Want some cuteness overload? Even big felines love cardboard boxes!

Another important detail is that Digg v4 pissed off most of the userbase, so the impact was pretty much immediate. Reddit APIcalypse pissed off only power users instead; the impact will only come off later (sadly likely past IPO).

Lunix sucks so much that it got stuck into the version 2 for years.

A compiler does it “good enough”, but AI = god in a bottle, thus it’ll do it “perfectly”. And for perfection you need to edit the raw metal using butterflies and cosmic rays, it’ll be the only real programmer to ever appear. Pressures like time and focus will stop existing. Why? Because AI = god, QED.

…or at least that’s the sort of crap that those Silicon Valley muppets believe in. The content itself doesn’t make sense, but why that pile of nonsense is uttered does - a fringe religious-like belief increasingly common among them.

That other poster is likely trying to deliver a point, that Musk probably never read a book, by clipping the sentence of the other poster.

Websearch “transhumanism silicon valley”, and it starts making sense: Musk has faith that artificial general intelligence is coming, Soon®, and that it’ll replace grunt labour like programming.

It isn’t “Hangul” that is saving the language, but the fact that it’s getting an orthography. That orthography could be theoretically in any writing system - not just Latin or Arabic (both already exist for Cia-Cia, contrariwise to what the video claims), but even a native one or Cyrillic or even, dunno, the Cherokee syllabary.

Abidin looks informed on the matter; the same cannot be said about whoever produced this video. I’ll highlight a few issues.

[0:33] - pretty much all languages are “syllable-based”. They organise sounds into syllables. The video is likely trying to convey that it’s a CV (consonant, vowel, repeat) language, unlike, say, Russian or English (that cram quite a lot of consonants in a single syllable).

[0:36] The video is trying to use “transliterated” as a posh synonym for “spelled”; both are not the same thing. Transliteration is to convert text from a script from another; for example, “Quis credis esse, Bellum?” (Latin, using the Latin script) → “Кўис кредис ессе, Беллум?” (Latin, using the Cyrillic script instead) is transliteration.

And you can spell pretty much any language in any writing system. The association between grapheme and sounds (or phonemes) is arbitrary.

You might say “but the Latin alphabet doesn’t have a letter for /ɓ/!” - well, it doesn’t have a letter for /ʃ/ either. Italian handled it by spelling it ⟨sci⟩, English as ⟨sh⟩, Polish as ⟨sz⟩, Portuguese kind of repurposed ⟨x⟩. And the current Latin spelling for Cia-Cia - that you can check here - handled /ɓ/ just fine, using a similar approach as the Hangul one.

Musk being an assumer (note how he’s vomiting certainty on future events) doesn’t surprise me a tiny bit.

If I were to discipline my cats by picking them up, one of them would be exactly like in this pic. The other would be tearing my arms apart with the claws of her back legs.

Aaaaah. I really, really wanted to complain about the excessive amount of keys.

(My comment above is partially a joke - don’t take it too seriously. Even if a new key was added it would be a bit more clutter, but not that big of a deal.)

The source that I’ve linked mentions semantic embedding; so does further literature on the internet. However, the operations are still being performed with the vectors resulting from the tokens themselves, with said embedding playing a secondary role.

This is evident for example through excerpts like

The token embeddings map a token ID to a fixed-size vector with some semantic meaning of the tokens. These brings some interesting properties: similar tokens will have a similar embedding (in other words, calculating the cosine similarity between two embeddings will give us a good idea of how similar the tokens are).

Emphasis mine. A similar conclusion (that the LLM is still handling the tokens, not their meaning) can be reached by analysing the hallucinations that your typical LLM bot outputs, and asking why that hallu is there.

What I’m proposing is deeper than that. It’s to use the input tokens (i.e. morphemes) only to retrieve the sememes (units of meaning; further info here) that they’re conveying, then discard the tokens themselves, and perform the operations solely on the sememes. Then for the output you translate the sememes obtained by the transformer into morphemes=tokens again.

I believe that this would have two big benefits:

1. The amount of data necessary to “train” the LLM will decrease. Perhaps by orders of magnitude.
2. A major type of hallucination will go away: self-contradiction (for example: states that A exists, then that A doesn’t exist).

And it might be an additional layer, but the whole approach is considerably simpler than what’s being done currently - pretending that the tokens themselves have some intrinsic value, then playing whack-a-mole with situations where the token and the contextually assigned value (by the human using the LLM) differ.

[This could even go deeper, handling a pragmatic layer beyond the tokens/morphemes and the units of meaning/sememes. It would be closer to what @njordomir@lemmy.world understood from my other comment, as it would then deal with the intent of the utterance.]

Not quite. I’m focusing on chatbots like Bard, ChatGPT and the likes, and their technology (LLM, or large language model).

At the core those LLMs work like this: they pick words, split them into “tokens”, and then perform a few operations on those tokens, across multiple layers. But at the end of the day they still work with the words themselves, not with the meaning being encoded by those words.

What I want is an LLM that assigns multiple meanings for those words, and performs the operations above on the meaning itself. In other words the LLM would actually understand you, not just chain words.

Complexity does not mean sophistication when it comes to AI and never has and to treat it as such is just a forceful way to make your ideas come true without putting in the real effort.

It’s a bit off-topic, but what I really want is a language model that assigns semantic values to the tokens, and handles those values instead of directly working with the tokens themselves. That would be probably far less complex than current state-of-art LLMs, but way more sophisticated, and require far less data for “training”.

Oh “great”, more crap between Ctrl and Alt.

[Grumpy grandpa] In my times, the space row only had five keys! And we did more than those youngsters do with eight, now nine keys!

Ah, got it. My bad. Yeah, not providing anything is even lazier, and unlike “lazy” bash scripts it leaves the user clueless.

I like them, even for software installation. Partially because they’re lazy - it takes almost no effort to write a bash script that will solve a problem like this.

That said a flatpak (like you proposed) would look far more polished, indeed.

Frankly in this case even a simple bash script would do the trick. Have it check your distro, version, and architecture; if you got curl and stuff like this; then ask you if you want the stable or beta version of the software. Then based on this info it adds Mullvad to your repositories and automatically install it.

You’re welcome.

I think that people being jerks take for granted how confusing this might be, if you’re new; we (people in general) tend to take vocab that we already know for granted, as well as solutions for small problems. …except that it doesn’t work when you’re starting out, and we all need to start out somewhere, right.

You have two options: install curl (check @TrickDacy@lemmy.world’s comment) or do it manually. Installing curl is the easiest.

If you want to do it the hard way (without the terminal), here’s how:

1. Download the file https://repository.mullvad.net/deb/mullvad-keyring.asc from your web browser.
2. Open your file browser as administrator. There’s probably some link for that in the Menu.
3. Move the file that you just downloaded to the directory /usr/share/keyrings/

It’s less complicated than it looks like. The text is just a poorly written mess, full of options (Fedora vs. Ubuntu, repo vs. no repo, stable vs. beta), and they’re explaining how to do this through the terminal alone because the interface that you have might be different from what they expect. And because copy-pasting commands is faster.

Can’t I just download a file and install it? I’m on Ubuntu.

Yes, you can! In fact, the instructions include this option; it’s under “Installing the app without the Mullvad repository”. It’s a bad idea though; then you don’t get automatic updates.

A better way to do this is to tell your system “I want software from this repository”, so each time that they make a new version of the program, yours get updated.

but I have no idea what I’m doing here.

I’ll copy-paste their commands to do so, and explain what each does.

sudo curl -fsSLo /usr/share/keyrings/mullvad-keyring.asc https://repository.mullvad.net/deb/mullvad-keyring.asc
echo "deb [signed-by=/usr/share/keyrings/mullvad-keyring.asc arch=$( dpkg --print-architecture )] https://repository.mullvad.net/deb/stable $(lsb_release -cs) main" | sudo tee /etc/apt/sources.list.d/mullvad.list
sudo apt update
sudo apt install mullvad-vpn

The first command boils down to “download this keyring from the internet”. The keyring is a necessary file to know if you’re actually getting your software from Mullvad instead of PoopySoxHaxxor69. If you wanted, you could do it manually, and then move to the /usr/share/keyrings directory, but… it’s more work, come on.

The second command tells your system that you want software from repository.mullvad.net. I don’t use Ubuntu but there’s probably some GUI to do it for you.

The third command boils down to “hey, Ubuntu, update the list of packages for me”.

The fourth one installs the software.