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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

#151

Post by dijksterhuis »

ta8645 wrote: post #145
dijksterhuis wrote: post #140

Earlier quoted context omitted.

reality is infinite. a corpus of training data from the internet is finite. any finite number divided by infinity ends up tending towards zero. so, mathematically at least, the training data is not a sufficient sample of reality because the proportion of reality being sampled is basically always zero! fun with maths ;) > What exactly do you think those math pipelines represent? probability distributions of human lang…

You're really missing the point and getting lost in definitions. The entire point of human language is to model reality. Just because it is limited, inexact, and imperfect does not disqualify it as a model of reality. Since LLMs are directly based on that language, they are definitely based on and are a model of reality. Are they perfect? No. Are they limited? Yes. Are they "bullshit"? Only to someone who is judging…

and herein lies the rub.

> The entire point of human language is to model reality.

is it? are you absolutely certain of that fact? is language not something that actually has a variety of purposes?

fiction novels usually do not describe our reality, but imagined realities. they use language to convey ideas and concepts that do not necessarily exist in the real world.

ref: Philip k dick.

> Since LLMs are directly based on that language, they are definitely based on and are a model of reality.

so LLMs are an approximation of an approximate model of reality? sounds like the statistical equivalent of taking an average of averages!

i am playing with you a bit here. but hopefully you see what im getting at.

by approximating something that’s approximate to start with, we end up with something that’s even more approximate (less accurate), but easier than doing it ourselves.

which is the whole USP of these things. why think about things when ChatGPT can output some approximation of what you might want?

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

#152

Post by krupan »

ta8645 wrote: post #96
TheOtherHobbes wrote: post #88

Earlier quoted context omitted.

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…

If not bullshit then what would you call it?

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

#153

Post by tmnvdb »

jcgrillo wrote: post #146
tmnvdb wrote: post #133

Earlier quoted context omitted.

The costs are a problem. We don't have hard evidence that this will be solved, but with algorithmic efficiency and raw compute costs both changing rapidly, the cost per token has gone down by about a factor of 10 per year for the last 3 years, i.e. 1000x over 3 years.

As far as I can tell, those charts are merely describing the price per token that LLM hosting companies are charging, not what running the model actually costs. The distinction is important for two reasons: 1. These companies are heavily subsidized by huge amounts of venture investment 2. If I'm integrating this technology into my web product there's absolutely no way I'll be adding a 3rd party company as a dependenc…

This is incorrect, there are real effiency gains.

Slightly old by the standards of this field, but a good overview: https://arxiv.org/abs/2403.05812

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

#154

Post by ta8645 »

krupan wrote: post #152
ta8645 wrote: post #96

Earlier quoted context omitted.

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…

If not bullshit then what would you call it?

As the technology exists today: imperfect, often prone to mistakes, and unable to relay confidence levels. These problems may be addressed in future implementations.

That's the same message, without any emotional baggage, or overly dismissive tone.

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

#155

Post by krupan »

uh_uh wrote: post #147
roland35 wrote: post #130

I like the term "bullshit" over "hallucination". These AI machines have no perceptions, no concept of truth, so indeed they are just spewing out words with no regard for truth. And unfortunately the cost of spreading bullshit has gone down to almost 0.

So why are they SOTA translators? Would you consider old translation software bullshit generators? Because LLMs can do their job, and more.

Those who sell these things as almighty powerful AI, so powerful and dangerous that it should be regulated (so my competition can't keep up with me), are responsible for this overreaction. Yes, not everything LLMs produce is bullshit but enough is, contrary to how they were marketed, that people are reacting this way.

In other words, you don't counter hyperbolic and downright false marketing with subtleties.

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

#156

Post by jaimebuelta »

gsky wrote: post #110

People said the world wouldn't need more than 10 computers. Newyork times ridiculed space industry and etc.. AI is gonna disrupt all industries

It’s totally possible that the net result is good (which is still quite early to really know), but it present new problems. For example, the creation of the car is probably good in general, but it has important issues that requires to be taken into account (accidents, pollution, city planning challenges, etc)

I’ve lived enough hype cycles to know that we are always very close to use VR every day or have autonomous cars… It took around 25 years to move from “we will pay with our mobile phones” to that becoming a reality.

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

#157

Post by Johanx64 »

myaccountonhn wrote: post #144
Johanx64 wrote: post #141

Somebody made a website to express their opinion - wherein their opinion can be surmised by reading the domain name. Text is scaled to 300% to indicate just how important and authoritative they think their opinion is. And it talks down to you in a "here comes the expert" style, with an atrocious aimed-at-preschoolers presentation. No thank you.

Two university professors in data science and computational biology are not just “somebody”.

People that find professors and similar in high esteem usually haven't spent enough time in or around academia and academics and for that reason still maintain some innocent aura of mystique and prestige around it in their mind.

Quite literally anyone with a bit of persistence could become a professor (and this by far isn't even a top university either).

They are quite literally just a somebody with an opinion just like anybody else. An opinion barked down to you with 300% scaled fonts and preschooler illustrations.

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

#158

Post by jaimebuelta »

picafrost wrote: post #20

I think a great number of working professionals need a course like this too. I am already tired of ChatGPT being cited by the less experienced as an invisible expert in the room during technical discussions.

Write well is think well. A big part of the writing process is being forced to structure your thoughts and ideas, and I am worried that we focus too much on the end result without understanding the process that lead to good outcomes.

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

#159

Post by m0llusk »

HPsquared wrote: post #47
anon373839 wrote: post #22

Earlier quoted context omitted.

“Bullshit” actually means something: > In philosophy and psychology of cognition, the term "bullshit" is sometimes used to specifically refer to statements produced without particular concern for truth, clarity, or meaning, distinguishing "bullshit" from a deliberate, manipulative lie intended to subvert the truth. https://en.m.wikipedia.org/wiki/Bullshit It’s really an ideal term to describe what LLMs do.

I prefer "waffle" https://en.m.wikipedia.org/wiki/Waffle_(speech) "Waffle machines" is even kind of funny.

Makes me imagine coming up to the hindquarters of a bull with a waffle machine on an extension cord.

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

#160

Post by HarHarVeryFunny »

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…

Well, duh ... of course there are statistical regularities in the data, which is what LLMs learn. However, the LLM has no first hand experience of the world described by those words, so the words (to an LLM) are not grounded.

So, the LLM is doomed to only be able to predict patterns in the dataset, with no knowledge or care as to whether what it is outputting is objectively true or not. Calling it bullshitting would be an anthromorphism since it implies intention, but it's effectively what an LLM does - just spits out words without any care (or knowledge) as to the truth of them.

Of course if there is more truth than misinformation and lies in the dataset, then statistically that is more likely to be output by an LLM, but to the LLM it's all the same - just word stats, just the same as when it "hallucinates" and "makes something up", since there is always a non-zero possibility that the next word could be ... anything.

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