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You're right that we could already feed everyone with a different distribution of produced wealth. That part is not something that AI will change (although it would raise the resulting standard of living).

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.


> 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

This is a non sequitur. People being economically redundant doesn’t necessitate a system collapse. It assumes our existing systems can’t handle an increase (assuming we have economically redundant people today) in those who are economically redundant.

Capitalism defines who owns the means of production scoped to the definition of ownership in a particular governance structure. In the U.S., for example, full ownership gives people the right to produce as much as they want with rules in place to seize the rights of ownership if broken.

One rule of ownership is that taxes must be levied on the positive return of capital. This today is what helps funds the welfare state. The idea that the system collapses implies we won’t be able to scale this welfare state up which seems unlikely to me.

There’s already a deficit caused by welfare spending. An increase in abundance (of work, resources, etc.) can reasonably alleviate this if we consider the possibilities in removing inefficiencies within the government itself and their biggest cost drivers like public health.


100% agreee with this comment; this is basically where my mind is at right now.

IQ hasn't been increasing in developed countries for about three decades now. In fact, it has been declining in most.

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


Indeed. The Flynn effect has reversed.

These are all implementation details.

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.


We would care about having fun.

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


> We would care about having fun.

For even more people fun is TikTok, Snap, Instagram -> sounds like a collapse of a civilization to me if you increase the ratio even more towards dancing kids sharing their content non-stop with no added value to the society


It's not fun, it's a physiological addiction, because we learned enough about our brains to hack dopamine and reward cycles for profit. It's literal abuse.

yeah, a lot of people are just watching 1 video after another.

I'm genuinely curious as to what you're working on that you find 4B models good enough. I wouldn't even let a 27B model code, never mind supervising smaller models.

At the moment I'm still doing shakedowns, so Typescript games compilation with a menu that has 4 games and retro artwork.

This seems to be a good example because things like the menu, high score boards etc are common, but the games are distinct. Then there's the artwork which requires decisions on look, and for coordinating.

The Qwen 4B model is multimodal so part of the AC is to view the output - I've a robust anti AI-look QA chain for that I've been using elsewhere, e.g. no floating parts, consistency, obvious missing fingers etc etc.

The longer term plan is to do some llama.cpp refactors specifically for some target hardware I have and implementing slightly different novel architectures I'd like to try (one I did already targeted CPU inference, which I did using 3 agents with specific roles; main planner, QA for planner, and benchmarking/environment handling)

The implementation was 85% of the speed of the original maxed out on my hardware but performance scaled with CPU core count whereas the original implementation plateaued. Unfortunately the break even mark seemed to be around 30 - non HT - threads.

I suppose I should look at that one again, since the increase in cores did not linearly drop off performance e.g. due to memory contention.


Never trust a single session.

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.


Problem is where to stop. Open a 3rd session? Are you sure the 4th iteration is mostly correct? Let’s try a fifth now…

I have, on a lark, reached 20 to 30 adversarial sessions a few times. For some tasks, the sessions will just never converge on anything that yet another session won't find fault with, recommending an alternative already ruled out by another session. Even if all the reasoning in between was documented, the new sessions will endlessly claim to find flaws in past reasoning.

You tell it, "let's brainstorm, don't implement anything yet". Then you talk about what you want to build and hammer out all the corner cases. Then you tell it "now do that".

I have something like this in my default rules which Claude has consistently always loaded before doing any work. Works really well!

It's touted as "hard science fiction" but it's riddled with this kind of stuff.

For black holes it is quite literal tho.

https://github.com/yt-dlp/yt-dlp is generally where the most up-to-date workarounds for Google's attempts to block downloads are.

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