

back before the days of hard drives being a standard thing :)


love to see it


I’ve been using LLMs pretty extensively. These tools are effective, they can solve hard problems, and they allow me to work on a wider range of tasks than could before.
But, they’re also jagged in terms of functionality. When you work with a human, you can learn what their core competencies are, and then if you give them a task that falls within that domain, you can be reasonably sure they’ll finish it correctly. That’s not the case with LLMs. It might do one task brilliantly, and a next similar task, it just shits the bed on. And since it has no understanding of the task in a human sense, it can’t self correct, learn or improve. All its doing is stringing tokens together based on probability.
So, you need a human in the loop to review everything that it’s doing. Reviewing everything the model outputs takes a lot of time, hence actual productivity gains aren’t all that significant. Having an LLM will allow a backend developer to work on the frontend with fairly low friction for example, but they’re still going to build stuff roughly at the same pace.
Companies that try to replace humans with LLMs will soon find that they end up with a whole bunch of code that doesn’t actually work, and they have no hope of fixing. The fact that LLMs can produce a lot of code very quickly is precisely the danger because nobody knows what that code is doing, and it’s almost certainly not correct.


That’s the beauty of Chinese state driven economy. The state can pour money into new technologies at a scale that no private business would ever do, which makes it possible to get to the point where new tech becomes commercially viable.
We’ll have to see what happens in the next three month when the real energy shortages hit https://www.reuters.com/commentary/reuters-open-interest/oil-market-clock-is-ticking-supply-crunch-looms-2026-05-21/
I still think this will be the big deciding factor. Europe can talk a big talk, but people have to eat. As Lenin put it, every society is three meals away from chaos. You saw how even Kid Starver tried to roll back sanctions on Russian energy, that tells you all you need to know about how bad the situation is.


I mean that fits given the US is a gerontocracy.
read all about it on your beloved wikipedia https://en.wikipedia.org/wiki/Democratic_centralism
literally every survey done in China by western orgs confirms that it is in fact a democracy, and one functioning better than any western attempt I might add


I mean we’ve seen how prices for Chinese solar and EVs dropped once production ramped up, I expect we’ll see the same with memory and eventually chips too.
Ah no worries, I made a community and a thread, tagged you both in it.
Did you see a recent interview with Karaganov where he basically says that the west does not understand what nuclear deterrence is, and that his view is that Russia will eventually end up striking a NATO country, first conventionally, and then if the message doesn’t get through then using a limited nuclear strike as a demonstration. It seems that’s where we’re headed at this point. https://www.youtube.com/watch?v=2Gd5jdl36cg
Incidentally, Mearsheimer agrees with Karaganov and also thinks that Russia has to reestablish nuclear deterrence https://www.youtube.com/watch?v=Dx7osj5gCmo


Basically, the actual problem is with the capitalist system of relations and how automation is inevitably applied by the capitalists to harm workers.


Same, AI haters really don’t realize just how far this tech has come in just the past year. I’ve had to work on frontend Js projects at work, and I’ve been lucky enough to avoid Js for most of my career. I have lots of experience programming, and I know how to structure applications, but I’m not familiar with Js stack, libraries, and syntax quirks. LLMs help me paper over all that and use it like any other language I’m already well versed in. Without LLMs, I would’ve had to spent literally months ramping up on Js ecosystem to do the work I’m doing now.


There are countless constructive and legitimate uses for AI/LLMs. This just another form of automation, and it works well for many tasks already. Other people in the thread have already given a ton of examples, so I don’t really have to reiterate them here. Meanwhile, practically all the criticisms of this tech actually boil down to problems with how it’s applied under capitalism.


Oh you can scan it, but as I recall they then force you to put your phone number in to finish the process.


That’s what google’s been using to lockout non official Android forks like GrapheneOS. You can click on the eye icon at the bottom to get the regular captcha though… for now.
I use these tools extensively, and they absolutely do not replace the need for a coder. The reality is that they’re fundamentally incapable of telling whether something is correct or not in the business sense. And Simply churning out a ton of wrong code really fast doesn’t actually help anybody.
They certainly can be a help for a developer. For example, I can fluently write code in any language now even if I’m not familiar with the stack or syntax. A skill that would’ve taken months of effort to build previously. But in terms of actual workflow, it’s not all that much faster because I still have to review what the tool is doing, and human comprehension is still the bottleneck in the whole process.