Hacker News Reader

https://cemulate.github.io/the-mlab/#y3Bt-co-extensional+lim...

This is a parody of the nLab, a wiki for collaborative work on category theory and higher category theory. As anyone who's visited is probably aware, the jargon can be absolutely impenetrable for the uninitiated -- thus, the idea for this project was born!

This project uses my package nearley-generator, a module that can turn a Nearley grammar into an efficient and controllable fake text generator. The grammar file for this site can be found at /src/grammar/nlab.ne

I figured this same thing in a similar manner. I used to make markov chains of game patches and send them to the community. Fake dota patches were a huge hit, specially since those are usually huge. Among mostly non-sense or unfunny exaggeration ("this hero now has 500 armor"), there would usually be at least 5 or 6 extremely funny lines in there, if not stuff that was outright prophetic (Fiend's Grip creates additional 1/2/3 illusions).

LLM's did a number on that unfortunately. Major subreddits banned all AI content, mostly due to the sheer infestation of really boring Midjourney content sent out by naive users and bots. Without reach, I lost interest, so no more Markov Chains.

I am sure I even remember that Valve once incorporated something from one of the fake patch notes in one of their patches, but now I cannot find it. It was something like +1 damage to something that already did a lot of damage.

Probably the Techies +25x damage talent? In 2017 [7.07] it was increased from +250 damage to +251 damage. Then in 2020 [7.28] it was increased again to +252 damage.

After some more looking around I found it, Puck's orb gained 1 movement speed in 6.87 [0] after the markov chain notes for the patch [1]. Though I think the techies one is a similar joke.

[0]: https://www.dota2.com/687

[1]: https://old.reddit.com/r/DotA2/comments/4fw6gm/how_687_would...

Hah, i felt compelled to mention Deadlock because of your Dota comments. Then i noticed your name.

I think the "uncle that doesn't know anything but claims to be an expert and will tell you his opinion" is the best description of LLMs that I can think of. They will say anything confidently without knowing anything.

>> They will say anything confidently without knowing anything.

Understanding how these algorithms work, I don't know why we would expect anything different from this?

Most ppl don't understand shit about these algorithms and will expect it be truthful and knowledgable. That is how it's marketed, despite the disclaimers..

It should be marketed more like “uncle Jim” than a trustworthy, all-domain competent oracle. I think if you just gave it a twangy accent and changed some output nouns to thingy, whatchamacallit and doohickey, people would actually be able to use it more competently.

The sheer amount of companies, media, influencers, heck even government agencies, acting otherwise? With billions of dollars on the line, there are many powerful forces pushing for people to have unrealistic expectations about LLMs (or "AI" as they call it).

A lot of money is being spent on trying to improve it too. But right now the emperor has very little clothes. It remains to be seen whether they have materialized by the time people open their eyes.

Because it's marketed as AI.

For me, my expectations are adjusted. I kinda know what to expect it to do, and it does quite well for what I use it for, essentially smart intellisense for coding.

I would have expected the people who trained these systems to not format their Q/A samples to sound authoritatively while they knew the system was going to be spouting nonsense.

LLMs are really disrupting the market for Mckinsey junior analysts meeting with clients.

Can an LLM provide the sort of psychological buffer that McKinsey Junior Analysts (some random person picked up off the street in a college town and handed a clipboard, a frequent flier card, and a six figure salary) provide to senior managers against the scrutiny of their board and chief executive?

If I want to close the paper division, and my boss wants to close the paper division, does the LLM whisper sweet nothings in our ear and show soothing Powerpoint decks about how in the eyes of an objective observer, the paper division is unprofitable and there would be no career risk in closing it?

It's not a sexual thing I swear, it's a sort of comforting intimacy that needs to be injected into the business process in order to cope with the pressures executives feel. I don't know that anybody has trained an LLM to do that yet.

I think this is the next sequel to the movie "Her".

You bring up a good point though. Very dystopian idea of a new type of enterprise tooling that emerges to soothe and calibrate human knowledge workers. Very Severance Wellness room.

Perfectly humanlike

We gave up the pursuit of pure crystalline Intelligence and instead just remade ourselves. Hopefully the AIs will be able to do better.

Yeah. We don't need Artificial Intelligence. We need to discover Actual Intelligence :)

Indeed, the more I use LLMs and see the confabulated output, I've started seeing similar in how actual people talk.

> modern LLMs are wrong in a "My uncle doesn't know basic geography" way

Oh, certainly not. I have been using LLM chatbots extensively this week. If your uncle were not just confident while stating falsities, but uncapable of self-assessment, he would have been murdered.

Or made a stellar career as a salesman or politician.

Until you are caught (in good societies).

Or fresh ones. Established democracies end up with political structures that self-select for being able to sound right and cooperate right, entirely independent of truth and merit.

I coincidentally just stumbled on a recent implicit comment by Angél Boligan Corbo:

Title: "The Talker" - https://image.cagle.com/287573/980/-the-talker.png

That sounds like all bureaucracies.

(a) That site is very funny. Thanks for sharing!

(b) The kids-vs-uncle metaphor is spot on in my experience too, and also illustrates how far these language models have come.

First thing I read on that page:

> There is no charge associated with your streamed applications, simply click Enable Microphone from the ElastiCache documentation.

It's way funnier when our brains try to make sense of the nonsense.

I played around with a Markov generator many years ago, trained on the corpus of everything I had ever said in a specific IRC channel. The resulting messages were pretty interesting - I specifically remember the realization that I apparently (used to, though honestly still do, too) talk about LEDs a lot...

Reminds me of git man pages generators. Extremely fun as well when you can't quite tell if it's real.

Ref: https://git-man-page-generator.lokaltog.net/

> I realized then that the humor of those early markov generations was the ridiculousness. The point where, a few words or sentences in, you realized it was all nonsense. LLM's these days are too good for that - the text they generate is sometimes wrong, but rarely nonsense in a humorous way.

This is the biggest challenge I run into when I see LLM Generated nonsense.

So much stuff that ChatGPT spits out is close enough to true that Brandolini is laughing.

But it's also that it's borrowing on stuff that's already there so it can't really get that 'creative' either.

> What I found was, ultimately, it was way less fun

I wonder if there is combination of temperature and prompt engineering that could make it interesting.

I just asked chatgpt to create an Aws product announcement in the style of Markov generated text and it was pretty good

I did the same thing and used it as the chum for a 'bot motel. (A 404 handler that always returns something and... success!). I trained it on a mixed NASA space shuttle and veterinary science corpus just to make it really bizarre.