Works for me!

You want me to explain the bloom filter? So that you can say “see, I told you it makes sense to use as a memory efficient guaranteed no false negative checks on if a user has seen a video before. Dumbass”.

Then I’d reply something like “yeah, I, know… The point isn’t whether or not bloom filters can make sense here… What’s being discussed is whether or not this was generated by a human or LLM… That, even if someone was making a diagram, of a system, where bloom filters was used, for the case of checking if you’ve already seen a video… It would still be weird to present it in the way it is presented in the diagram, for a human, but not so weird for an LLM, if you consider how LLMs work by associated concepts, where a ‘creator filter’ and ‘bloom filter’ are linguistically more connected, and explains why they are used similarly in the diagram, even though the latter is hardly considered a filter by anyone who has used one, not to mention that the actual ‘filter’ here would be the concept of ‘not/seen before’… and again, who’d want to give a shit about which data structure is used to most space-efficiently perform that evaluation… for fucks sake”

Then, you’ll be all non sequitur and accuse me of some ad hominem like “you use big words on purpose to seem smart, but you are dumb”.

Nah. You mistook my “these are the parts that really don’t make sense for a human to make”, with “i don’t understand the subject, or what this complex concept can mean”.

If you don’t see the difference, you’re just going in a loop of trying to argue the wrong point. I was hoping to save you the trouble of “you don’t get it” line, by saying “trust me, I do get it, I’m a god damn expert”.

I’m happy to indulge in explaining things to people who want to learn something. I happily fuck with people who seem disingenuous to that goal. If I was wrong and you genuinely meant to ask “why doesnt this make sense”, then I’m sorry. I misread your intentions, and I’ll keep it in mind.

Wouldn’t want to be accused of using big words, now, would I?

Happy to hear. Cheers

You still think that’s a relevant point? Did I also not point out to what extent it does make sense in that context, but still why it is weird, and why an LLM might do that weird thing, but a human wouldn’t?

Maybe start at the beginning, and read again what I wrote. This time, do it with an assumption that I know what I’m talking about? Also, since you’re already learning stuff. Read about how LLMs and transformers work. Maybe that might help. I don’t know. Either way, fine by me. Fingers crossed you figure it out.

Let me ask you this tho. When you say “do in fact make sense”. Are you basing it that in the context of what you think this diagram is saying? Or do you mean “do in fact make sense” in the context of knowing how such an algorithm would be constructed?

You still keep missing my points. And they aren’t difficult points either. The fancy jargon words were a basic ass description of what a bloom filter does. So you’re kinda making my argument, which is funny for reasons I’m sure won’t be appreciated.

I’m also not tangentially an expert, for fucks sake. I’m the kind who’s day job is to design simpler things than what this diagram is trying to “explain”, and telling you, that it comes across as if made by with a toddler’s understanding. I also didn’t say this was 100% guaranteed to be LLM, I said it smelled like it. I have suggested other possible explanations: stupidity, incompetence, and even a mental stroke.

Your take on being tangentially an expert might be a woosh moment

I’m also out of shits to give at this point. Literally.

I think you might have missed my point. I wasn’t listing stuff I had trouble understanding. I was listing stuff that didn’t make much sense. The distinction is relevant. The end result, even if you manage to find some excuse that extends the already generous benefit of doubt, it still doesn’t result in anything useful or informative.

I’m also not using fancy words (or…?). The only fancy thing that stands out is the the “Bloom filter”, which isn’t a fancy word. It’s just a thing, in particular a data structure. I referenced it because its an indication of an LLM, in behaving like the stochastic parrot that it is. LLMs don’t know anything, and no transformer based approach will ever know anything. The “filter” part of “bloom filter” will have associations to other “filters”, even tho it actually isn’t a “filter” in any normal use of that word. That’s why you see “creator filter” in the same context as “bloom filter”, even though “bloom filter” is something no human expert would put there.

The most amusing and annoying thing about AI slop, is that it’s loved by people who don’t understand the subject. They confuse an observation of slop (by people who… know the subject), with “ah, you just don’t get it”, by people who don’t.

I design and implement systems and “algorithms” like this, as part of my job. Communicating them efficiently is also part of that job. If anyone came to me with this diagram, pre 2022, I’d be genuinely concerned if they were OK, or had some kind of stroke. After 2022, my LLM-slop radar is pretty spot on.

But hey, you do you. I needed to take a shit earlier and made the mistake of answering. Now I’m being an idiot who should know better. Look up Brandolini’s law, if you need an explanation for what I mean.

I’m not too happy to spend time pointing out flaws in AI slop. That kind of bullshit asymmetry feels a bit too much like work. But, since you’re polite about it, and seem to ask in good faith…

First of all this is presented as a technical infographic on an “algorithm” for how a recommendation engine will work. As someone whose job it is to design similar things, it explains pretty much nothing of substance. It does, however, include many concepts that would be part of something like this, with fuzzy boxes and arrow that make very little sense. With some minor trivial parts you can assume from the problem description itself. It’s all just weird and confusing. And, “confusing” not in the “skill issue” sense.

So let’s see what this suggested algorithm is.

1. It starts out with “user requests the feed”, and depending on whether or not you have “preference” data (prior interests or choices, etc), you give either a selection based on something generic, or something that you can base recommendations on. Well… sure. So far, silly, and trivial.

2. “Scoring and ranking engine”. And below this, a pie diagram with four categories. Why are there lines between only the two top categories, and the engine box? Seems weird, but, OK. I suppose all four are equally connected, which would be clearer without the lines. Also, what are the ratios here? Weights for importance, of some sort? “Time-Decayed”? I hope that’s not the term that stuck for measuring retention/attention time.

3. On the three horizontal “Source Streams” arrows coming in from the left, its all just weird. The source streams are going to be… generated content, no? But let’s give it the befit of the doubt and assume it’s suggesting that, given generated content, some of it might can be considered relevant for “personal preference” and has a “filter: hidden creators”, but, none of that makes any sense. The scoring and ranking engine is already suggested to do this part… The next one is “Popular (high scores) filter: bloom filter (already seen)”. Which mixes concepts. A bloom filter is the perfect thing to confuse an LLM, because it has nothing to do with filters in the exact same context “filters” was used for the above source stream. Something intelligent wouldn’t make this mistake. But, it does statistically parrot it’s way to suggest that a bloom filter might have something to do with a cost effective predicate function that could make sense for a “has seen before”. However, why is this here?

I’ll just leave it at that. This infographic would make a lot of sense if it was created by some high schoolers who were tasked to do something like this. Came up with some relevant sounding concepts. Didn’t fully understand any of them. Which is also exactly the kind of stuff LLMs do

I don’t think loops hired a bunch of kids, so LLM it is.

And the like “Our new For You algorithm is pretty complex, so we created this infographic to make it easier to understand!”, doesn’t help the case against LLM either. There a many complex parts of a recommendation engine, but none of the things in this infographic explain or illuminate those complex parts…

But, I might be wrong, and this is their earnest attempt at explaining how their algorithm works. In which case, they are just bad at either explaining it, or at designing it, most likely both. Then again, if I’m right, and this is generated by an LLM still gives the same impression, but leaves some room for “someone who isn’t technical, asked an LLM, and phoned this in because it looked cool, and people who don’t know any better will think so too!”

That’s way too reductive.

This infographic reeks of AI slop.

Having used pixel phones as long as they’ve been around, and used some AOSP based OS, I cannot imagine what it would be to not be able to block network access on a per-application basis.

Calculator app? No, you don’t need to read my contacts or network access to ship it to God knows who. Keyboard app that is an ipso keylogger, also no. Launcher, no… Image gallery? Fuck off.

I trust companies to do the wrong thing, always. They all sell your data. If they ever get caught, the punishment will be less than what they made by it, so why wouldn’t they.

I got the lifetime pass 5 years ago. I’ve switched to JF because of the disappointment so far about a year ago.

JF is exactly what I wanted and needed plex to be, and everything added since is a worsened product. The lifetime pass was an attempt at getting the peace of mind of “then you just have it”. If anything, only FOSS can give that.

Relevant section on Wikipedia:

The government may not criminally punish immigrants based on speech that would be protected if said by a citizen.[83] On entry across borders, the government may bar non-citizens from the United States based on their speech, even if that speech would have been protected if said by a citizen.[84] Speech rules as to deportation, on the other hand, are unclear.[85] Lower courts are divided on the question, while the leading cases on the subject are from the Red Scare.

https://en.wikipedia.org/wiki/United_States_free_speech_exceptions

Regarding the protections against illegal searches, I think all bets are off, even for US citizens.

What does “based” mean to you?

I had mixed feelings about the whole Ondsel thing. And, please correct me if I’m wrong.

Most of the significant features in 1.0, that supposedly came from Ondsel, are things that I’ve been using for perhaps 3 years now, with a fairly well known branch of FreeCAD called Linkstage3 by a user that goes by RealThunder.

I don’t know how much he was involved in Ondsel, or the merging of those features into FreeCAD, but it sure looked like a whole lot of great work wasn’t credited to mind boggling amount of work by one person.

I still use the Linkstage3 branch, because it has a lot more features still, than what was present in the 1.0 pre-release i tried some months ago. Maybe things have changed since then.

Hadn’t heard of it before. Searched for it, and came across both Path of Diablo, and Project diablo. Some polls suggested preferring the latter 2:1. I haven’t played D2 in a few decades (sheesh). Any thoughts on comparing those mods?

“Install Linux”, is usually a hurdle for most people. We should be willing to help with that part.

Alacritty is fine. If you’re not combining it with tmux and zsh/fish, id pluck those fruits first.

I’ve used DOS, 3.11 to all the way to 11. Switched to Linux as main driver around 2009. Used MacOS at work for over a year now. I occasionally boot into windows for rare game that uses some anti cheat that doesn’t play well with wine.

I’m old enough that I just want things to work. I don’t care for any fanboyism. These are my opinions:

• Windows is a mess. It has different UI from different decades, depending on what and where. NT kernel is ancient. The registry is a horror show. The only edge it has, is third party software, like propriatery drivers. that’s it. And that’s isn’t a merit of windows, but rather market share.

• MacOS is inconsistent at every turn. It’s frustrating to use, and riddled with UX bugs, and seemingly deliberate lack of functionality. The core tooling, like the file manager, is absolute garbage. The only good thing it has going it, is that the Unix core is solid. In that year, I’ve experienced a soft brick once, that almost was a hard brick, and the reason was having set the display refresh rate from 120 to 60 Hz. Something I changed BTW, because certain animation transitions in MacOS took twice as long on 120 Hz… Yeah, top notch QA there Apple.

• Linux. It has its own flaws. For sure. But as for “just works”, it happens so often, that it’s exactly why Windows and MacOS feels so frustrating. I’d have my grandmother use Linux.

And, I’m not just saying this. When I upgraded components on windows, I spent 2 hours debugging problems. One of the problems was also that it reverted a GPU driver, where every single version information was unmistakably older. It also made it not work.

I’ve also experienced that the WiFi network adapter also doesn’t work until I download some proprietary software over ethernet cable.

On Linux? I didn’t need to do a single thing in either case. It for sure didn’t use to be this way. In 2009 I was hunting WiFi drivers for fedora over ethernet. But in the last, say 5 years, on Arch, it’s been amazing. Did I mention that I use arch?

Ps: The last 4 times I’ve had problems on Linux have been:

• 1. A Windows update fucks up grub.
• 2. Reboot from windows doesn’t release hardware claim on WiFi adapter, so it doesn’t work on Linux.
• 3. The system clock is wrong, which was easy to notice because of 2. leading to a lack of remote sync. This is due to Windows storing system time as local time, and not UTC. If you do software development, you’d know how dumb the former is.
• 4. Raid partition destroyed because a windows 7 install decided to, unprompted, write a boot partition on a disk with “unknown” file system.