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TechNewsWorld columnist Rob Enderle argues that local resistance to large data centres and pressure on memory supplies could push more AI processing towards businesses’ own servers and devices.
Why it mattersHis proposed alternatives include smaller models, quantisation and better use of existing hardware, rather than simply building more capacity. These are the columnist’s analysis and forecasts, not confirmed outcomes. Still, it is a useful argument about what happens when the AI build-out meets limits on power, space and hardware costs.
Discuss: If AI infrastructure faces tighter limits, should the industry prioritise smaller models running locally, or keep investing in ever-larger data centres?
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