John Koomey discusses historical precedents like the end of Dennard scaling to predict how the tech industry will optimize AI computing efficiency.
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“Between those various, ah, improvements that you can get beyond just shrinking transistors and making things closer together, there's orders of magnitude possibility for improving efficiency, and so my sense is that the, you know, the focus has been basically building out AI infrastructure and while there was some improvement, and you can see it in the NVIDIA chips over time, there's some improvement. Efficiency was not the major focus, because these constraints that you've been talking about haven't been as proximate. So people weren't really focused on it. And this is very similar to that year, 2000 to 2005 situation where people were just putting in as much infrastructure as they could. And then they said, oh my God, you know, we've doubled electricity use. Maybe we better focus on this. And that's what I think is likely to happen here as well, is that the industry will actually really focus on this in a way that they haven't yet.”
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