On cars it can of course identify the make and model but it’ll also catalog things like bumper stickers and custom rims for that car.
I think the bill covers that. It additionally states that it’s anything that “identifies, locates, and tracks a vehicle through the license plate or other persistent visual identifier of the vehicle”
Haven’t ever had anything like this on my Pixel running Graphene. Seems more like some odd corruption of OS files than an implementation bug in the OS’s code itself to me.
While it’s kind of a ban, to be extremely clear, this is not a direct ban!
This would prohibit federal agencies from using ALPRs or accessing data from them, and it would block federal funding for ALPR systems, but locally-funded systems would still be allowed:
https://www.gadgetreview.com/bernie-sanders-aoc-and-jeff-merkley-just-introduced-the-ban-flock-act
There’s about as much political will for this as dissolving the US.
Absolutely not true lmao
“dissolving the US” is a pretty generic and nonspecific term, but I think support for states seceding, effectively “dissolving” the union, would be a fair comparison? So in that case, while some individual states have had support rise, just 18% of Americans support their state seceding from the USA, and that’s down by 6% from 2024:
https://www.newsweek.com/map-shows-states-where-support-for-seceding-from-us-is-rising-11515967
Nearly half of Americans support abolishing ICE, and a larger percent of even Republicans support abolishing ICE than support their state seceding.
I would be concerned about language collapse (i.e. models incrementally forget vocabulary + fail to adapt to new terms leading to language becoming incrementally worse) before I would worry about knowledge collapse
Why so?
The exact same mechanism is on display here. Ask an LLM for information, and it’s more likely to condense an answer, not display additional relevant information, and slowly but surely produce less and less outputs including that given information.
Sources then begin to be generated by the AI model that adds less and less of that information over time, LLMs cite those new sources that don’t include that information, etc, etc, and now that information is just not present in a majority of sources, and is never stated in any LLM responses.
If anything, this is more likely than models forgetting certain vocabulary, because while the underlying tokens for a lot of that vocabulary still exist in the model, the subsequent combinations for a given piece of information are substantially less likely, and the models’ finite size can only store a subset of that actual information in statistical averages. (i.e. you can store the alphabet and a dictionary of every word in the English language, and many simple phrases, in a tiny fraction of what the sum of Wikipedia is, and Wikipedia itself will contain a subset of all information on the internet, and so on, but you can still theoretically write any English content you’ll find on Wikipedia or the internet using that alphabet and dictionary)
What’s wrong with wanting a UI you’re used to?
Everyone wants other people to switch to Linux until they do literally anything a purist wouldn’t do with their own personal setup 😅
Feels to me like this is AI assisted but not entirely AI generated. Lyrics’ timing is a bit off and the sounds of the instruments blend together in a sort of odd way, but it doesn’t feel like what you typically see from something pumped straight out of an AI model in its entirety.
I hope I’m wrong, since it is genuinely a fun animated video and is the general sort of style of music I like, but I don’t want to support someone using generative AI to displace people who put actual effort into making their music.
hmmmmmmm good point, I didn’t consider that!
According to the Ars review, the 1.5 hour battery life is when running games on the Steam frame itself
I was going off the LTT number which put it at 1:36 when streaming Half Life Alyx from a desktop PC, running at 144Hz. Ars’ number is when running on Performance mode with “most VR titles”, so I don’t know how comparable that is.
The Verge says they never got above 2 hours even when using battery-saving mode or streaming-only, and demanding games got under 1 hour.
As for charging time, LTT claims it’s 3 hours to 100%, and 2.4 to 95%, and doesn’t seem to state there’s much of a speed increase below that point, and as far as I’m aware you usually only see a major difference in charging speed for the last ~10%, though previously The Verge did also state a power bank could keep them going up to 2.5 hours.
So with all that said, if it takes around 1-2 hours for it to die after starting from full, and it takes a minimum of 2.4 hours just to get it almost full… that means it’ll still run out of battery eventually, even if plugged in.
I would get it if the battery life didn’t suck.
~1.5 hours when streaming from PC at 144hz, and a full charge time of around 3 hours, meaning you probably can’t even get unlimited playtime if it’s plugged in the entire time and solely streaming from a PC instead of computing the game itself.
You could make a super long argument against this but I think there’s a few simple points (that you can use any number of, you don’t really need all of these at once for most people) that usually get it across to people, at least from my experience.
There’s the moral/emotional argument:
“You do have something to hide. Wanna unlock your phone and let me go through all your messages/photos/emails, leave the bathroom door open all the time, and never close your blinds? Even if you aren’t doing something illegal AND have no problem with me seeing all your conversations and data, privacy is still a comfort for many people”
…and there’s the monetary arguments:
“If a company is collecting that data, it’s because they make money off it. It’s a multi-billion dollar industry, and it’s the only reason Google, Facebook, etc can physically exist. If they know more about you, they can manipulate you into spending money with advertisers easier, allow political campaigns to manipulate your opinion more effectively, etc”
“You might not have a problem with how your data is used now, but if the law changes, or a corporation decides to do something different, suddenly data about your health and finances that was just for ads might then become a way to increase your health insurance pricing to the max you can afford”
all android devices have been using file based disk encryption since several Android versions now.
All Android devices are supposed to support it, but not all do. (or at least, not all do effectively without compromising the cryptographic root of trust by not implementing proper hardware security chips)
I’ll grant it to you on the scopes, PIN changes, etc, but realistically I just don’t think anyone can justify GrapheneOS being something that should be supported on Fairphone given how absolutely desolate the phone looks with regard to any attempt at all to hardware security.
It really depends on what security level you want out of a phone
It does, but that’s exactly my point. GrapheneOS will provide you essentially no more security than any other alternative Android operating system, should it have to operate on a Fairphone with all those features not supported by a Fairphone stripped away.
Unless Fairphone adds more hardware security features that are standard on most other phones, and highly supported on Pixels, installing a heavily crippled GrapheneOS on a Fairphone would get you essentially none of the benefits of GrapheneOS in the first place.
Entirely lacking disk encryption for typical users due to not having a secure element is a pretty major flaw.
It’s also missing hardware accelerated virtualization which is necessary for much of GrapheneOS’s sandboxing, has weak security for other keys in the OS keystore, is missing hardware memory tagging which makes it much easier for apps to use overflow attacks, doesn’t have proper verified boot support once a custom alternative OS is flashed, and leaves exposed debugging APIs even when the phone is locked.
This breaks:
At that point, GrapheneOS can’t physically provide you essentially any security anymore.
It wasn’t just the update cycle either, it’s that they don’t have the physical hardware chips to support Graphene’s minimum requirements for security, which would severely weaken any benefits you actually get from GrapheneOS.
If his life was on the line, you’d see him change his tune real quick, but it’s not, so he’ll sacrifice 114,000 people for the sake of his donors’ stock portfolios. Fuck you, Jeffries.
Some patterns can. This one won’t.
Adversarial patterns/noise can confuse cameras, but that’s usually done not by tricking it into thinking, for example, that this one van is actually a hundred mini vans crammed into the same space, but by tricking it into thinking there’s not a car there because the pattern just confuses it and it recognizes it as any random sequence of random objects and things simultaneously.
Just slapping a bunch of car photos won’t make it think it’s a car, because the little photos are tiny, don’t move like a car, are still visually distinct from the background, and are on a much larger car-shaped object. If your car has patterns that makes it look like the general concept of an asphalt road, road signs, lamp posts, etc, then it might be enough to confuse the camera into thinking the odd blob shapes are something else, because cars on the road are also always passing on top, in front of, and by asphalt, road signs, lamp posts, etc.
The cameras don’t have depth perception, so if your car looks close enough to the road and objects around it, it’ll blend right in, to the camera.
Especially given it has a similar effect to how spam emails are often deliberately bad so they just don’t waste their time with people that waste some of their time before wising up. If you only get the most easily duped people in the first place, that’s a lot less time wasted.
With LLMs, you’re explicitly targeting people that are less likely to strongly ideologically object to things (like LLMs, or genocide funding) on moral grounds, you’re getting the people that are willing to just get a quick answer without having to look into it deeply, and you’re getting the people who’s sole goal it is to flood the web with any SEO-optimized slop they can with the least effort possible.
LLMs self select for people not willing to put in cognitive effort, that are easily influenced and less careful about fact-checking things.
This will not work. AI-enabled surveillance cameras are more than capable of determining that it’s a wrap on a car, rather than multiple cars all somehow moving in the exact same direction in the exact same area while all facing in incorrect directions relative to the camera.
If anything, it’s just another data point, because Flock cameras also catalog details about your vehicle like stickers, color, wraps, graffiti, dents, etc.
They used an AI model to repeatedly generate guesses of the code until it matched the compiled bytecode, then AI-generated new code based on the decompiled source to create a technically unique codebase that can do most of the same functions and looks extremely close to the original.
Has essentially every feature, but also bugs out a lot or has features that technically work, but not in the same way as Photoshop (e.g. magic wand selection tool might bug out and select stuff on more than one layer, and might be less accurate and selecting fine edges)