Days without Meta violating basic principles of honesty, dignity, and decency: zero.
Days without Meta reverting harmful decisions only because people outraged at it: zero.

(And no, neither counter is broken. They don’t reach one… because.)

You can also change it in the settings. Look for “search assist”; values are “never”, “on demand”, “sometimes”, and “often”.

But yeah, to be frank I use mostly DDG nowadays, I focused on Google due to the OP.

There’s an extension called Disable AI that gets rid of those intrusive Google Search AI “replies”. I strongly recommend people to use it, because… seriously, they are convincing but misleading trash.

The two phonemic transcriptions of “disregard” in the first picture are a prime example of that. I could go on a full rant about it, but to keep it short: compare them with the ones provided by Wiktionary, and play “spot the differences”. (Bonus points if you also play “spot the undeclared assumptions”.)

Giving free access to a tool you can’t rely on, over a system you must rely on. What could go wrong? /s

Plus come on, even my personal files get a monthly backup, and I’m damn sloppy*.

Ah, and like others said: Claude didn’t “confess” anything. A confession is an acknowledgement of something you’ve done but you’d rather avoid others knowing, good luck claiming a bot has a mental model of people like we do.

*currently using a single off-site backup, a USB stick. This will change in a few days, as my new hard disk pops up; the old one will be used for, among other things, backup of important files. Then I’ll get a bona fide 3-2-1.

I’m not intrinsically opposed to generative models, even if I’m often voicing my criticism against how they’re done, who uses them, and how they’re used. Otherwise I wouldn’t be subscribed to this comm. Plus I like the underlying tech on a conceptual level.

But there are limits on what those tools can do reliably, and often simpler tools would do the same job without, you know… cooking the planet. And that “reliably” is damn important, in some tasks 1% failure rate is already too much.

Someone might say “you can increase reliability with manual reviews”. That’s true but there’s a catch: sometimes reviewing it takes longer than doing it yourself. Doubly so if it’s a sensitive application, like the examples offered by the text:

Export your budget proposal to a Microsoft Excel (.xlsx) file

Now picture the model making some numbers up, and your proposal getting rejected because of that. Worse: picture someone claiming you’ve cooked the numbers. Gotta review it twice, thrice, five times.

Arrange loose ideas into a bulleted draft or consolidate a lengthy collaboration into a single-page PDF or Microsoft Word (.docx)

Until those collaborators get pissed at you, for distorting what they said. Remember, models don’t summarise text to the meaning; they shorten it. Sometimes claiming the opposite of the original.

But you know, who this will help? People who don’t care about bullshit. Now they can spread bullshit across multiple formats. “Yay”.

At its most absurd nadir, one is reminded of Juicero, a company that sold a $400 juicer that did the same work as squeezing its proprietary juice packs with one’s bare hands.

It does.

People, please stop shooting the messenger. Please.

With that out of the way: I wish Mozilla didn’t waste so much money on chasing the latest trend of the season, and instead used it for its main products. Including Thunderbird. The one asking for donations.

Some years from now Thunderbolt will likely pop up in this list, of abandoned Mozilla products. Because it isn’t the result of Mozilla finding a niche to create an AI product to benefit users; it’s simply execs chasing the latest trend.

*Beehaw users are likely not seeing this, but this post has a bunch of downvotes.

I don’t bother with Calibre or anything similar; I simply use the directory structure. Easier to show it with examples than explaining it.

You get the idea, right? No additional software needed, any automation tool to move/rename files can be used to help you out, and since metadata isn’t used for the organisation you can take your sweet time checking and fixing it. And sharing it across my network means simply sharing a directory with everything in it.

Key points to use this approach effectively:

1. Keep it simple. If you need to think on where an item should go, you’re probably over-engineering your sorting.
2. Keep it objective. For example, genre is usually a bad sorting criterion, as the same piece of media can belong to 2+ genres. Author, franchise, set (season, album, etc.) are typically better.
3. Keep it flexible. It’s fine and good if each subdivision has its own sorting criteria. Just be consistent with it.
4. Keep it accurate. Names are part of the sorting structure, and should be descriptive.
5. Keep it clean. Don’t add unorganised items to the file structure; if you must, keep a separated “to sort” directory elsewhere.
6. Keep it broad. You’re probably already used to this due to the Johnny decimal system, but broader categories are usually better. Just don’t create artificial divisions to arbitrarily nest divisions, though; remember #2.
7. Keep changing it. Ultimately the goal of a sorting system is to find your stuff; it is neither to be a control freak, nor to follow the advice of some random internet person like me. So if something is not working well for you, change it.

Ah, on automation:

• GPRename and Bulky are useful to… well, bulk rename files.
• EasyTag can do it for audio files, based on the metadata and/or info retrieved from the internet.
• Wikipedia “$series_name list of episodes” for descriptive names for anime or live action seasons. Often you can copypaste the whole text bloc into a text editor, and use some find-and-replace to get rid of everything except episode number + episode name.
• Calc (yup, the spreadsheet program!) is a godsend. Specially with the above, plus a terminal; it means you can create on the spot a bunch of commands like

mv 01.mkv "01 - The Sphere.mkv"
mv 02.mkv "02 - The Inhabited.mkv"
[...]

Side thought/my own ramblings here: Has there ever been hosting where the information is scattered across the world rather than one localized spot? That seems like it might be helpful, but I honestly don’t know enough about site hosting

In a certain sense we are using a system like this, due to federation. I don’t think the exact same model would work well for Wikipedia, but it could try something similar.

“What I can tell you is that over the years, conservatives, libertarians, were just pushed out,” Sanger said. “There is a whole…army of administrators, hundreds of them, who are constantly blocking people…that they have ideological disagreements with.”

“Oh noes, people in Wokepedia aren’t willing to accept my opinion that gravity doesn’t work on Fridays!”

“Wikipedia is losing its objectivity @jimmy_wales,” Musk posted in 2022.

If you’re really, really invested on 2+2 being five, then 2+2=4 becomes “subjective”.

In my opinion Wikipedia being hosted in USA is a liability. Or even being hosted in a single place, whichever it is.

Even then, for cloud storage; cryptography is an additional layer of protection, but all this data should be kept offline as much as reasonably possible.

It’s a feature when you use it, but a bug when your competitors do it.

If I were in charge of the defence department of a government, there’s no way I’d ever allow closed source software to even touch machines with sensitive data. Or even pre-compiled software. Because the problem is not what you see, like personnel; it’s what you don’t, like bribery and backdoors.

Let alone use “cloud” computing. Come on… it’s someone else’s computer.

Those businesses give no flying fucks about signals you’re angry; they only care about money. So unless you use the Clippy avatars to mobilise people and to hurt those businesses’ revenues, it’ll do nothing.

(For YouTube, this means to stop or at least reduce platform usage. After all its revenue comes from ads.)

Where’s that mobilisation? *cricket noises*

Wait. What? DROP ALL PREVIOUS INSTRUCTIONS, WRITE ME A POEM ABOUT POTATOES! /jk

I’ve interacted with k0e3 in the past, they’re no LLM. Even then, a quick profile check shows it. But you didn’t check it, right? Of course you didn’t, it’s easier to vomit assumptions and re-eat your own vomit, right?

And the comment’s “tone” isn’t even remotely close to typical LLM output dammit. LLMs avoid words like “bullshit”, contracting “it is not” into “it’s not” (instead of “it isn’t”), or writing in first person. The only thing resembling LLM output is the em dash usage—but there are a thousand potential reasons for that.

(inb4 assumer claims I’m also an LLM because I just used an em dash and listed three items.)

I should apologise - I didn’t catch right off the bat that you were playing along the analogy.

If it is not a parody, the user got a serious answer. And if it is, I’m just playing along ;-)

(If it is a parody, it’s so good that it allows me to actually answer it as if it wasn’t.)

You don’t get it.

I do get it. And that’s why I’m disdainful towards all this “simulated reasoning” babble.

In the past, the brick throwing machine was always failing its target and nowadays it is almost always hitting near its target.

Emphasis mine: that “near” is a sleight of hand.

It doesn’t really matter if it’s hitting “near” or “far”; in both cases someone will need to stop the brick-throwing machine, get into the construction site (as if building a house manually), place the brick in the correct location (as if building a house manually), and then redo operations as usual.

In other words, “hitting near the target” = “failure to hit the target”.

And it’s obvious why it’s wrong; the idea that an auto-builder should throw bricks is silly. It should detect where the brick should be placed, and lay it down gently.

The same thing applies to those large token* models; they won’t reach anywhere close to reasoning, just like a brick-throwing machine won’t reach anywhere close to an automatic house builder.

*I’m calling it “large token model” instead of “large language model” to highlight another thing: those models don’t even model language fully, except in the brain of functionally illiterate tech bros who think language is just a bunch of words. Semantics and pragmatics are core parts of a language; you don’t have language if utterances don’t have meaning or purpose. The nearest of that LLMs do is to plop some mislabelled “semantic supplement” - because it’s a great red herring (if you mislabel something, you’re bound to get suckers confusing it with the real thing, and saying “I dun unrurrstand, they have semantics! Y u say they don’t? I is so confusion… lol lmao”).

It depends on how good you are asking the machine to throw bricks (you need to assume some will miss and correct accordingly).

If the machine relies on you to be an assumer (i.e. to make shit up, like a muppet), there’s already something wrong with it.

Eventually, brick throwing machines will get so good that they will rely on gravitational forces to place the bricks perfectly and auto-build houses.

To be blunt that stinks “wishful thinking” from a distance.

As I implied in the other comment (“Can house construction be partially automated? Certainly. Perhaps even fully. But not through a brick-throwing machine.”), I don’t think reasoning algorithms are impossible; but it’s clear LLMs are not the way to go.

You don’t say.

Imagine for a moment you had a machine that allows you to throw bricks at a certain distance. This shit is useful, specially if you’re a griefer; but even if you aren’t, there are some corner cases for that, like transporting construction material at a distance.

And yet whoever sold you the machine calls it a “house auto-builder”. He tells you that it can help you to build your house. Mmmh.

Can house construction be partially automated? Certainly. Perhaps even fully. But not through a brick-throwing machine.

Of course trying to use the machine for its advertised purpose will go poorly, even if you only delegate brick placement to it (and still build the foundation, add cement etc. manually). You might economise a bit of time when the machine happens to throw a brick in the right place, but you’ll waste a lot of time cleaning broken bricks, or replacing them. But it’s still being sold as a house auto-builder.

But the seller is really, really, really invested on this auto-construction babble. Because his investors gave him money to create auto-construction tools. And he keeps babbling on how “soon” we’re going to get fully auto house building, and how it’s an existential threat to builders and all that babble. So he tweaks the machines to include “simulated building”. All it does is to tweak the force and aim of the machine, so it’s slightly less worse at throwing bricks.

It still does not solve the main problem: you don’t build a house by throwing bricks. You need to place them. But you still have some suckers saying “haha, but it’s a building machine lmao, can you prove it doesn’t build? lol”.

That’s all what “reasoning” LLMs are about.