For the U.S., the stakes of this transition are uniquely high. As a primary hub for the global AI infrastructure boom, the U.S. is poised to capture a significant portion of the projected $3 trillion in data-center-related investments over the next five years, as projected by Moody’s. However, this leadership comes with a steep entry fee: massive demands on power grids and digital connectivity that require enormous spending before productivity gains ever hit the bottom line.
Фото: Kacper Pempel / Reuters
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The problem gets worse in pipelines. When you chain multiple transforms — say, parse, transform, then serialize — each TransformStream has its own internal readable and writable buffers. If implementers follow the spec strictly, data cascades through these buffers in a push-oriented fashion: the source pushes to transform A, which pushes to transform B, which pushes to transform C, each accumulating data in intermediate buffers before the final consumer has even started pulling. With three transforms, you can have six internal buffers filling up simultaneously.
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