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.

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iLemming 5 days ago | parent [-]

Raising, nurturing, training, and mentoring an expert mathematician is not cheap; it never was, perhaps the first time in history when we can witness that rule to change - spinning up a bunch of math-savvy agents, each smarter than Ramanujan maybe will get too cheap.

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high_na_euv 4 days ago | parent [-]

You dont have to raise them, someone already did it, you have to hire them

	▲	iLemming 4 days ago \| parent [-]
		You're oversimplifying the message I'm trying to convey. "you just hire them, someone already raised them" - treats mathematicians as a commodity stock rather than a flow. The conversation frames it as "mathematicians vs. RAM" - a cost comparison. But that's like comparing the cost of a GPS unit vs. a ship captain. The captain isn't expensive because they can calculate routes; they're expensive because they know when the route is wrong. AI makes the math cheaper but makes the mathematician more valuable, at least until true AGI genuinely surpasses human mathematical creativity - at which point we have much bigger economic questions than mathematician salaries. The topic on itself is quite interesting, and far complex than supply/demand norms. Even before AI, there was and both wasn't shortage of mathematicians - academic pure mathematics - there's a glut. High school teachers - people exist; but they won't work for teacher salaries. Applied math - acute shortage - quant finance, ML research, cryptography, pharmaceutical modeling - we don't have enough. NSA - always struggled to hire - private sector salaries pull people away. Interdisciplinary - mathematical biology, climate modeling, materials science - domains where math is the bottleneck but the job title isn't really "mathematician" - acute shortage.