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Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world

thebullshitmachines.com

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Re: Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world

#91

Post by TheOtherHobbes »

tmnvdb wrote: post #82
qwGafv wrote: post #73

That's an interesting Altman quote on the site. LLMs cannot be compared to electricity and the Internet. People wanted those. LLMs were an impressive parlor trick at first but disappointing later. Many stopped using them altogether. Now there is a president who fuels the hype, shakes down rich countries for "AI" investments. The Saudi prince who lost money on Twitter is in for the new grift and praises Musk on Tucker…

People have stopped using LLMs? I wasn't aware of that. Can you share a source for that?

I know a lot of people who went through the "Oh, wow - wait a minute..." cycle. Including me.

They're approximately useful in some contexts. But those contexts are limited. And if there are facts or code involved, both require manual confirmation.

They're ideal for bullshit jobs - low-stakes corporate makework, such as mediocre ad copy and generic reports that no one is ever going to read.

Re: Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world

#92

Post by tmnvdb »

rwmj wrote: post #90
vladms wrote: post #53

Earlier quoted context omitted.

My impression is that companies in most of the fields do not like to be regulated or scrutinized, so nothing new there. While observing some people using LLMs, I realized that for a lot of people it really makes a huge difference in time saved. For me the difference is not significant, but I am generally solving complex problems, not writing nicely formatted reports where words and not numbers are relevant, so YMMV.

Is it good for one person (the writer) to save time, only for lots of other people (the readers) to have to do extra work to understand if the work is correct or hallucinated?

Is it good for one person (the writer) to ask a loaded question just to save some time on making their reasoning explicit, ony for lots of other people (the readers) to have to do extra work to understand what the argument is?

Re: Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world

#93

Post by Earw0rm »

K0balt wrote: post #35

There is a bit of very important content missing from the explanation of the autocomplete analogy. The combination of encoding / tokenization of meanings and ideas, related concepts, and mapping these relationships in vector space makes LLMs not so much glorified text prediction engines as browsers/oracles of the sum total of cultural-linguistic knowledge as captured in the training corpus. Understanding how the impl…

What they capture is not knowledge, it's word relationships.

And that can indeed be powerful, useful and valuable. They're a tool I'm grateful to have in my armoury. I can use it as a torch to shine light into areas of human knowledge which would otherwise be prohibitively difficult to access.

But they're information retrieval machines, not knowledge engines.

Re: Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world

#94

Post by tmnvdb »

nonrandomstring wrote: post #89
tmnvdb wrote: post #80

Earlier quoted context omitted.

I think the way he sketches the the AI labs as "marketing geniuses" for not just releasing their models as auto-correct is a bit cynical, as well as implying in general that these labs are muddying the waters on purpose by not agreeing with and by engaging in "hype" (believing in the technology).

Sorry, "inappropriate" might have been inappropriate :) What am I trying to say here?....that we're soon gonna find ourselves in an insoluble and exhausting debate around machine thinking and its value.

Death, taxes, and insoluble and exhausting debates around machine thinking and its value.

Re: Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world

#95

Post by TeMPOraL »

"The LLMs have no ground truth" claim (around chapter 2) that's core to the "bullshit machines" argument is itself wrong. Of course LLMs have ground truth. What do the authors think here, that the text in training corpus is random?

Hint: it isn't. Real conversations are anything but random. There's a lot of information hidden in "statistical ordering of the words", because the distribution is not arbitrary.

Statistical ground truth isn't any worse than explicitly given one. In fact, fundamentally, there only ever is statistical certainty. Realizing it is a pretty profound insight, and you'd think it should be table stakes at least in STEM, but sonehow it fails to spread as much as it should.

Re: Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world

#96

Post by ta8645 »

TheOtherHobbes wrote: post #88
Freak_NL wrote: post #74

Earlier quoted context omitted.

They address this in lesson 2: > According to philosopher Harry Frankfurt, a liar knows the truth and is trying to lead us in the opposite direction. > A bullshitter either doesn't know the truth, or doesn't care. They are just trying to be persuasive. Being persuasive (i.e., churn out convincing prose) is how LLMs were designed to be.

Some pushback on this, but it remains true. Easy to see when - for example - Claude gushes about how great all your ideas are. Also the stark absence of "I don't know."

I've never used Claude, but Perplexity often says that no definitive information about a topic could be found, and then tries to make some generalized inferences. There's a difference between a specific implementation, and the technology in general.

In any case, it's worthwhile for people to understand the limitations of the technology as it exists today. But calling it "bullshit" is a mischaracterization; I believe based on an emotional need for us to feel superior, and to dismiss the capabilities more thoroughly than they deserve.

It's a little like someone saying in the industrial revolution, "the steam shovel is too rigid, it will NEVER have the dexterity of a man with a shovel!". And while true and important to know, it really focuses on the wrong thing, it misses the advantages while amplifying the negatives.

Re: Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world

#97

Post by heikkilevanto »

Almondsetat wrote: post #60

I'm sorry, but this website is awful. Not only does it have an illogical structure (table of contents at the end? no "next lesson" button? gigantic images that fill the entire screen?), but the aesthetic of the entire thing is off. It tries to be sleek and modern with scrolling animations, but they are janky and rigid and the images are rectangles put in front of a bad gradient. Not to mention the video interviews ar…

I agree. I tried the first chapter with the Reader Mode in FireFox, and the whole long scroll hell collapsed to about one screenful of text. I have a feeling it skipped some text, but the result was a quick read that got the main points through.

I wish the whole thing was available in a plain text format, preferably in one longer document.

Re: Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world

#99

Post by ohthehugemanate »

I just want to say: I've been publicly calling them "bullshit machines" since the first big media wave. I am incredibly pleased that this mental model helps other people, too. And that the specific term sees broader use is also nice.

Also, neener neener neener I called them bullshit machines BEFORE it was cool. /humor

Seriously though the humanities have a lot to chew on with LLMs, and are incredibly important to how we live and work with them. Who knew that epistemology would become front page news, and the sexiest topic for VC?

Re: Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world

#100

Post by ImPleadThe5th »

TeMPOraL wrote: post #95

"The LLMs have no ground truth" claim (around chapter 2) that's core to the "bullshit machines" argument is itself wrong. Of course LLMs have ground truth. What do the authors think here, that the text in training corpus is random ? Hint: it isn't. Real conversations are anything but random. There's a lot of information hidden in "statistical ordering of the words", because the distribution is not arbitrary . Statist…

So if I ask ChatGpt about bears and in the middle of explaining their diet it tells me something about how much they like porridge and in the middle of habitat it tells me they live in a quaint cabin in the woods, that's ... True?

Statistically we certainly have a lot of words about 3 bears and their love for porridge. That doesn't mean it's true, it just means it's statistically significant. If I asked someone a scientific question about bears and they told me about Goldilocks, id think it was bullshit.

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