They won't necessarily map out all the circuits but they will generally test them all with a tester to find wiring problems.

Becoming increasingly convinced that the pattern that will stick is not AI "integrated" into everything but personal agents. As in I will have one personal assistant that helps me in all of my tasks instead of using the little ones bolted on to every product.

Similar - had an HVAC tech out to diagnose mine (some intermittent electrical problem was killing thermostats randomly) and since it was intermittent they couldn't figure it out. I ended up using Gemini to narrow down a list of potential problem components and just replacing them all which fixed the issue.

Kind of a superpower to turn anyone with a bit of tech inclination and problem solving skills into an HVAC tech - not a very good one, but one with enough motivation to get the results you need

Same story, ended up just need to replace a fuse and clean out some filters.

I hate to be a "tech elitist" or whatever, but goddamn it seems like software is one of the most learning intensive careers you can pick. A little dabbling around the house has made me an amateur plumber/HVAC/handyman/gardener/etc. I should have gone into a trade, just for the comfort of having a skillset that doesn't need to be updated every 3 months. I guess my brain plasticity will thank me.

Kinda tired of being inundated with low quality AI slop absolutely everywhere.

Same - 13" macbook screen becomes less functional when you fill it with padding.

State of the art 7 months ago is good enough for a lot of use cases.

That was my thought. At my work, 7 months can be less time than it takes to get a project organized around a high-level plan. It sounds like nothing.

I suppose this is a more forward looking post though. It's about whoever gets to whatever is awaiting us in the future 7 months before the other.

And I guess the idea is is that there is this extreme inflection point in utility somewhere that makes it so getting there first gives you some incredible economic edge.

It might not exist though. Like either utility plateaus and its bubble crash of the century time or it just keeps going up but without any specific point where you can differentiate something.

Feels like that inflection point possibility passed a while ago since these models are starting to plateau in performance.

The GP is talking about recursive self-improvement.

What yes, it's clear by now it's way beyond the capacity of those AIs, and the odds are pretty good it's impossible to a large extent (but some limited version of it may be possible).

What makes you think they plateaued?

Exactly - for an average person's task, how different is AI today vs 7 months ago?

I think a lot of usage will move to the cheap open weight Chinese models once there is an incentive to do that. Everything below the highest end frontier models are becoming commoditized and I suspect the commodity segment will pass the "good enough" bar for most applications.

This seems true for our moment in time but looking forward I'm not sure how much it will stay that way. The LLMs will inevitably need to find a sustainable business model so I can very much see them becoming enshittified similar to google eventually making 2) and 3) more similar to each other.

An alternative business model is that you, or more likely your insurance, pays $20/mo for unlimited access to a medical agent, built on top of an LLM, that can answer your questions. This is good for everyone -- the patient gets answers without waiting, the insurer gets cost savings, doctors have a less hectic schedule and get to spend more time on the interesting cases, and the company providing the service gets paid for doing a good job -- and would have a strong incentive to drive hallucination rate down to zero (or at least lower than the average physician's).

The medical industry relies on scarcity and it's also heavily regulated, with expensive liability insurance, strong privacy rules, and a parallel subculture of fierce negligence lawyers who chase payouts very aggressively.

There is zero chance LLMs will just stroll into this space with "Kinda sorta mostly right" answers, even with external verification.

Doctors will absolutely resist this, because it means the impending end of their careers. Insurers don't care about cost savings because insurers and care providers are often the same company.

Of course true AGI will eventually - probably quite soon - become better at doctoring than many doctors are.

But that doesn't mean the tech will be rolled out to the public without a lot of drama, friction, mistakes, deaths, and traumatic change.

This is a great idea and insurance companies as the customer is brilliant. I could see this extend to prescribing as well. There are huge numbers of people that would benefit from more readily prescribed drugs like GLP-1s, and these have large portential to decrease chronic disease.

> I could see this extend to prescribing as well.

The western world is already solving this, but not through letting LLMs prescribe (because that's a non-starter for liability reasons).

Instead, nurses and allied health professionals are getting prescribing rights in their fields (under doctors, but still it scales much better).

It's a forcing function that ensures the middle layers of a vertically integrated stack remain market competitive and don't stagnate because they are the default/only option

This is the right take - there is a huge variation in "value per dollar" across AWS services. The base ones that solve hard problems like durable persistent state can be very much worth it. They tend to be the older ones.