GamingChairModel

joined 3 years ago
[–] GamingChairModel@lemmy.world 13 points 1 day ago (2 children)

There just wasn't really user-submitted content back then. If you wanted to post something on the internet, you had to create a website.

There were tools that made a website a bit easier to create (most notably Geocities), but it was still a fairly technical task to simply get text that you typed show up on a website accessible to all.

Simply being able to reply to someone else? That wasn't really on the web, although by 2001 there were a few attempts to bring that kind of forum functionality to the broader web on actual http/www webpages (when it was previously on Usenet and BBSes and mailing lists and the technologies known as the internet before and separate from the world wide web). vBulletin was the popular one, and I think phpBB was fairly popular, too, but those projects started in 2000 and weren't that popular in the first years. Web hosts actually offering a full blown LAMP stack (Linux, Apache, MySQL, PHP) for hosting, and the technical skills to administer that kind of service, even on free software, was a pretty big hurdle to adoption before 2003 or so.

In 2001, almost all of the web was static content, with no method of interacting with the content other than simply viewing it. You'd click on links to retrieve another piece of content. By 2005 the web 2.0 revolution was underway, and websites had become interactive, with dynamic content drawing from relational databases under the hood. But in 2001? No, the web was pretty static.

Your description of the rise of the social algorithms is part of the story since 2010, but even that leaves out the period of time in between.

[–] GamingChairModel@lemmy.world 3 points 3 days ago (1 children)

HTML / JS is still a buggy pile of slop.

In what world is JavaScript considered buggier than Flash, either in the actual content in the wild or the client-side software rendering/running that content? It wasn't true when Flash died and certainly isn't true today.

Flash was a security nightmare, with all sorts of kludges patched on to try to deal with fundamental flaws in how it handled privileges. If you want to go back to the days where zero click exploits can take over your machine just from a browser visiting the wrong URL, leave the rest of us out of that vision.

The current web experience is complete garbage in comparison.

Mm, and what makes you think that handing Adobe the keys to control everyone's web experience would make it better?

Apple's Safari supports still images in JXL.

Perhaps more notably, Apple's iPhone ProRaw supports JXL encoding for its raw sensor data. They're laying the groundwork for JXL to be a supported format from the point of capture at the camera, through all the processing to make an image for web publishing or whatever.

[–] GamingChairModel@lemmy.world 15 points 4 days ago

The killer feature is that JXL is better in that it can losslessly encode JPEG further, and the overwhelming majority of the legacy image files that people have are JPEG. That alone should justify its support, because there are a lot of files out in the world where the highest quality, closest to "original" quality file is stored in JPEG format. A format that allows for the further compression with zero loss of quality from those originals is really important.

And the other thing this article (and a lot of the discussion around JXL) chooses not to cover is how JXL is a good format outside of just web images. It's not just looking to replace JPG/PNG/webp. It's also looking to replace raw photography formats like DNG, TIFF, and other formats that are used for full workflows from image capture from the imaging sensor itself, from cameras to scanners to medical imaging.

If JXL succeeds at becoming the dominant raw capture format, the entire workflow of processing those raw images into exported web-friendly images will favor JXL for photography.

[–] GamingChairModel@lemmy.world 12 points 4 days ago (1 children)

No, you've got it all wrong. Flash was buggy and insecure proprietary software written for proprietary OSes. I'm glad it died, after several years of trying to fight its normalization on the web, where you'd need to install shitty plugins like gnash on Linux to try to see the same web that people were seeing on Mac or Windows.

The web should always be built on open standards, and Flash was the biggest barrier to that ideal at the time that iPhones came out. Flash deserved to die, and I celebrated when it did.

Microverse battery

In the late 2000's and early 2010's, the base MacBook used to be the base model laptop: the cheapest option, nothing special in terms of performance or quality. Then, if you wanted a more premium option, there was the MacBook Air for thinness or the MacBook Pro for the highest performance features and hardware.

But the thinness of all laptops started to encroach on what made the Air special, and the general march towards cheaper electronics made it so that the base level MacBook didn't make a ton of market sense when the MacBook Air was $999, and the MacBook Pro's special hardware differentiation started to trickle down to the cheaper models, too (high DPI "retina" displays, aluminum unibody construction, huge multi-touch haptic trackpads). So there wasn't a place for a base MacBook anymore. The Neo came in and took that old space once Apple developed a willingness to sell a laptop for less than $999.

I'm just not seeing what market segment a base MacBook is intended for, at this point.

[–] GamingChairModel@lemmy.world 5 points 1 week ago (1 children)

Hmm I don't think you would be a good choice to be appointed as the champion standing up for human emotion.

[–] GamingChairModel@lemmy.world 8 points 1 week ago (1 children)

Steps that either would not work between architectures or that Rosetta would handle (thereby answering your own question)

What? They would compile the code that they control for the M-series architectures. The target architecture is M-series ARM chips running on MacOS.

Rosetta is for translating x86 to ARM. Which wouldn't be necessary because there are no x86 binaries involved at all.

[–] GamingChairModel@lemmy.world 11 points 1 week ago (6 children)

I don't understand why Rosetta has to be involved in any way at all.

Apple provides APIs for programming low level GPU instructions, including AI workloads, on their chips, using the Metal API. Anyone interested in using Apple hardware to its full potential can just write Mac-native software, same as any other MacOS native software directly compiled as binaries to run on Mac M series chips. No Rosetta required for translating x86 instructions to ARM, when the whole thing compiles for Apple's native instructions in the first place.

 

In recent years, I've seen people use projectors at night to protest policies: projecting slogans, images, etc., using a normal projector against the wall of the target of a protest (embassies, government buildings, prisons/detainment facilities, corporate headquarters, etc.).

Here's an example, but I've seen lots of other examples. And even outside of protest, people have been doing ridiculous things with 3D projection, like this guy animating a hotel cuck chair (SFW).

This got me to thinking: if the image recognition of Flock and similar cameras is just an AI image recognition function (using ImageNet or something like that) being run on captured video, what's stopping people from projecting false data onto streets and sidewalks in a way that tricks the Flock camera into recording false people/vehicles in places where there was no person/vehicle? Including fake license plates, etc.?

Seems like an attack vector for some kind of denial of service attack, like putting fake faces and license plates all over.

Is there anyone doing this? Would it be possible, at least at night, for certain camera locations and angles?

[–] GamingChairModel@lemmy.world 11 points 1 week ago

In 2011, Motorola split into two companies, each with rights to the Motorola name and logo.

Motorola Mobility took the business lines related to cell phones. It got bought by Google, and then Lenovo.

Motorola Solutions took the business lines related to everything else, including (and especially) radios for law enforcement, fire departments, militaries, and surveillance video tech.

[–] GamingChairModel@lemmy.world 1 points 1 week ago (3 children)

Yup. My main living data is on a NAS, my on-site backup is an external USB enclosure with a SATA hard drive hooked up to a Mac Mini, all so that I can leverage a Backblaze account to back up the external hard drive with unlimited data.

 

(Note: McSweeney's is a satirical publication)

 

I've read some of Ed Zitron's long posts on why the AI industry is a bubble that will never be profitable (and will bring down a lot of companies and investors), and one of the recurring themes is that the AI companies are trying to capture growing market share in an industry where their marginal profits are still negative, and that any increase in revenue necessarily increases their costs of providing their services.

But some of the comments in various HackerNews threads are dismissive, saying that each new generation of models makes the cost of inference lower, so that with sufficient customer volume, the companies running the models can make enough profit on inference to make up for the staggering up-front capital expenditures it took to build out the data centers, train their models, etc.

It's all pretty confusing to me. So for those of you who are familiar with the industry, I have several questions:

  1. Is the cost of running any given pretrained model going down, for specific models? Are there hardware and software improvements that make it cheaper to run those models, despite the model itself not changing?
  2. Is the cost of performing a particular task at a particular quality level going down, through releases of newer models of similar performance (i.e., a smaller model of the current generation performing similarly to a bigger model of the previous generation, such that the cost is now cheaper)?
  3. Is the cost of running the largest flagship frontier models going down for any given task? Or does running the cutting edge show-off tasks keep increasing in cost, but where the companies argue that the improvement in performance is worth the cost increase?

I suspect that the reason why the discussion around this is so muddled online is because the answers are different depending on which of the 3 questions is meant by "is running an AI model getting cheaper over time?" And the data isn't easy to synthesize because each model has different token prices and different number of tokens per query.

But I wanted to hear from people who are knowledgeable about these topics.

 

Curious what everyone else is doing with all the files that are generated by photography as a hobby/interest/profession. What's your working setup, how do you share with others, and how are you backing things up?

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