AI data centers are some of the largest consumers of electrical energy in the world of computing, and with gigawatt-sized projects currently in development, there is increased demand for sustainable means to power them. It just so happens that there's one solution that's entirely off-grid, with apparently zero emissions, and even generates the water required for cooling. Enter stage left, hydrogen fuel cells.
What might come as a surprise, though, is that it's only just started to be used in the machine learning sector, with t, utilising the services of hydrogen power company .
While as the solution to the power demands, I should imagine that if the Lambda-ECL collaboration turns out to be a successful project, then hydrogen fuel cells could become the preferred option. In terms of maintenance costs, they're much cheaper to keep running than anything with large-scale moving parts (e.g. gas
or steam turbines), plus it's relatively simple to just add more fuel cell modules, should you need more power.
The main stumbling block is the hydrogen. By itself, it's not expensive, nor is it costly to store. However, the infrastructure for the delivery of hydrogen is nowhere near as expansive and established as other fuels, particularly gas.
It's this aspect that is most likely to be the barrier that's preventing other AI firms from using fuel cells; depending on where one builds a new data center, it could be quicker and cheaper to use the local grid, rather than relying on regular shipments of hydrogen.
With Lambda willing yono arcade to bet on fuel cells, other AI firms are probably looking at it being an option, too. Ultimately, we'll all be winners if they make the jump.

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