Likely contentious but my experience has been “newb” has a slight vocal raising to indicate light-heartedness, ie:

Noob: no͞ob Newb: nyo͞ob

Removed by mod

Do you want to share those “eyebrow raising” numbers?

Best summary I can find stating the elections were “rigged” is the report from the Carter center which uses almost entirely qualitative data or hearsay arguments to support the claim and conveniently forgets to mention any of the surrounding context around US interventionism.

In contrast the argument for fair and open elections is well summarized in the report from the NLG delegation’s report which does a good job of providing quantitative data as well as useful context to support the conclusion it was fair.

Can you provide those quantitave arguments from these “third party left-wing governments”? Because I am having a hard time finding any of them…

“Why don’t you want to compromise with the leopards? They don’t want to kill you, just let them lick your nose a bit. That would be cute, right!?”

Except that’s not even how most bus systems work because most of them are majority funded by taxes with fares originally meant to serve as a stopgap but then slowly converted into a profit engine (usually after privitization). Fares are a way to gatekeep a service which your taxes already pay for, which I would argue, is by itself a form of theft.

As an example check out the latest MTA report only 26% of funding comes from fares, and that ones a bit in the higher end from what I’ve seen (NYC public transit, picked as the example a it’s recently been in the news for issues with fare evasion)

All that aside, it’s also worth noting that fare increases are extremely unpopular and it’s not that easy to increase them without potential serious backlash (ie the mass protests in Chile a few years back that were in part set off by the fare hikes.)

From an article about a recent lawsuit

The App Store appeared to harvest information about every single thing you did in real time, including what you tapped on, which apps you search for, what ads you saw, and how long you looked at a given app and how you found it. The app sent details about you and your device as well, including ID numbers, what kind of phone you’re using, your screen resolution, your keyboard languages, how you’re connected to the internet—notably, the kind of information commonly used for device fingerprinting.

Notably, knowing keyboard language and monitoring tap locations allows for reconstruction of text the user types (as detailed in this article

I do think you are correct that Apple probably isn’t actively keylogging every iOS device (just because there’s easier ways with less legal concerns that ultimately get the same outcomes), but it’s not like there’s “no evidence”.

Exactly, hence the root of the problem the original meme is getting at…

For healthy working relationships and solid infrastructure you under-promise and over-deliver.

For maximal profit and sustainable business models you over-promise and under-deliver.

If you build a base on/near a bunch of ore nodes and dedicate it entirely to mining your pals will mine it for you and it respawns daily (passive ore generation ftw!!!)

Another factor was the PPP and other “totally not bailouts” that were part of the COVID relief spending.

Of the roughly $800 billion dollars from PPP which was provided as uncollateralized, low-interest loans 66-77% went directly to companies and ~92% of those loans were completely forgiven.. In other words an ~5-600M bailout predicated on keeping positions open long enough to maintain plausible deniability that is what the goal was.

“All models are wrong, some are useful.”

It’s not, the underlying data is still just as biased. Taking a bunch of white people and saying they are “ethnically ambiguous” is just statistical blackface.

Advertising is just propaganda where the politick is centered around consumerism.

However, even if you consider that “not a real politic” this article skips past the consumerism and straight into police state normalization.

There’s a specific model for stable diffusion called riffusion that does an okay job. If you want to play with it I recommend downloading the automatic 1111 client and installing it from the “plugins” tab.

Yep! It’s known as “The Gell-Mann Amnesia Effect”.

The academic name for the field is quite literally “machine learning”.

You are incorrect that these systems are unable to create/be creative, you are correct that creativity != consciousness (which is an extremely poorly defined concept to begin with …) and you are partially correct about how the underlying statistical models work. What you’re missing is that by defining a probabilistic model to objects you can “think”/“be creative” because these models dont need to see a “blue hexagonal strawberry” in order to think about what that may mean and imagine what it looks like.

I would recommend this paper for further reading into the topic and would like to point out you are again correct that existing AI systems are far from human levels on the proposed challenges, but inarguably able to “think”, “learn” and “creatively” solve those proposed problems.

The person you’re responding to isn’t trying to pick a fight they’re trying to help show you that you have bought whole cloth into a logical fallacy and are being extremely defensive about it to your own detriment.

That’s nothing to be embarrassed about, the “LLMs can’t be creative because nothing is original, so everything is a derivative work” is a dedicated propaganda effort to further expand copyright and capital consolidation.

It doesn’t aim to destroy extensions but point #1 within the problem statement:

Users like visiting websites that are expensive to create and maintain, but they often want or need to do it without paying directly. These websites fund themselves with ads, but the advertisers can only afford to pay for humans to see the ads, rather than robots. This creates a need for human users to prove to websites that they’re human, sometimes through tasks like challenges or logins.

I partially agree with you, but I think you’re missing the end goal of Facebook et al.

As HughJanus pointed out it’s not really any different than a person reading a book and by that reasoning using copyrighted material to train models like these falls well within the existing framework of “fair use”.

However, that depends entirely on “the purpose and character of the use, including whether such use is of a commercial nature or is for nonprofit educational purposes.” I agree completely with you that OpenAI’s products/business (the most blatant violator) does easily violate “fair use” due to that clause. However they’re doing it, at least partially, to “force the issue” on the open question of “how much can public information be privatized?” with the goal of further privatizing and increasing commercial applications of raw data.

As you pointed out LLMs can only create facsimiles and not the original work, and by that logic they can’t exactly replicate the inputs either.

No I don’t think artists can claim that they own any and all “cheap facsimiles” of their works, but by that same reasoning none of these models produced should be allowed to be the enforceable property of any individual/company either.

For further reading check out:

• Kelly v. Arriba Soft Corporation on why “thumbnails” (and by extension LLMs, “eigen-images”, etc.) are inherently transformatve and constitute fair use.
• Bridgeport Music, Inc. v. Dimension Films for the negative impacts that ruling has had and how it still doesn’t protect the artists from their stuff being used for training and LLM.
• “Variational auto-encoders” for understanding on how the latest LLMs actually do achieve a significant amount of “originality” and I would argue are able to be minimally creative.

“embrace, extend, and exterminate”