[cdata]

We are living in a ZIRP-like era where builders at the fastest pace layer have misattributed their velocity to exponential gains in model capability. In fact, they are surfing on decades of careful effort to build a robust foundation of highly reusable software libraries.

This strategy will seem to work really well until the economy that enabled that foundation to form is hollowed out. Then, there will be a reckoning (but we will have no choice but to march forth from there).

[patates]

It's not just software libraries. Specs, applications (the browser!), expectations, device integrations, operating systems, etc. So much that starting from scratch seems impossible.

I'm not agreeing or disagreeing with you, but my brain cannot comprehend how machines can advance such interconnected systems while keeping humans in focus.

Perhaps I shouldn't have watched the Animatrix again.

[justinai6]

Same! Animatrix is just so so so good and 2023 - 2026 I just keep on trying to keep "life" in context. ;)

[andai]

Well all we have to do is minimize animosity and ensure peaceful relations.

We're good at that, right?

[solenoid0937]

> This strategy will seem to work really well until the economy that enabled that foundation to form is hollowed out. Then, there will be a reckoning (but we will have no choice but to march forth from there).

There will only be a reckoning if models don't get much better.

If they do get much better you can just have them refactor, fix bugs in, or replace the existing codebase.

The concept of tech debt is sort of meaningless if you anticipate intelligence gains in models to continue.

[chairmansteve]

"but we will have no choice but to march forth from there".

If you haven't seen it, I think you would appreciate the film Margin Call.

[gbro3n]

This is a great point. LLMs can't speed up human decision processes and alignment.

[DoctorOetker]

Not entirely sure about that.

Its already speeding up human decision processes, and while ethics / alignment may seem unique to humans we also see normative expressions in monkeys or apes (like the experiment where one is given a grapes, the other cucumber).

A lot of ethics is based on symmetry: symmetric relations, equal rights, equal voting power, ... symmetries sound rather mathematical if you ask me, and decision structures have historically been pressed towards democracy (or at least depiction of it). One could say that modeling humanity as an empire with a king, ignores the will of sometimes hungry farmers with pitchforks. To prevent the occasional "implicit democracy" (royaltycide), it turned out in the interest of the king to recognize the powers of those farmers, and to formalize it in the decision making process. Or at least pretend to.

I believe machines will be able predict the preference sentient creatures would prefer in terms of decision structures, but I don't believe it will be able to predict (without human exposition) those novel preferences that stem not from sentience but from being specifically human properties (i.e. irritants which are quasi universal for humans, etc.), some of them humans know how to make predictions for (we can run expensive simulations modeling what happens when protein X is exposed to substance Y, and then make heuristic predictions of the effect on a full human in a realistic environment). So at a fundamental level I agree: machine learning models are not guaranteed to help much in predictions concerning entirely unexplored territory, neither by humans nor by natural selection. But it will definitely be capable of replacing the average human job, which doesn't involve consensual exploration outside of the homeostasis required in the implicit job description, that seems entirely automatable, regardless if its physics, mathematics, (harder than computer science), let alone programming.

It won't be able to magically systematically correctly predict out of distribution datapoints, it could only explore it like humans could by trial and error.

[noman-land]

How many years do you think we can coast on that foundation. 20?