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CheatGPT

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Re: CheatGPT

#391

Post by Aperocky »

cheeze wrote: post #382
Aperocky wrote: post #344

Earlier quoted context omitted.

This take is widely prevalent in every single ChatGPT discussion. I'll quote myself for discussion for a previous article: https://news.ycombinator.com/item?id=34746348 > I've find two groups of people on this subject, first one has taken a graduate level stat course and/or ML course, and may have work experience in machine learning/data science. The latter camp is more numerous and did not do those things. > The lat…

The big question I'd ask is "do we need AGI?" Surely an LLM could take over the ordering flow at say, Jack in the Box today. That's gotta be true for a lot of different situations.

I see this as another step in automation, like the sewing machine, the internal combustion engine, the microchip, internet, etc.

Re: CheatGPT

#392

Post by sovande »

kurisufag wrote: post #222
throw310822 wrote: post #209

I don't understand how most of the comments here seem to be along the lines of "these interview questions are useless now" or "we need to rethink education, it hasn't kept up". These all seem absurdly myopic to me. What we're seeing is the first instance, still very limited and imperfect, of AGI. This is not going to make some interview questions obsolete, or give students more tools to cheat with their homework. It…

>What we're seeing is the first instance, still very limited and imperfect, of AGI absolutely not. language-model text generation is actually about as non-general as it gets -- they are fundamentally incapable of understanding anything at all, ever. they can't do math, work through basic logic problems, or produce any output that isn't just an assumed logical continuation of the input.

> they can't do math, work through basic logic problems

ChatGPT begs to differ:

Me: How do I measure 4 liters when I have a 3 liter bottle and a 5 liter bottle?

ChatGPT: Here are the steps to measure 4 liters using a 3 liter and a 5 liter bottle:

Fill the 5 liter bottle completely with water. Pour 3 liters from the 5 liter bottle into the 3 liter bottle, leaving 2 liters in the 5 liter bottle. Now you have 3 liters of water in the 3 liter bottle, and 2 liters of water in the 5 liter bottle. Empty the 3 liter bottle, and pour the 2 liters from the 5 liter bottle into the 3 liter bottle. Fill the 5 liter bottle again with water, and pour 1 liter from the 5 liter bottle into the 3 liter bottle, which already has 2 liters of water. You will be left with 4 liters of water in the 5 liter bottle, which is the desired amount.

Re: CheatGPT

#393

Post by petilon »

JohnFen wrote: post #333
zeckalpha wrote: post #329

Earlier quoted context omitted.

Can you point to where the thinking happens in a human?

Nope. But I don't have to do that to understand that LLMs do not assess truth or accuracy of anything.

There is research that shows humans are also predicting the next word.

I posted that here: https://news.ycombinator.com/item?id=34875324

Re: CheatGPT

#394

Post by analog31 »

grugagag wrote: post #334
stuckinhell wrote: post #283

Earlier quoted context omitted.

I agree 1000000%. Watching all the ART AI's change so radically fast, Watching ChatGPT being adopted by so many people at my company. Watching people say art will shift to prompt engineering, then watching prompt engineering being automated away already! Watching the rise of stable diffusion tooling like invokeai, controlnet, and more. Watching youtube videos of people integrating openai and stable diffusion together…

It is a paradigm shift and whoever happens to be on the good side of this may survive just a bit longer before they too become redundant.

Do we know if anything, other than luck, will determine who's on which side? Or, if any decisive action on anybody's part is more likely to pay off than just staying mentally flexible, watching, and waiting?

Re: CheatGPT

#395

Post by EamonnMR »

throw310822 wrote: post #209

I don't understand how most of the comments here seem to be along the lines of "these interview questions are useless now" or "we need to rethink education, it hasn't kept up". These all seem absurdly myopic to me. What we're seeing is the first instance, still very limited and imperfect, of AGI. This is not going to make some interview questions obsolete, or give students more tools to cheat with their homework. It…

Butlerian Jihad when?

Re: CheatGPT

#396

Post by canjobear »

lapinot wrote: post #325
iameli wrote: post #284

Earlier quoted context omitted.

People seem so convinced of this and I just don't get it. I'm seeing this comment through my eyeballs, generating some pertinent text in my brain, and outputting it back out. But so many people seem convinced convinced this process is something radically, fundamentally, irreducibly different than what ChatGPT is doing internally, and I don't get why. Is it because I have a consciousness with an internal narrative and…

LLM (and deep learning in general) are to AGI what bogosort is to sorting. For some reason beyond me people think it's very important to not try to understand anything about the structure of the problem you're trying to solve and just make a very general algorithm which will be suboptimal in just about every way except for the generality of it's code. Seeing the world as a trillion dimensional token soup is definitel…

No other approach has worked as well for natural language, and not for lack of trying.

Re: CheatGPT

#397

Post by pixl97 »

dpflan wrote: post #348
JohnFen wrote: post #317

Earlier quoted context omitted.

> through various kinds of data abstraction, reasoning by analogy, and other techniques similar to what humans do. No, that's exactly not how LLMs work. They are extremely good at predicting what sentences resemble the sentences in their training data and creating those. That's all. People are getting tripped up because they are seeing legitimate intelligence in the output from these systems -- but that intelligence…

“People are getting tripped up because they are seeing legitimate intelligence in the output from these systems -- but that intelligence was in the people who wrote the texts that it was trained with, not in the LLM.” This is the real magic. Let’s train ChatGPT on absolute garbage information and compare the intelligence of the two.

Let's take a kid and teach them garbage information as they are growing up... minimize as much 'real knowledge' as possible and see what comes out.

Re: CheatGPT

#398

Post by pixl97 »

RhysU wrote: post #296
adastra22 wrote: post #241

Earlier quoted context omitted.

Have you actually used any of these products? GPT et al are perfectly capable of taking knowledge from any one domain and applying it towards the solution of any other problem domain, through various kinds of data abstraction, reasoning by analogy, and other techniques similar to what humans do. It makes plenty of goofups along the way, just like humans do. But if your requirement is that it performs absolutely perfe…

To be completely ridiculous, we'll have AGI when it can convince a human to mate with it over any other human followed by raising its offspring to a successful adulthood. This is the game we're all playing.

Parasites are also lifeforms. It doesn't have to convince you to breed, it has to convince you to keep it plugged in and feeding ever increasing amounts or computing power.

In theory GPT is there with the right prompt.

Re: CheatGPT

#399

Post by Jtsummers »

dcow wrote: post #367
Jtsummers wrote: post #351

Earlier quoted context omitted.

Let bindings in Lisp are not const. You can use `setf` (among others) to mutate the variable. For instance, this works just fine in Lisp: (let ((x 1)) (print x) ;; => 1 (incf x) (print x)) ;; => 2 Scheme also allows let bindings to be mutated, but using `set!`.

I assumed scheme and lisp were the same here semantically. Bad assumption on my part. My experience is primarily with scheme. Similar Rust and Swift allow let bindings to be shadowed but you need to re-declare your intent. You can't just mutate the binding on a whim.

I'm confused, Scheme also permits mutation of let bindings so Lisp and Scheme do have similar semantics here. Neither language provides immutable (const) let bindings. Scheme just makes it more obvious (by convention) when you may have mutation, through function and form names ending in !.

Re: CheatGPT

#400

Post by guy98238710 »

JohnFen wrote: post #317
adastra22 wrote: post #241

Earlier quoted context omitted.

Have you actually used any of these products? GPT et al are perfectly capable of taking knowledge from any one domain and applying it towards the solution of any other problem domain, through various kinds of data abstraction, reasoning by analogy, and other techniques similar to what humans do. It makes plenty of goofups along the way, just like humans do. But if your requirement is that it performs absolutely perfe…

> through various kinds of data abstraction, reasoning by analogy, and other techniques similar to what humans do. No, that's exactly not how LLMs work. They are extremely good at predicting what sentences resemble the sentences in their training data and creating those. That's all. People are getting tripped up because they are seeing legitimate intelligence in the output from these systems -- but that intelligence…

Vast majority of knowledge any one of us has comes from cultural heritage. We all stand on the shoulders of giants. And knowledge, not computation, is behind intelligent behavior.
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