GPT-4 Designed a Programming Language • Hacker News Board

Re: GPT-4 Designed a Programming Language

#281

Post by AnimalMuppet » Thu, Mar 16, 2023, 1:11 PM UTC

RHSman2 wrote: post #199

raincole wrote: post #139

Earlier quoted context omitted.

It's totally possible that humans don't do reason. It's possible that the parrot in our brain makes the decision, and then the "frontend" of our mind makes fake reasons that sound logical enough. But it's just a possibility, and I don't find it's particularly convincing.

Fast thinking/slow thinking by Daniel Kannerman (and the Unlocking Project) is a book people need to read and understand. When we slow think, we work things out, when we fast think we are parrots.

Hmm. If you want to argue that ChatGPT has half of what an AI needs, I could buy that a lot more than I buy "ChatGPT is the road to AGI".

Do inference engines have the other half? Or Cyc plus an inference engine? Can that be coupled to ChatGPT?

My own (completely uninformed) take is that such a coupled AI would be very formidable (far more than ChatGPT), but that it will be very hard to do so, because the representations are totally different. Like, really totally - there is no common ground at all.

Re: GPT-4 Designed a Programming Language

#282

Post by AnimalMuppet » Thu, Mar 16, 2023, 1:15 PM UTC

ummonk wrote: post #194

jmcgeeney wrote: post #72

Earlier quoted context omitted.

The difference between humans and sophisticated stochastic parrots is reason . The most common kinds of mistakes that chatGPT currently makes are when it says things that are not simply wrong, but don't make sense. Perhaps it will be possible to emulate reason with enough data, training, parameters, etc, but without some representation of the ability to understand what you don't know, what you know, and what follows…

I’m sure a stochastic parrot model could be trained to exhibit reasoning, but the issue is that there isn’t any automated loss function which can discern whether the output of a large language model exhibits reasoning or is illogical. When you train based on text similarity, it will have a hard time learning logic, especially given the amount of illogical writing that is out there.

Hmm. That's classically the job of an educator - to choose good training material, not just to let students read the internet all day. Would a ChatGPT trained on a carefully curated reading list do better than one trained on a wider reading list?

But it's more than that. A good educator teaches students to evaluate sources, not to just believe everything they read. As far as I can tell, ChatGPT totally lacks that, and it hurts.

Re: GPT-4 Designed a Programming Language

#283

Post by AnimalMuppet » Thu, Mar 16, 2023, 1:24 PM UTC

okaleniuk wrote: post #93

marviel wrote: post #16

Earlier quoted context omitted.

Author here -- I think it is a stochastic parrot, don't get me wrong. But my argument is that humans are also , at some level, sufficiently advanced stochastic parrots. At least, as it pertains to many creative endeavors. You're always building on the back of something that comes before. We're all just remixing ideas we've heard before. I mean even this comment -- none of the words I'm saying are new, and many of the…

I would go even further. People are not even that advanced stochastic parrots. In the similar task, we failed just as spectacularly as the GPT-4 did right now. Rust, Zig, Julia, Kotlin, and dozens smaller "new" languages fail to bear a smear of originality in them. Their authors remixed old ideas in different proportions and got different grammars as a result. That's something an LLM can do and much faster too. But t…

> Language models can and are useful if you specifically want to avoid marginality. To reduce noise, to remove errors.

But this makes me think of Shannon Information Theory. What you're describing is something that has no actual information (in the Shannon sense) at all.

And maybe that's why so much GPT output reads so blandly. Even the ones that are not glaringly wrong still read like... like food with no seasoning.

Re: GPT-4 Designed a Programming Language

#284

Post by tjr » Thu, Mar 16, 2023, 1:34 PM UTC

theonemind wrote: post #158

tjr wrote: post #150

Earlier quoted context omitted.

ChatGPT. I was under the impression ChatGPT was now running with GPT-4? But if not, then I stand mistaken.

An email from OpenAI 2 days ago said that GPT4 is on the paid ChatGPT Plus plan, and "severely resource constrained" with a dynamically adjusted usage cap based on availability. Seems like for today, if you're not sure if you're using GPT4, you're not.

Thank you!

Re: GPT-4 Designed a Programming Language

#285

Post by kristoff_it » Thu, Mar 16, 2023, 1:45 PM UTC

okaleniuk wrote: post #93

marviel wrote: post #16

Earlier quoted context omitted.

Author here -- I think it is a stochastic parrot, don't get me wrong. But my argument is that humans are also , at some level, sufficiently advanced stochastic parrots. At least, as it pertains to many creative endeavors. You're always building on the back of something that comes before. We're all just remixing ideas we've heard before. I mean even this comment -- none of the words I'm saying are new, and many of the…

I would go even further. People are not even that advanced stochastic parrots. In the similar task, we failed just as spectacularly as the GPT-4 did right now. Rust, Zig, Julia, Kotlin, and dozens smaller "new" languages fail to bear a smear of originality in them. Their authors remixed old ideas in different proportions and got different grammars as a result. That's something an LLM can do and much faster too. But t…

> I would go even further. People are not even that advanced stochastic parrots. In the similar task, we failed just as spectacularly as the GPT-4 did right now. Rust, Zig, Julia, Kotlin, and dozens smaller "new" languages fail to bear a smear of originality in them. Their authors remixed old ideas in different proportions and got different grammars as a result. That's something an LLM can do and much faster too.

We are in good part stochastic parrots for sure, but there's a small nuance that is completely lost in your reasoning and which is what makes the difference today between humans and GPT.

In those languages, reusing commonly known syntax is an explicit feature. Whenever the language had no reason to introduce something new, it used known idioms to lower the amount of things one has to learn to use the language.

Occasionally though, a language will have something unusual, but it won't be for random reasons, but instead to mark something unique and interesting that was added to the language to tackle a facet of programming in a new way.

Rust has lifetime annotations, Zig inverts the usage of async/await (https://kristoff.it/blog/zig-colorblind-async-await/) to support color-blindness.

Present day GPT wouldn't be able to come up with a borrow checker or colorblind asyncness all by itself.

Re: GPT-4 Designed a Programming Language

#286

Post by bsaul » Thu, Mar 16, 2023, 1:47 PM UTC

noelherrick wrote: post #259

bsaul wrote: post #247

Earlier quoted context omitted.

we ( the software industry ) have spent the last 60 years intruding in other people's job and automating most of their task using computers. Under the saying "it will remove the most boring parts of your activity, and let you focus on where you really make a difference " i guess it's time to taste a bit of our own medecine.

OP is clearly distressed and you replied with with what comes out as “it’s your fault and you deserve this.” It costs nothing to refrain from replying and only the smallest amount of effort to provide some solidarity with your fellow human. OP, I feel you-I had a similar response to this clearly orchestrated PR campaign. OpenAI really loves that people think that it can replace the entire tech industry with an API. I…

there's another way to look at my comment : all the other jobs we "automated" transformed, but kept existing under one form or another.

And so will ours.

Re: GPT-4 Designed a Programming Language

#287

Post by lostmsu » Thu, Mar 16, 2023, 1:58 PM UTC

KyeRussell wrote: post #206

eitland wrote: post #198

Earlier quoted context omitted.

Sorry if I am missing something here, but I think we all know well functioning, productive humans, maybe even in our field, who wouldn't have been able to create this language or a similarly well thought out one. I know a competent man should be able to "change a diaper, plan an invasion, butcher a hog, conn a ship, design a building, write a sonnet, balance accounts, build a wall, set a bone, comfort the dying, take…

Don’t bother. Hacker News takes the throne for “I could do this in a weekend” rhetoric.

"in a weekend" now is too slow. They'd have to do it in 5 minutes or even less.

Re: GPT-4 Designed a Programming Language

#288

Post by tpoacher » Thu, Mar 16, 2023, 2:13 PM UTC

yowzadave wrote: post #141

Last year, when Blake Lemoine was fired by Google for claiming his AI was sentient, a lot of people on this website sensibly noted that the danger of these chatbots was not that they were sentient, but that average people could easily be tricked into thinking that they were. And now here we are: it seems we tech people are every bit as susceptible to this kind of thinking as the average joes we looked down on. Actual…

Whenever there is a simple error that most laymen fall for, there is always a slightly more sophisticated version of the same problem that experts fall for.

--Amos Tversky

Re: GPT-4 Designed a Programming Language

#289

Post by HervalFreire » Thu, Mar 16, 2023, 2:22 PM UTC

inkysigma wrote: post #255

HervalFreire wrote: post #235

Earlier quoted context omitted.

Taking a long time to learn something doesn't mean that something wasn't learned nor understood. Two separate topics. Even chatGPT understands this: ME: Does someone or something requiring a thousand examples to understand something imply that it doesn't understand anything? CHATGPT: No, requiring a thousand examples to understand something does not necessarily imply that someone or something doesn't understand anyth…

I have to disagree with that. Like maybe for a toy example to demonstrate what I'm talking about, imagine I was teaching you the addition operation mod 100 and I gave a description of the operation f(x, y) = x + y % 100 for x, y in Z_100. If you take more than 100^2 samples to learn the function, I'm not sure you understand the function. Obviously, in that many samples, you could've just specified a look up table wit…

You're describing over fitting to some look up table.

Can't be what's happening here. Because the examples LLMs are answering are well out of bounds of the "100^2" training data.

The internet is huge but it's not that huge. One can easily find chatGPT saying, doing or creating things that obviously come from a generalized model.

It's actually trivial to find examples of chatGPT answering questions with responses that are wholly unique and distinct from the training data, as in the answer it gave you could not have existed anywhere on the internet.

Clearly humans don't need that much training data. We can form generalizations from a much smaller sample size.

This does not indicate that for machine learning a generalization doesn't exist in LLMs when clearly the answers demonstrate that it does.

Re: GPT-4 Designed a Programming Language

#290

Post by HervalFreire » Thu, Mar 16, 2023, 2:43 PM UTC

AnimalMuppet wrote: post #280

HervalFreire wrote: post #11

quotation from the link: "LLMs in the GPT family have read every programming language in the world, billions of times. It's been known for some time that these agents can write small snippets of code with some limited success. However, to my knowledge, none of these agents have ever been asked to make their own programming language. This type of task is a bit more complex, and requires a bit more creativity and fores…

> I'd argue that remixing is the fundamental force of creativity. Yes, but. Creativity - real creativity - is in choosing the right pieces to remix out of the immense amount of what's available. And, perhaps just as important, choosing what not to put in the remix. There's an immense difference between a meal prepared by a good chef, and throwing random ingredients in a blender. They both remix. But they are not remo…

Your example here is obvious right? All humans agree with you because all humans can tell the difference.

The thing with these LLMs is that it's exhibiting both seemingly random remixes and remixes with extreme creativity.

A lot of people see some error and flaw with chatGPT or they don't dig deep enough and they miss the fact that there are many instances of intelligent remixing of creative data. Real creativity. Trust that the opposing party has the intelligence to not be tricked by some obvious answer that an LLM took from a look up table and that the opposing party saw something wholly novel and unique.

The main issue here is that people are getting hung up on the part where chatGPT fails to be creative and are completely missing the fact that it can be successful as well.