It's also less frustrating to organize world wide ram production and logistics than to deal with a single mathematician.
Constantly sitting around trying to solve problems that nobody has made headway on for hundreds of years. Or inventing theorems around 15th century mysticism that won't be applicable for hundreds of years.
Now if you'll excuse me I need to multiply some numbers by 3 and divide them by 2 ... I'm so close guys.
I don't know, I think if you weighed up the costs of AI related datacentre spend vs. the average mathematics academic's salary you could come to a different conclusion.
It's also less frustrating to organize world wide ram production and logistics than to deal with a single mathematician.
Constantly sitting around trying to solve problems that nobody has made headway on for hundreds of years. Or inventing theorems around 15th century mysticism that won't be applicable for hundreds of years.
Now if you'll excuse me I need to multiply some numbers by 3 and divide them by 2 ... I'm so close guys.
The comment feels a bit like Verdex may have dated a mathematician at some point and it went sour.
I don't know, I think if you weighed up the costs of AI related datacentre spend vs. the average mathematics academic's salary you could come to a different conclusion.
Doubt it. You have to pay these mathematicians once and then you can deploy to millions of sites.
But not everyone has to pay mathematicians, like RAM :-)
At the same time, processing is much cheaper than memory
Without memory you have no data to compute on. Memory and compute scaling only makes sense in tandem.
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