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From: Pancho <Pancho.Jones@proton.me>
Newsgroups: comp.os.linux.misc
Subject: Re: Well DUH ! AI People Finally Realize They Can Ditch Most
 Floating-Point for Big Ints
Date: Sun, 13 Oct 2024 14:23:25 +0100
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On 10/13/24 13:25, The Natural Philosopher wrote:
> On 13/10/2024 10:15, 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.
>>
> Last I heard they were going to use D to As feeding analog multipliers. 
> And convert back to D afterwards. for a speed/ precision tradeoff.
> 

That sounds like the 1960s. I guess this idea does sound like a slide rule.