Re: Well DUH ! AI People Finally Realize They Can Ditch Most Floating-Point for Big Ints

On 10/13/24 5:15 AM, Richard Kettlewell wrote:

"186282@ud0s4.net" <186283@ud0s4.net> writes:

https://techxplore.com/news/2024-10-integer-addition-algorithm-energy-ai.html

[...]

   The default use of floating-point really took off when
   'neural networks' became popular in the 80s. Seemed the
   ideal way to keep track of all the various weightings
   and values.
>
   But, floating-point operations use a huge amount of
   CPU/NPU power.
>
   Seems somebody finally realized that the 'extra resolution'
   of floating-point was rarely necessary and you can just
   use large integers instead. Integer math is FAST and uses
   LITTLE power .....

 That’s situational. In this case, the paper isn’t about using large
integers, it’s about very low precision floating point representations.
They’ve just found a way to approximate floating point multiplication
without multiplying the fractional parts of the mantissas.

   They need to take it further - integers instead
   of ANY floating-point absolutely anywhere possible.
   The greenies have begun to freak over the sheer electric
   power required by "AI" systems. It IS rather a lot. It's
   getting worse than even bitcoin mining now. Judging by
   the article, a large percentage of that energy is going
   into un-needed floating-point calx.