I bet MechaHitler was what really cinched the deal.

I can tell you for a fact that they can. However, even managing boilerplate and repetitive code is a huge benefit. Furthermore, these tools are great at combing through code bases and helping you find where you need to make changes in code. If you haven’t actually used these tools in a real project yourself then you don’t really know what they’re capable of.

Indeed, self hosing has to be the way forward.

It depends on the task and the specific LLM. My experience is that they can do a lot of things effectively nowadays, and they’re improving rapidly.

One huge impact mass FOSS adoption would have is that there would be a lot less software and hardware churn. Commercial nature of proprietary technology is the main driver for constant upgrade cycles we see. Companies need to constantly sell products to stay in business, and this means you have to deprecate old software and hardware in order to sell new versions of the product.

Windows 11 roll out is a perfect example. Vast majority of Windows 10 users are perfectly happy with the way their computer works currently, they’re not demanding any new features, they just want their computer to continue to work the way it does currently. However, Microsoft is ending support for Windows 10 and now they’re forced to buy a new computer to keep doing what they’ve been doing.

This problem goes away entirely with open source because there is no commercial incentive at play. If a piece of software works, and there is a community of users using it, then it can keep working the way it does indefinitely. Furthermore, in cases where a software project goes in a directions some users don’t like, such as the case with Gnome, then software can be forked by users who want to go in a different direction or preserve original functionality. This is how Cinnamon and Mate projects came about.

Another aspect of the open source dynamic is that there’s an incentive to optimize software. So, you can get continuous performance improvements without having to constantly upgrade your hardware. For most commercial software, there’s little incentive to do that since that costs company money. It’s easier to just expect users to upgrade their hardware if they want better performance.

I would argue that non technical software users would be far better off if they had the option to fund open source software instead of buying commercial versions. Even having to pay equal amounts, the availability of the source puts more power in the hands of the users. For example, building on the example of Gnome, users of an existing software project could also pull funds together to pay developers to add features to the software or change functionality in a particular way.

This is precisely what makes licenses like GPL so valuable in my opinion. It’s a license that ensure the source stays open, and in this way inherently gives more power to the users.

seems fine for me, here’s the content:

Mainland China is on track to surpass Taiwan in semiconductor foundry capacity by 2030, according to a report from Yole Group, underscoring Beijing’s progress in its push for chip self-sufficiency amid ongoing US tech restrictions. The mainland’s share of global foundry capacity is projected to reach 30 per cent by the end of the decade, up from 21 per cent in 2024, the French market research firm said. Taiwan is currently the market leader with a 23 per cent share last year, while mainland China is already ahead of South Korea at 19 per cent, Japan at 13 per cent and the US at 10 per cent. “Mainland China is rapidly becoming a central player,” Yole Group said, attributing the shift to Beijing’s intensified efforts to build a self-sufficient domestic semiconductor ecosystem since Washington launched a tech war that aimed to curb China’s progress in critical areas such as chips and artificial intelligence (AI). Beijing has doubled down on its “whole nation” approach to its self-sufficiency drive. The state-backed China Integrated Circuit Industry Investment Fund, known as the “Big Fund”, has successfully fostered the development of key companies such as Semiconductor Manufacturing International Corporation (SMIC) and Hua Hong Semiconductor, two of the country’s leading wafer foundries. Domestic fabs are set to play a bigger role over the next few years, according to the report, which said local chipmakers accounted for 15 per cent of foundry capacity in 2024. That share will be “significantly more” by 2030, the report said. Chinese chipmakers have been investing heavily in expanding their facilities to meet surging demand from sectors such as automotive and generative AI. China was expected to start three new fab construction projects this year, one-sixth of the world’s total, according to a report published in January by US-based industry association SEMI. China’s self-sufficiency strategy, along with expected demand from automotive and internet-of-things applications, would help boost capacity by 6 per cent for chips made with process nodes between 8 and 45 nanometres, SEMI added. Despite the projected gains, the mainland still trails Taiwan and South Korea in advanced process nodes, which are crucial for producing high-performance chips with greater transistor density. SMIC, China’s top foundry, had difficulty advancing its process nodes from 7-nm to 5-nm, Canadian research firm TechInsights said in a report last month. Two years after its 7-nm chip first appeared in a Huawei Technologies smartphone, “SMIC’s 5nm process node remains elusive,” TechInsights said. The report came after it looked into the chip used in Huawei’s new laptop with a foldable display, which also used 7-nm chips from SMIC. Meanwhile, global leaders Taiwan Semiconductor Manufacturing Company (TSMC) and Samsung Electronics are locked in a race to achieve mass production at the 2-nm node level. TSMC was expected to reach that level this year, while Samsung has reportedly planned to reach the same stage in early 2026.

Yup, it’s frustrating that there’s still no process that’s easy enough for a non techie to go through easily.

I think that’s exactly what’s gonna happen in the long run. Right now we’re in the hype phase of a new technology, but one the hype dies down we’ll start identifying use cases where the tech actually works well. At the same time the tech itself is going to mature, and people will figure out how to work with it effectively.

Yeah basically, a turn key solution where your machine gets wiped and imaged with a Linux distro that does all the basic stuff most people need would be an ideal solution. A good way to look at it would be making sort of a Linux based console for non technical users as opposed to a general purpose computer. Tech people want the latter, but non technical users just want a reliable tool that can reliably handle a few tasks.

Indeed, it kills me how much perfectly hardware is constantly thrown out because Windows refuses to run on it.

I think the trick has to be that somebody who has a bit of technical skill sets the laptop up initially. I did this for my mom a while back, and once I set it up once, it just worked from there on. Non technical users tend to have a fairly small set of things they need to do like check email, browser the web, and play media. Once that’s working, they never need to change anything. In fact, they don’t want to change anything because they get used to the workflow, and they’re comfortable.

It would be great if people set up community centres where people can bring their old laptops, and somebody switches them over to Linux for them.

Yeah, like how do they not see this project as being strategic for them.

related research

• https://www.sciencedirect.com/science/article/pii/S2666498425000031
• https://www.sciencedirect.com/science/article/pii/S2590332221002888

Have some humility and willingness to learn.

I have plenty of willingness to learn from people who have a clue on the subject.

I didn’t say it was the primary function.

You literally tried to argue that evolution doesn’t create complexity if there’s a more efficient path.th.

Then what about Darwin who literally said, “Natural selection is continually trying to economize every part of the organization.” Now please go and read some introductory texts on biology before trying to explain to me why Darwin is wrong. There’s so much going on when it comes to the thermodynamics of living systems and you’re clearly not ready to have a conversation about it.

Again, you’re showing a superficial understanding of the subject here. Natural selection selects for overall fitness, and efficiency is only a small part of equation. For example, plants don’t use the most efficient wavelength for producing energy, they use the one that’s most reliably available. Similarly, living organisms have all kinds of redundancies that allow them to continue to function when they’re damaged. Evolution optimizes for survival over efficiency.

You’re baseless assuming that hydrocephalus causes the brain to lose a substantial amount of its complexity.

Maybe read the actual paper linked there?

But hey neuroscience hasn’t really advanced at all since 1980 right? The brain is totally redundant right? There’s no possible way a critical and discerning person such as yourself could have been taken in by junk science, right?!!

What I linked you is a case study of an actual living person who was missing large parts of their brain and had a relatively normal life. But hey why focus on the actual facts when you can just write more word salad right?

I took issue with specific statements you made that stand apart from the rest of your comment.

You took issue with made up straw man arguments that you yourself made and have fuck all with what I actually said. Then you proceeded to demonstrate that you don’t actually understand the subject you’re debating. You might as well start believing in the astrology, crystals, and energy healing. At least those interests will make you seem fun and quirky instead of just a sad debate bro.

Im simply stating that you’re way off base when you claim that they appear to operate using the same principles or that all evidence suggests the human mind is nothing more than a probability machine.

I literally said these things, and you never gave any actual counter argument to either of them.

You’re betraying your own ignorance about neuroscience. The complexity of the brain is absolutely linked with its ability to reason and we have plenty of evidence to show that. The evolutionary process does not just create needless complexity if there is a more efficient path.

You’re betraying your ignorance of how biology works and illustrating that you have absolutely no business debating this subject. Efficiency is not the primary fitness function for evolution, it’s survivability. And that means having a lot of redundancy baked into the system. Here’s a concrete example for you of just how much of the brain isn’t actually essential for normal day to day function. https://www.rifters.com/crawl/?p=6116

This is such a silly statement especially when you’ve been claiming that both the brain and AI appear to work using the same principles.

There’s nothing silly in stating that the underlying principles are similar, but we don’t understand a lot of the mechanics of the brain. If you truly can’t understand such basic things there’s little point trying to have a meaningful discussion.

I don’t really care about your arguments concerning embodiment because they’re so beside the point when you just blowing right by the most basic principles of neuroscience.

That’s literally the whole context for this thread, it just doesn’t fit with the straw man you want to argue about.

A ruthless criticism of that exists includes the very researchers whose work you’re taking at face value.

Whose work am I taking at face value specifically? You’re just spewing nonsense here without engaging with anything I’m saying.

I suspect that something like LLMs is part of our toolkit, but I agree that this can’t be the whole picture. Ideas like neurosymbolic AI might be on the right track here. The idea here is to leverage LLMs at parsing and classifying noisy input data, which they’re good at, then use a symbolic logic engine to operate on the classified data. Something along these lines is much more likely to produce genuine intelligence. We’re still in very early stages of both understanding how the brain works and figuring out how to implement artificial reasoning.

LLMs and the human mind operate on categorically different principles.

A bold statement given that we don’t actually understand how the brain operates exactly and what algorithms that would translate into.

Where the straw man?

The straw man is you continuing to argue against equating LLMs with the functioning of the brain, something I never said here.

All the verbiage used to describe neural network models has little to do with how the brain actually works.

You appear to be conflating the implementation details of how the brain works with the what it’s doing in a semantic sense. There is zero evidence that all the complexity of the brain is inherent to the way our reasoning functions. Again, we don’t have a full understanding of how the brain accomplishes tasks like reasoning. It may be a lot more complex than what LLMs do, or it may not be. We do not know.

Finally, none of this has anything to do with the point I was actually making which is regarding embodiment. You decided to ignore that to focus on braying about tech companies and LLMs instead.

This completely understates the gulf between what we call AI and how the human brain actually works.

Way to completely misrepresent what I was actually saying. Nowhere was I suggesting that there isn’t a huge difference between the two. What I pointed out is that, while undeniably more complex, our brains appear to work on similar principles.

My only point was that the feedback loop from embodiment creates the basis for volition, and that what we call intelligence is our ability to create internal models of the world that we use for decision making. So, this is likely a prerequisite for any artificial system that has any meaningful intelligence.

Maybe try engaging with that instead of writing a wall of text arguing with a straw man.

All the evidence suggests that our own minds are also nothing more than probability engines. The reason we consider humans to be intelligent is because our brains learn to model the events in the physical world that are fed into our brains by the nervous system. The whole purpose of a brain is to try and keep the body in a state of homeostasis. That’s the basis for our volition. The brain gets data about about the state of the organism, and interprets it as hunger, pain, fear, and so on. Then it uses its internal world model to figure out actions that will put the body into a more desirable state. From this perspective, embodiment would indeed be a necessary component of human style intelligence.

While LLMs on their own are unlikely to provide a sufficient basis for a reasoning system, its not strictly impossible that a model trained on sensory data from a robot body it inhabits wouldn’t be able to build a representation of the world and its body that could be used as the basis for decision making and volition.

US threats mean nothing because the US has no bargaining power, and everybody knows this now.