> Jarred was a stinky manager. Poor communication, unrealistic expectations, low empathy, no experience. Just a total shit show

Are these claims false, though?

What you need is a loop. And if you try running an LLM in a loop with internet access, it will eventually use it.

If their business truly requires that to survice, then their business doesn't deserve to survive.

Like with most other things of this nature, the returns are diminishing, but ultimately it's for you to decide how much is enough.

And why is it important that people "add value to the society", whatever that even means when all needs are already met.

What it does change is the basic equation underlying capitalism as an economic system: a few people concentrate capital in their hands, but capital by itself is useless without labor, so they have to hire workers to produce something useful with all that capital that they own. The workers get a shit sandwich, comparatively speaking (given the amount of wealth they generate), but they do get something out of it. The system is stable overall because, while a better arrangement is possible, most people - even low-wage workers - have too much to lose to riot.

With AI that can do most work, the capital no longer needs labor. People who own all the robots can just have them produce whatever they need. Everybody else is then "economically redundant", and the whole system collapses because people aren't going to sit around and starve because there are no longer jobs to be had - and at this point they have nothing left to lose and everything to gain by rebelling and taking over the capital.

The increases still happen globally but mostly driven by developing countries.

At the end of the day, an LLM is just a very big mathematical function. That is, by definition, deterministic. A particular implementation might give up on determinism for the sake of higher efficiency, but it you want a deterministic LLM, it can absolutely be done.

For some people, fun is doing physics and mathematics. So they are going to keep doing that.

Things improve drastically however if you spin up a second session and ask it to adversarially review everything that the first session produces (this goes for everything: not just code, but also design, planning, and explanations).

This works even better if you use models from different families to do so.