The "AI 2027" Scenario: How realistic is it?

What you get out of that being the consequence of disconnection is people being willing to accept a lot more before resorting to that than if the consequences were more mild.

It's the stick for motivating the ugly bags of mostly water.

The 1700s can't keep your electrical grid running let alone replace any of the parts burning out or failing. Anything more than a couple days of it would be at best Flowers For Algernon and more likely suicide for a computer.

Honestly, I’ve been thinking about this whole AGI timeline talk—like, people saying we’re going to hit some major point by 2027 where AI just changes everything. And to me, it feels less like a purely tech-driven prediction and more like something being pushed. Like there’s an agenda behind it, probably coming from certain elites or people in power, especially in the West, who see the current system and think it needs a serious reset.

What’s really happening, in my view, is a forced economic shift. We’re heading into a kind of engineered recession—huge layoffs, lots of instability—where millions of service and admin-type jobs are going to disappear. Not because the tech is ready in a full AGI sense, but because those roles are the easiest to replace with automation and AI agents. They’re not core to the economy, and a lot of them are wrapped in red tape anyway.

So in the next couple years, I think we’ll see AI being used to clear out that mental bureaucracy—forms, paperwork, pointless approvals, inefficient systems. AI isn’t replacing deep creativity or physical labor yet, but it is filling in the cracks and acting like a smart band-aid. It’ll seem useful and “intelligent,” but it’s really just a transition tool.

And once that’s done, the next step is workforce reallocation—pushing people into real-world industries where hands-on labor still matters. Building, manufacturing, infrastructure, things that can’t be automated yet. It’s like the short-term goal is to use AI to wipe out all the mindless middle-layers of the system, and the longer-term vision is full automation—including robotics and real-world systems—maybe 10 or 20 years out.

But right now? This all looks like a top-down move to shift the population out of the “mind” industries and into something else. It’s not just AI progressing—it’s a strategic reset, wrapped in the language of innovation.

> You don't have to learn to know -- you can reason from ideal priors.

This is kind of how math works. There are plenty of mathematical concepts consistent and true yet useless (as in no relation to anything tangible). Although you could argue that we only figured out things like Pi because we had the initial, practical inspiration of counting on our fingers. But mathematical truth probably could exist in a vacuum.

> A brain in a vat can't learn anything and it can't reason beyond the bounds of the accumulated knowledge it's already carrying.

It makes sense that knowledge and information are derived from primary data (our physical experience) yet the brain in a vat idea is still an interesting thought experiment (no pun intended). It's not that the brain wouldn't keep busy given the mind's ability to imagine, but it would likely invent a set of information that is all nonsense. Physical reality makes imagination coherent, yet imagination is necessary to make the leaps forward.

> Ultimately all information comes from "the universe." Where it comes beyond that, we don't know

That's an interesting assertion - knowledge and information are both dependent and limited by the universe and our ability to experience it, as well proxies for experience (scientific measurement).

Though information is itself an abstraction, like a text editor versus the trillion transistors of a processor - we're not concerned with each and every particle dancing around the room but instead with simplified abstractions and useful approximations. We call these models "the truth" and assert that the universe is governed by exact laws. We might as well exist inside a simulation in which we are slowly but surely reverse engineering the source code.

That assumption is the crux of intelligence - there is an objective truth, it is knowable, and intelligence can be defined (at least partially) as the breadth, quality, and utilization of information it possesses - otherwise you're just a brain in a vat churning out nonsense. Ironically, we're making these assumptions from a position of imperfect information. We don't know that's how it works, so our reasoning may be imperfect.

Information existing "beyond the universe" becomes a useless notion since we only care about information such that it maps to reality (at least as a prerequisite for intelligence).

A more troubling proposition is whether the reality of the universe exists beyond what can be imagined?

> How will it know how to do that? Like a perpetual motion machine -- where is the energy coming from?

I suppose once it's able to measure all things around it, including itself, it will be able to achieve "gradient ascent".

> Where will the training data to go beyond human come from?

I think its clear that LLMs are not the future, at least not alone. As you state, knowing all man made roads is not the same as being able to invent your own. If I had to bet, its more likely to come from something like AlphaFold - a Solver that tells us how to make better thinking machines. In the interim, we have tireless stochastic parrots, which have their merits, but are decidedly not the proto super intelligence that tech bros love to get hyped up over.

It was all over twitter, I don't know if its still there, but this guy is a performance artist