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Reports of code's death are greatly exaggerated

stevekrouse.com

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Re: Reports of code's death are greatly exaggerated

#161

Post by djeastm »

somewhereoutth wrote: post #128
derrak wrote: post #47

Earlier quoted context omitted.

Maybe you’re right about modern LLMs. But you seem to be making an unstated assumption: “there is something special about humans that allow them to create new things and computers don’t have this thing.” Maybe you can’t teach current LLM backed systems new tricks. But do we have reason to believe that no AI system can synthesize novel technologies. What reason do you have to believe humans are special in this regard?

In the grand scale of things, a computer is not much more than a fancy brick. Certainly it is much closer to a brick than to a human. So the question is more 'why should this particularly fancy brick have abilities that so far we have only encountered in humans?'

> fancy brick

If we're going to be reductionist we can just call humans "meat sacks" and flip the question around entirely.

Re: Reports of code's death are greatly exaggerated

#162

Post by coldtea »

lateforwork wrote: post #125
irishcoffee wrote: post #117

Earlier quoted context omitted.

The LLM was trained on 100% of humans, the 99% you’re scoffing at is feeding the LLM answers.

100% (or close to it) of material AI trains on was human generated, but that doesn't mean 100% of humans are generating useful material for AI training.

Let's train one on just the expert written code and books then, and not the entirety of GitHub or Stack Overflow and such, and see how it fares...

Re: Reports of code's death are greatly exaggerated

#163

Post by coldtea »

j_bum wrote: post #87
ffsm8 wrote: post #60

Earlier quoted context omitted.

i'd go one step further, they're going to turbo charge the NIH syndrome and treat every code file as a seperate "here"

For others like me who know “NIH” to be “National Institutes of Health”… “NIH” here refers to “Not Invented Here” Syndrome, or a bias against things developed externally.

Basically not wanting to use dependencies or frameworks from outside the company or team.

Re: Reports of code's death are greatly exaggerated

#164

Post by [deleted] »

coffeefirst wrote: post #138
bluGill wrote: post #103

A week ago there was an artical about Donald Knuth asking an ai to prove something then unproved and it found the proof. I suppose it is possible that the great Knuth didn't know how to find this existing truth - but there is a reason we all doubted it (including me when I mentioned it there) i have never written a c compiler yet I would bet money if you paid me to write one (it would take a few years at least) it wo…

So I would like to know how it found the proof. Because it’s much more likely to have been plucked from an obscure record where the author didn’t realize this was special than to have been estimated on the fly. This makes LLMs incredibly powerful research tools, which can create the illusion of emergent capabilities.

[deleted]

Re: Reports of code's death are greatly exaggerated

#165

Post by coldtea »

kstrauser wrote: post #19
pacman128 wrote: post #16

In a chat bot coding world, how do we ever progress to new technologies? The AI has been trained on numerous people's previous work. If there is no prior art, for say a new language or framework, the AI models will struggle. How will the vast amounts of new training data they require ever be generated if there is not a critical mass of developers?

That’s factually untrue. I’m using models to work on frameworks with nearly zero preexisting examples to train on, doing things no one’s ever done with them, and I know this because I ecosystem around these young frameworks. Models can RTFM (and code) and do novel things, demonstrably so.

>I’m using models to work on frameworks with nearly zero preexisting examples to train on

Zero preexisting examples of your particular frameworks.

Huge number of examples of similar existing frameworks and code patterns in their training set though.

Still not a novel thing in any meaningful way, not any more than someone who has coded in dozens of established web frameworks, can write against an unfamiliar to them framework homegrown at his new employer.

Re: Reports of code's death are greatly exaggerated

#166

Post by cactusplant7374 »

bigstrat2003 wrote: post #111
idopmstuff wrote: post #27

Earlier quoted context omitted.

Yeah, I don't really accept the argument that AI makes mistakes and therefore cannot be trusted to write production code (in general, at least - obviously depends on the types of mistakes, which code, etc.). The reality is we have built complex organizational structures around the fact that humans also make mistakes, and there's no real reason you can't use the same structures for AI. You have someone write the code,…

Humans also make mistakes, but unlike LLMs, they are capable of learning from their mistake and will not repeat it once they have learned. That , not the capacity to make mistakes, is why you should not allow LLMs to do things.

Developers repeat the same mistakes all the time. Otherwise off by one wouldn’t be a thing.

Re: Reports of code's death are greatly exaggerated

#167

Post by runarberg »

conception wrote: post #159
lateforwork wrote: post #71

Chris Lattner, inventor of the Swift programming language recently took a look at a compiler entirely written by Claude AI. Lattner found nothing innovative in the code generated by AI [1]. And this is why humans will be needed to advance the state of the art. AI tends to accept conventional wisdom. Because of this, it struggles with genuine critical thinking and cannot independently advance the state of the art. AI…

So the problem with Chris’ take is “This one for fun project didn’t produce anything particularly interesting.” So outside of the fact that we have magic now that can just produce “conventional “ compilers. Take it to a Moore’s Law situation. Start 1000 create a compiler projects- have each have a temperature to try new things, experiment, mutate. Collate - find new findings - reiterate- another 1000 runs with some o…

Moors law states that the number of transistors in an integrated circuit doubles about every two years. It has nothing to say about the capabilities of statistical models.

In fact in statistics we have another law which states that as you increase parameters the more you risk overfitting. And overfitting seems to already be a major problem with state of the art LLM models. When you start overfitting you are pretty much just re-creating stuff which is already in the dataset.

Re: Reports of code's death are greatly exaggerated

#168

Post by legulere »

fasterik wrote: post #107
thesz wrote: post #91

Earlier quoted context omitted.

> ...generate answers near the center of existing thought. This is right in the Wikipedia's article on universal approximation theorem [1]. [1] https://en.wikipedia.org/wiki/Universal_approximation_theore... "n the field of machine learning, the universal approximation theorems (UATs) state that neural networks with a certain structure can, in principle, approximate any continuous function to any desired degree of ac…

It has been proven that recurrent neural networks are Turing complete [0]. So for every computable function, there is a neural network that computes it. That doesn't say anything about size or efficiency, but in principle this allows neural networks to simulate a wide range of intelligent and creative behavior, including the kind of extrapolation you're talking about. [0] https://www.sciencedirect.com/science/article…

I think you cannot take the step from any turing machine being representable as a neural network to say anything about the prowess of learned neural networks instead of specifically crafted ones.

I think a good example are calculations or counting letters: it's trivial to write turing machines doing that correctly, so you could create neural networks, that do just that. From LLM we know that they are bad at those tasks.

Re: Reports of code's death are greatly exaggerated

#169

Post by coldtea »

adamiscool8 wrote: post #52
derrak wrote: post #47

Earlier quoted context omitted.

Maybe you’re right about modern LLMs. But you seem to be making an unstated assumption: “there is something special about humans that allow them to create new things and computers don’t have this thing.” Maybe you can’t teach current LLM backed systems new tricks. But do we have reason to believe that no AI system can synthesize novel technologies. What reason do you have to believe humans are special in this regard?

After thousands of years of research we still don’t fully understand how humans do it, so what reason (besides a sort of naked techno-optimism) is there to believe we will ever be able to replicate the behavior in machines?

Well, understanding how it works is not a prerequisite to being able to do it.

People have been doing thigs millenia before they understood them. Did primitive people understood the mechanism behind which certain medicinal plants worked in the body, or just saw that when they e.g. boil them and consume them they have a certain effect?

Re: Reports of code's death are greatly exaggerated

#170

Post by _pdp_ »

bitwize wrote: post #151
_pdp_ wrote: post #129

Remember Deep Thought, the greatest computer ever built that spent 7.5 million years computing the Answer to the Ultimate Question of Life, the Universe, and Everything? The answer was 42, perfectly correct, utterly useless because nobody understood the question they were asking. That's what happens when you hand everything to a machine without understanding the problem yourself. AI can give you correct answers all d…

Well, yes, but AI can also give you wildly incorrect answers with alarming frequency. I know, I know, "skill issue"/"you're holding it wrong". And maybe that's vacuously true, in that it's so hard to guess what will produce correct output, because LLMs are not an abstraction layer in the way that we're used to. Prior abstraction layers related input to output via a transparent homomorphism: the output produced for an…

You are correct.

One minor note. The skill issue isn't about failing to prompt it correctly, but rather failing to understand what it actually does.

There's an entire crop of professionals who believe we can Harry Potter our way out of any situation with the right magic words.

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