The only people who are safe are those whose jobs depend in some way on their humanity. e.g. yoga teachers, bouncers, etc
It's not a zero sum game. You can have AI "senior engineers" working under humans building bigger things than we've been able to.
We also don't know where the capabilities of current AIs will plateau. The benchmarks aren't really telling the entire story. From my perspective of using the models there are certain axis where they're not making a lot of progress, like being able to have large accurate context on the scale that humans can. There are other dimensions where there is still a large gap between human capabilities and LLMs. It's true that relative to other areas (lessay chess) LLMs are more generalized but they are still not fully generalized (back to the chess example, LLMs are not good at chess).
Resources are, though. The planet cannot support a race of digital super-people, and us, and an continually growing economy.
It's the height of folly to think that, as things are going, we are going anywhere "good".
Once we've met our basic material needs, we're tending to consume things that are replicable with low marginal costs, and which do not interfere with the production of other goods. So maybe we can actually support a continually growing digital and entertainment economy, at least for a few more generations.
Maybe these mathematical contributions will also impact the efficiency and capabilities of our material production systems as well, which is another way to keep the economy growing.
I'm optimistic that we'll do more with our resources rather than trying to optimize for doing the same more efficiently with less resources.
It's a threat to everyone. UBI is the only way.
I would be willing to be proven wrong, but I doubt the ability of LLMs to give useful corrections in yoga much more than their ability to write useful code.
In relation to that, I guess my question becomes: if the same thing will happen in math research, who will write the ten page math proof prompts in the future?
What i see today is the opposite of what you see : product owners not knowing a thing about software engineering but being able to vibe code prototypes handed over to the dev team are rock stars.
They are closely followed by senior software developers having more of an architecture & design background than a low-level computer science background. Most businesses are looking for builders these days.
Where what you say may converge with my observation is that to be able to do to things such as proper database query optimization, even using AI assistance, you need to be able to understand the concepts of working memory set, cache misses etc...
I've found huge problems, like database servers being grossly underprovisioned (like, 60% cache hit, 4gb RAM server for a 700gb dataset with an 50gb circa hot data set). SSD were used and only latency was measured, so no one realized how problematic the situation was (including a consulting shop they hired to help them manage their DBs - backup, maintenance etc...).
However, having a high affinity with hardware is not a driver / computer science of hiring decisions from what i can see in the enterprise software world. But it would make sense for it to become the case within 10 years. I suspect that you work in a niche where performance optimization matters a lot.
Actually it's sad there are people out there dumb enough to believe knowing L1 cache is any different than knowing recipies when it comes to the story which jobs AI will take. I'm convinced by now it will be the jobs of those people believing such crap.
Calling notable conjectures that have been open for decades “low-hanging fruit” is an act of desperation. Most professional mathematicians couldn’t have proved those conjectures if their lives depended on it.
So, yes, AI is a big deal and we don’t know what it’s going to affect, but the goal of replacing everyone’s job is extremely ambitious and there’s a long way to go.
This has to be assessed separately for each kind of job.
Moravec must be at some level gratified things are arriving close to his predicted timeline.
There might be a thing beyond intelligence that we can't even conceive of.
The “absurd” dimension does not enter. This is a situation where you have no evidence at all.
In the absence of any information, the average (mean or median) is your best guess. Now where that average is, you have no idea.
> There might be a thing beyond intelligence that we can't even conceive of.
This statement already supposes there is a thing called “intelligence”. People have been pretending to measure this for more than a century. Modern thinking at least says what we call intelligence is not a single concept.
Most technologies level off sharply after bouts of boundless improvements.
In 1968 they thought we'd be flying to the moon by now but instead we're flying across the ocean in planes not that different from the 747 that existed back then.
> BY L. J. LANDER AND T. R. PARKIN
> A direct search on the CDC 6600 yielded:
27⁵ + 84⁵ + 110⁵ + 133⁵ = 144⁵
https://www.ams.org/journals/bull/1966-72-06/S0002-9904-1966...
It is a conjecture whether grinding it out on Lean is a difference in kind, rather than degree. I say degree. But it remains to be seen.