Comment by nisten
7 hours ago
At the end of the day, if you look at almost any government, roughly 2/3 of expenses go towards healthcare and education things which, AI worlkflow are very likely continue offsetting a larger and larger percentage of the costs on.
Can we still have a financial crisis from all this investment going bust because it might take too long for it to make a difference in manufacturing enough automation hardware for everyone? Yes.
But, the fundamentals are still there, parents will still send their kids to some type of school, and people will trade good in exchange for health services. That's not going to change. Neither will the need to use robots in nursing homes, I think that assumption is safe to make.
What's difficult to predict change in is adoption in manufacturing, and repairs ( be that repairing bridges or repairing your espresso machine ) because that is more of a "3D" issue and hard to automate reliably (think about how many gpus today would it actually take to get a robot to reason out and repair a whole in your drywall), given that your RL environments and training data needs grow exponentially. Technically, your phone should have enough gpu performance to do your taxes with a 3B model and a bunch of tools, eventually it'll even be better than you at it. But to tun an actual robot with multiple cameras and stuff doing troubleshooting and decision making.... you're gonna need a whole 8x rack of gpus for that.
And that's what makes it now difficult to predict what's going to happen. The areas under the curve can vary widely. We could get a 1B AGI model in 6 months, or it could take 5 years for agentic workflows to fully automate everyones taxes and actually replace 2/3 of radiology work...
Either way, while theres a significant chance of this transition to the automation age being rough, I am overall quite optimistic given the fundamentals of what governments actually spend majority of their money on.
For the vast majority of US taxpayers, automating their taxes is feasible right now and the obstacles are political not technical.
The fundamentals are not there.
Talk to an educator. Education is being actively harmed by AI. Kids don’t want to do any difficult thinking work so they aren’t learning. (Literally any teacher you talk to will confirm this)
AI in medicine is challenging because AI is bad at systems thinking, citation of fact and data privacy. Three things that are absolutely essential for medicine. Also everything for healthcare needs regulatory approval so costs go up and flexibility goes down. We’re ten years away from any AI for medicine being cost effective.
Having an AI do your taxes is absurd. They regularly hallucinate. I 100% guarantee that if you do your taxes with AI you won’t pass an audit. AI literally can’t count. You’re be better off asking it to vibecode a replacement for TurboTax. But again the product won’t be AI it will be traditional code.
Trying for AGI down the road of an LLM is insanity sauce. It’s a simulated language center that can’t count, it can’t do systems thinking. It can’t cite known facts. We’re not six months away we’re a decade or a “cost effective fusion” distance (defined as perpetually 20 years in the future from any point in time)
There are at least six Silicon Valley startups working on AGI. Not a single one of them has published an architecture strategy that might work. None of the “almost AGI” products that have ever come out have a path to AGI.
Meh is the most likely outcome. I say this as someone who uses it a lot for things it is good at.