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Integer addition algorithm could reduce energy needs of AI by 95% (techxplore.com)

submitted 1 month ago by floofloof@lemmy.ca to c/technology

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[–] technocrit@lemmy.dbzer0.com 69 points 1 month ago* (last edited 1 month ago) (2 children)

This is an extremely misleading headline.

From the abstract:

... applying the L-Mul operation in tensor processing hardware can potentially reduce 95% energy cost by element-wise floating point tensor multiplications and 80% energy cost of dot products.

In other words... This method of computation could save 95% of the energy spent on floating point multiplication (and save 80% on dot products)... Not 95% of total energy.

It's an improvement (potentially), but I don't see any analysis of how this would impact total energy.

[–] AndrasKrigare 11 points 1 month ago

I'd say it's not just misleading but incorrect if it says "integer" but it's actually floats.

[–] IrritableOcelot 5 points 1 month ago

Good point. Though, the vast majority of ML training and use is tensor math on floating points, so largely dot and cross products, among other matrix operations.