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Professor Tabarrok uncritically praises the report, which might lead to the conclusion that either human intelligence or moral standards are "falling rapidly".
All were working alongside me, a self-taught programmer making websites.
I've long thought that there's an oversupply of smart people in the world but for the field of software development, which was hiding that fact by soaking all of them up.
If SDE is collapsing as a field, a whole bunch of people who thought their intelligence and credentials guaranteed them a comfortable life are in for a shock.
Even if we accept your precondition as true, that SWEs contain multitudes of smart people who will jump to other industries, I don't think the conclusion holds.
In the US at least, SWEs are among the most entrepreneurial industry members. They'll bring that attitude to whatever their new industry is. I think there will be an explosion of new startups in different areas, and we'll Jevons Paradox our way forwards.
https://www.oecd.org/en/publications/education-at-a-glance-2...
It's generally true that the rarer something is the more valuable that is, but only if there are enough potential buyers of the thing that can recognize it. If there is an ever-decreasing amount of intelligence there is probably an ever-increasing amount of stupidity - so will the stupid be smart enough to reward the intelligent with high paid positions?
What I suppose is actually that human intelligence will become more monetizable, by allowing those with it to better take advantage of their unrecognizable ability. But only if the interlocking systems of humanity do not fall apart and destroy the world due to there not being enough intelligent people left to make things work, as per various works of science fiction on the subject.
When asked about how one might attain social mobility in such a society, where the intrinsic value of our intelligence and ability to do labor is gone, I unironically respond with "be hot".
Where?
What's your definition of "rapidly"?
I could see an argument for price of human intelligence going down - we're essentially in a global stagflation - which feels like a recession (sometimes moreso) even if it isn't technically one...
Rapidly? I think we have different definitions, or you're only looking in a niche.
I'd also argue that global stagflation doesn't yet have anything to do with AI. My crystal ball doesn't work. Things could change quickly. But I don't see any evidence now.
What about the cost? Inference looks like a viable business model for those operators that have access to SOTA model and serving infrastructure, but the investment required to have it is enormous, and appears to be never-ending, because if an operator stops investing aggressively, its model and serving infrastructure quickly become non-competitive, and customers will quickly leave for alternatives.
The 20 euros GPT plan with GPT 6 Luna (and Astra for doing the tough stuff) and OpenCode Go (8 euros) offer me both way more intelligence and tokens than spending 400 euros just at the beginning of the this summer did.
Today I worked two hours with GPT 6 Luna, have been very productive tackling some hard stuff and...my weekly usage went from 57% to 56%?
You really don't need to use the strongest model for everything. And even chinese open models are effectively few months old sota. You can use mimo 2.6 or DS 4.1 flash on 8 $/months OpenCode and barely ever have to worry about consumption.
What I don't know, and was asking about, is whether the cost of providing that service is also falling rapidly, including the cost of training.
At some point this will probably happen, but we’re not quite there yet.
To take an intuition: there are lots of problems that are easier to pose and to check than they are to solve, in mathematics.
Not necessarily. https://arxiv.org/html/2609.26457v1
In the age of AI, human super-intelligence, is extremely valuable. But yeah, just being intelligent? Not so much.
Just to illustrate, many have complained that big AI labs "buy" startups only because they want to acqui-hire the Stanford/CalTech/MIT PhDs who started it. Then they pretty much $#!t-can the rest of the people who were, to be fair, mostly just run of the mill UTexas/Umichigan/UofwhateverState TF/PyTorch monkeys. But the point is that in the old days, the second tier guys would have made out like bandits as well.
I think that was, kind of, the start of human intelligence becoming a winner take all game. The AI's only need to learn the latest and greatest from one person before they can leverage that value everywhere. And business is not likely to care too much about who that person is. They will care even less about the people who are not that person.
Source, please! I'm a machine learning layperson but how can this not be overfitting?
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