Elon Musk

Most of the time, what you're doing is engineering, not coming up with a fundamentally new algorithm.

I somewhat disagree with the AI companies that are C-corps or B-corps, trying to generate profit as much as possible, or revenue as much as possible, saying they're labs.

They're not labs.

Lab is a quasi-communist thing at universities.

They're corporations, literally.

Let me see your incorporation documents.

Oh, okay, you're a BRC corp, whatever.

And so I actually much prefer the word engineer than anything else.

The vast majority of what we've done in the future is engineering.

It rounds up to 100%.

Once you understand the fundamental laws of physics, and not that many of them, everything else is engineering.

So then what are we engineering?

We're engineering to make a good mind of the AI debugger to see where it said something, it made a mistake, and trace the origins of that mistake.

so just like you know you can do this obviously with uh heuristic programming if you have like c plus plus whatever you know step through the thing and you can you can jump you can you can jump across into you know whole files or functions what are subroutines and or you can draw eventually drill down right to the exact line where you perhaps did a single equals instead of double equals or something like that yeah figure out where the bug is um so um

It's harder with AI, but it's a solvable problem, I think.

Also, I'm a little worried that there's a tendency...

I have a theory here that if simulation theory is correct, that the most interesting outcome is the most likely because simulations that are not interesting will be terminated.

Just like in this version of reality, on this layer of reality, if a simulation is going in a boring direction, we stop spinning off and on.

We terminate the boring simulation.

Yeah.