRs) and certainly for nuclear fusion power plants.

Next year, an unconventional new idea to tackle this challenge will emerge and attract real resources: putting AI data centers in space.

AI data centers in space—at first blush, this sounds like a bad joke about a VC trying to combine too many startup buzzwords. But there may in fact be something here.

The biggest bottleneck to rapidly building more data centers on Earth is accessing the requisite power. A computing cluster in orbit can enjoy free, limitless, zero-carbon power around the clock: the sun is always shining in space.

Of course, plenty of practical challenges remain to be solved. One obvious issue is whether and how large volumes of data can be moved cost-efficiently between orbit and Earth. This is an open question, but it may prove solvable, with promising work underway using lasers and other high-bandwidth optical communications technology.

A buzzy startup out of Y Combinator named Lumen Orbit recently raised $11 million to pursue this exact vision: building a multi-gigawatt network of data centers in space to train AI models.

As Lumen CEO Philip Johnston put it: “Instead of paying $140 million for electricity, you can pay $10 million for a launch and solar.”

Lumen will not be the only organization taking this concept seriously in 2025.

Other startup competitors will emerge. Don’t be surprised to see one or more of the cloud hyperscalers launch exploratory efforts along these lines as well. Amazon already has extensive experience putting assets into orbit via Project Kuiper; Google has a long history of funding moonshot ideas like this; even Microsoft is no stranger to the space economy. Elon Musk’s SpaceX could conceivably make a play here, too.