Ground level parking isn’t really all that expensive, not unless you have very high land values. It does cost far more if you want to put up a multistory parking garage; from past reading, that’s maybe $30k-$50k per spot (though I’d still personally favor a parking mandate in that case, as otherwise you get people turning the street into a parking lot, which is awful for everyone, and parking illegally all over).

In the picture shown, though, it looks like townhouse-type stuff, two stories, not high density housing, so the land value probably isn’t that insane, and they can do ground level parking instead of multistory parking.

I didn’t have any problem with the guy in the first picture either, but I would be willing to bet that many of us are viewing this thread using very different display brightness/contrast settings.

I’m currently looking at it on a laptop. My laptop has no light sensor with automatic brightness adjustment, and I use the laptop in a wide range of environments, so I need to use brightnessctl on Linux to fiddle the brightness, usually between about 10% and 60%. It’s not like there’s one single “correct brightness” when I’m in a ton of different environments.

My desktop’s monitor doesn’t have a light sensor with automatic brightness adjustment either.

There’s probably some way to go get a brightness sensor and a daemon to auto-fiddle the thing on the desktop — webcams, which often have automatic brightness adjustment themselves, aren’t great for this. But, well, I never got around to it.

Your display likely has some sort of brightness/contrast setting.

If you’re playing this movie on a computing device, the video player software likely also has adjustment settings at the software level. I use mpv on Linux to watch most video, and there, by default, 1 and 2 are contrast, 3 and 4 brightness, and 5 and 6 gamma.

1. Obtain bottle of different size.

2. Pour bottle of undesirable height into new bottle.

3. Label new bottle.

Though to be fair, Amazon’s scale is very large, so it’s worth it to spend a lot on automation. They’ve done a lot with robots before. 14k isn’t as many as it might sound, at their scale.

kagis

https://www.nytimes.com/2025/10/21/technology/inside-amazons-plans-to-replace-workers-with-robots.html

Amazon’s U.S. work force has more than tripled since 2018 to almost 1.2 million. But Amazon’s automation team expects the company can avoid hiring more than 160,000 people in the United States it would otherwise need by 2027. That would save about 30 cents on each item that Amazon picks, packs and delivers to customers.

Executives told Amazon’s board last year that they hoped robotic automation would allow the company to continue to avoid adding to its U.S. work force in the coming years, even though they expect to sell twice as many products by 2033. That would translate to more than 600,000 people whom Amazon didn’t need to hire.

Why is so much coverage of “AI” devoted to this belief that we’ve never had automation before (and that management even really wants it)?

I’m going to set aside the question of whether any given company or a given timeframe or a given AI-related technology in particular is effective. I don’t really think that that’s what you’re aiming to address.

If it just comes down to “Why is AI special as a form of automation? Automation isn’t new!”, I think I’d give two reasons:

It’s a generalized form of automation

Automating a lot of farm labor via mechanization of agriculture was a big deal, but it mostly contributed to, well, farming. It didn’t directly result in automating a lot of manufacturing or something like that.

That isn’t to say that we’ve never had technologies that offered efficiency improvements across a wide range of industries. Electric lighting, I think, might be a pretty good example of one. But technologies that do that are not that common.

kagis

https://en.wikipedia.org/wiki/Productivity-improving_technologies

This has some examples. Most of those aren’t all that generalized. They do list electric lighting in there. The integrated circuit is in there. Improved transportation. But other things, like mining machines, are not generally applicable to many industries.

So it’s “broad”. Can touch a lot of industries.

It has a lot of potential

If one can go produce increasingly-sophisticated AIs — and let’s assume, for the sake of discussion, that we don’t run into any fundamental limitations — there’s a pathway to, over time, automating darn near everything that humans do today using that technology. Electrical lighting could clearly help productivity, but it clearly could only take things so far.

So it’s “deep”. Can automate a lot within a given industry.

No problem. Yeah, it’s an invaluable off-site resource that new users don’t get informed about. Indexes all of the Threadiverse instances, whereas any given instance can only search the communities that are local or at least one local user has subscribed to.

https://lemmyverse.net/communities?query=networking&order=active_month

The world was full of flat surfaces that did not yet have an Android-platform device driving a screen displaying advertisements on them.

Training a model to generate 3D models for different levels of detail might be possible, if there are enough examples of games with human-created different-LOD models. Like, it could be a way to assess, from a psychovisual standpoint, what elements are “important” based on their geometry or color/texture properties.

We have 3D engines that can use variable-LOD models if they’re there…but they require effort from human modelers to make good ones today. Tweaking that is kinda drudge work, but you want to do it if you want open-world environments with high-resolution models up close.

Take-Two’s CEO doesn’t think a Grand Theft Auto built with AI would be very good | VGC

Sounds fair to me, at least for near-term AI. A lot of the stuff that I think GTA does well doesn’t map all that well to what we can do very well with generative AI today (and that’s true for a lot of genres).

He added: “Anything that involves backward-looking data compute and LLMs, AI is really good for, and that and that applies to lots of things that we do at Take-Two. Anything that isn’t attached to that, it’s going to be really, really bad at…. there is no creativity that can exist, by definition, in any AI model, because it is data driven.”

To make a statement about any AI seems overly strong. This feels a little like a reformed “can machines think?” question. The human mind is also data-driven; we learn about the world, then create new content based on that. We have more sophisticated mechanisms for synthesizing new data from our memories than present LLMs do. But I’m not sure that those mechanisms need be all that much more complicated, or that one really requires human-level synthesizing ability to be able to create pretty compelling content.

I certainly think that the simple techniques that existing generative AI uses, where you just have a plain-Jane LLM, may very well be limiting in some substantial ways, but I don’t think that holds up in the longer term, and I think that it may not take a lot of sophistication being added to permit a lot of functionality.

I also haven’t been closely following use of AI in video games, but I think that there are some games that do effectively make use of generative AI now. A big one for me is use of diffusion models for dynamic generation of illustration. I like a lot of text-based games — maybe interactive fiction or the kind of text-based choose-your-own-adventure games that Choice of Games publishes. These usually have few or no illustrations. They’re often “long tail” games, made with small budgets by a small team for a niche audience at low cost. The ability to inexpensively illustrate games would be damned useful — and my impression is that some of the Choice Of games crowd have made use of that. With local computation capability, the ability to do so dynamically would be even more useful. The generation doesn’t need to run in real time, and a single illustration might be useful for some time, but could help add atmosphere to the game.

There have been modified versions of Free Cities (note: very much NSFW and covers a considerable amount of hard kink material, inclusive of stuff like snuff, physical and psychological torture, sex with children and infants, slavery, forced body modification and mutilation, and so forth; you have been warned) that have incorporated this functionality to generate dynamic illustrations based on prompts that the game can procedurally generate running on local diffusion models. As that demonstrates, it is clearly possible from a technical standpoint to do that now, has been for quite some months, and I suspect that it would not be hard to make that an option with relatively-little development effort for a very wide range of text-oriented games. Just needs standardization, ease of deployment, sharing parallel compute resources among software, and so forth.

As it exists in 2025, SillyTavern used as a role-playing software package is not really a game. Rather, it’s a form of interactive storytelling. It has very limited functionality designed around making LLMs support this sort of thing: dealing with a “group” of characters, permitting a player to manually toggle NPC presence, the creation of “lorebooks”, where tokens showing up trigger insertion of additional content into the game context to permit statically-written information about a fictional world that an LLM does not know about to be incorporated into text generation. But it’s not really a game in any traditional sense of the word. One might create characters that have adversarial goals and attempt to overcome those, but it doesn’t really deal well with creating challenges incredibly well, and the line between the player and a DM is fairly blurred today, because the engine requires hand-holding to work. Context of the past story being fed into an LLM as part of its prompt is not a very efficient way to store world state. Some of this might be addressed via use of more-sophisticated AIs that retain far more world state and in a more-efficient-to-process form.

But I am pretty convinced that with a little work even with existing LLMs, it’d be possible to make a whole genre of games that do effectively store world state, where the LLM interacts with a more-conventionally-programmed game world with state that is managed as it has been by more traditional software. For example, I strongly suspect that it would be possible to glue even an existing LLM to something like a MUD world. That might be via use of LoRAs or MoEs, or to have additional “tiny” LLMs. That permits complex characters to add content within a game world with rules defined in the traditional sense. I think I’ve seen one or two early stabs at this, but while I haven’t been watching closely, it doesn’t seem to have real, killer-app examples…yet. But I don’t think that we really need any new technologies to do this, just game developers to pound on this.

That Slate Truck thing had the right idea. Make the computer a replaceable thing, not something tied to the lifetime of the car. The lifespan of a smartphone is typically a lot less than the lifespan of a car.

This is a 500W charger with one port that can do 240W.

https://www.amazon.com/UGREEN-Charging-Station-Temperature-Space-Saving/dp/B0DL5L1ZLH

It’s quite large and heavy. 2.2kg (4.9 lbs).

There are going to be some practical limitations on what people are going to be willing to carry for portable stuff.

Not only is the RADV for Llama.cpp past processing faster than the official (former) AMDVLK Vulkan driver but also ROCm.

I assume that they mean “prompt processing”. That was one test for one person, but that seems like what I’d lead with, as it seems pretty significant for some use cases.

I think that there’s maybe a need for something like this, but if it’s not just going to be a one-off research project — which maybe this is, which is okay — I’d very visibly version the testset and its results from the get-go. You’re going to want to add more tests to it over time, and it’ll affect change test results, and you’re going to want to be able to reproduce results.

although I concede that better metrics would be hard to find.

Maybe get ALPRs to start logging bumper stickers. :-)

Aside from a MAGA hat, there is likely no object that feels more emblematic of US president Donald Trump’s return to the White House than the Tesla Cybertruck.

If Musk had been able to attract the typical F-150 owner to the Cybertruck, then the Cybertruck wouldn’t have flopped, and I bet that the F-150 is a whole lot more correlated with voting Trump than the Cybertruck is.

IIRC from past reading, in terms of voting correlation by party, the Toyota Prius is the “most Democratic” vehicle and the Ford F-150 is the “most Republican” vehicle.

kagis

Nope (or at least, not by the metrics chosen here), but I’m close.

https://www.businessinsider.com/car-models-owned-by-republicans-democrats-american-politics-jeep-2024-10

To get a sense of how our rides reflect our political leanings, we compared 1.7 million vehicles listed on CarGurus with the results from the 2020 presidential election. We included only counties that were strongly red or blue — those where either Donald Trump or Joe Biden won by at least 19 percentage points. Then we placed every car on a political spectrum from reddest to bluest.

According to this, which excludes more-politically-mixed counties from the dataset, the vehicle most-correlated with voting Trump in 2020 at a county level is the Jeep Wrangler, followed by the Jeep Gladiator, followed by the Chevrolet Silverado 1500 (which I assume is the Chevy analog of the F-150), followed by the Ford F-150.

The vehicle most-correlated with voting Biden (at a county level) was indeed the Toyota Prius.

EDIT: To be fair, the article author is probably partly talking about Musk’s association with Trump and the Cybertruck coming out about that time, and he’s talking about the 2024 election specifically, but I think that the Cybertruck is maybe high-media-visibility, but doesn’t have all that much to actually do with voting Trump.

On AMD hardware, I moved from rocm 6 to 7 and the associated amdgpu driver release and saw pretty noticeable inference performance improvements on an RX 7900 XTX with llama.cpp (as of rocm 7.0.2, AMD has a Debian Trixie build, BTW).

But I imagine that AMD/Nvidia, specific hardware, application, and settings are probably all major inputs into that. YMMV.

EDIT: Not to mention model being run.

Inclusion of Erowid in the training corpus had initially seemed like a good idea.

The prediction comes from OpenAI employee Leopold Aschenbrenner, who claims AI will “reach or exceed human capacity” by 2027.

I suppose that it depends on the metric you’re using. There are some tasks at which humans are outperformed now.

But I am pretty comfortable saying that come January 2027, the great bulk of things that humans do will continue to not be able to be done by existing AI.

We aren’t going to just tweak an existing LLM somewhere slightly, throw a bit more hardware at it, and get general intelligence.