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AI engineers claim new algorithm reduces AI power consumption by 95%

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Re: AI engineers claim new algorithm reduces AI power consumption by 95%

#141

Post by Ygg2 »

soulofmischief wrote: post #130
Ygg2 wrote: post #129

Earlier quoted context omitted.

> Didn't you just do that to an entire class of engineers Not really. He said "if you claim LLM's are next thing since sliced butter I am doubting your abilities". Which is fair. It's not really a class as much as a group. I've never been wowed over by LLMs. At best they are boilerplate enhancers. At worst they write plausibly looking bullshit that compiles but breaks everything. Give it something truly novel and/or…

> Not really. He said "if you claim LLM's are next thing since sliced butter I am doubting your abilities". Which is fair. No, OP said: > Claiming LLMs are a massive boost for coding productivity is becoming a red flag that the claimant has a tenuous grasp on the skills necessary Quotation marks are usually reserved for direct quotes, not paraphrases or straw mans. > I've never been wowed over by LLMs. Cool. I have,…

> Quotation marks are usually reserved for direct quotes,

Not on HN. Customary is to use > paragraph quotes like you did. However I will keep that in mind.

> Cool. I have, and many others have. I'm unsure why your experience justifies invalidating the experiences of others

If we're both grading a single student (LLM) in same field (programming), and you find it great and I find it disappointing, it means one of us is scoring it wrong.

I gave papers that demonstrate its failings, where is your counter-proof?

> Your and OP's lack of imagination at the capabilities of LLMs

It's not lack of imagination. It's terribleness of results. It can't consistently write good doc comments. I does not understand the code nor it's purpose, but roughly guesses the shape. Which is fine for writing something that's not as formal as code.

It can't read and understand specifications, and even generate something as simple as useful API for it. The novel part doesn't have to be that novel just something out of its learned corpus.

Like Yaml parser in Rust. Maybe Zig or something beyond it's gobbled data repo.

> Few thoughts are truly novel, most are derivative or synergistic.

Sure but you still need A mind to derive/synergize the noise of everyday environment into something novel.

It can't even do that but remix data into plausibly looking forms. A stochastic parrot. Great for DnD campaign. Shit for code.

Re: AI engineers claim new algorithm reduces AI power consumption by 95%

#142

Post by quantadev »

dotnet00 wrote: post #103
quantadev wrote: post #100

Earlier quoted context omitted.

No, I'm not imagining things. You are, however, imaging (incorrectly) that I'm not an expert with AI who's already seen superhuman performance out of LLM prompts in the vast majority of every software development question I've ever asked them, starting all the way back at GPT-3.5.

So, where are all of your world changing innovations driven by these superhuman capabilities?

You raise a great point. Maybe I should be asking the AI for more career advice or new product ideas, rather than just letting it merely solve each specific coding challenge.

Re: AI engineers claim new algorithm reduces AI power consumption by 95%

#143

Post by soulofmischief »

Ygg2 wrote: post #141
soulofmischief wrote: post #130

Earlier quoted context omitted.

> Not really. He said "if you claim LLM's are next thing since sliced butter I am doubting your abilities". Which is fair. No, OP said: > Claiming LLMs are a massive boost for coding productivity is becoming a red flag that the claimant has a tenuous grasp on the skills necessary Quotation marks are usually reserved for direct quotes, not paraphrases or straw mans. > I've never been wowed over by LLMs. Cool. I have,…

> Quotation marks are usually reserved for direct quotes, Not on HN. Customary is to use > paragraph quotes like you did. However I will keep that in mind. > Cool. I have, and many others have. I'm unsure why your experience justifies invalidating the experiences of others If we're both grading a single student (LLM) in same field (programming), and you find it great and I find it disappointing, it means one of us is…

> Not on HN. Customary is to use > paragraph quotes like you did. However I will keep that in mind.

Hacker News is not some strange place where the normal rules of discourse don't apply. I assume you are familiar with the function of quotation marks.

> If we're both grading a single student (LLM) in same field (programming), and you find it great and I find it disappointing, it means one of us is scoring it wrong.

No, it means we have different criteria and general capability for evaluating the LLM. There are plenty of standard criteria which LLMs are pitted against, and we have seen continued improvement since their inception.

> It can't consistently write good doc comments. I does not understand the code nor it's purpose, but roughly guesses the shape.

Writing good documentation is certainly a challenging task. Experience has led me to understand where current LLMs typically do and don't succeed with writing tests and documentation. Generally, the more organized and straightforward the code, the better. The smaller each module is, the higher the likelihood of a good first pass. And then you can fix deficiencies in a second, manual pass. If done right, it's generally faster than not making use of LLMs for typical workflows. Accuracy also goes down for more niche subject material. All tools have limitations, and understanding them is crucial to using them effectively.

> It can't read and understand specifications, and even generate something as simple as useful API for it.

Actually, I do this all the time and it works great. Keep practicing!

In general, the stochastic parrot argument is oft-repeated but fails to recognize the general capabilities of machine learning. We're not talking about basic Markov chains, here. There are literally academic benchmarks against which transformers have blown away all initial expectations, and they continue to incrementally improve. Getting caught up criticizing the crudeness of a new, revolutionary tool is definitely my idea of unimaginative.

Re: AI engineers claim new algorithm reduces AI power consumption by 95%

#144

Post by specialist »

williamcotton wrote: post #133
namaria wrote: post #116

Earlier quoted context omitted.

Claiming LLMs are a massive boost for coding productivity is becoming a red flag that the claimant has a tenuous grasp on the skills necessary. Yeah if you have to look up everything all the time and you can't tell the AI slop isn't very good, you can put out code quite fast.

I know plenty of fantastic engineers that use LLM tools as code assistants. I’m not sure when and why reading documentation and man pages became a sign of a lack of skill. Watch a presentation by someone like Brian Kernighan and you’ll see him joke about looking up certain compiler flags for the thousandth time! Personally I work in C, C#, F#, Java, Kotlin, Swift, R, Ruby, Python, Postgres SQL, MySQL SQL, TypeScript,…

For me, thus far, LLMs help me forage docs. I know what I want and it helps me narrow my search faster. Watching adepts like Simon Willison wield LLMs is on my to do list.

Re: AI engineers claim new algorithm reduces AI power consumption by 95%

#145

Post by fragmede »

williamcotton wrote: post #133
namaria wrote: post #116

Earlier quoted context omitted.

Claiming LLMs are a massive boost for coding productivity is becoming a red flag that the claimant has a tenuous grasp on the skills necessary. Yeah if you have to look up everything all the time and you can't tell the AI slop isn't very good, you can put out code quite fast.

I know plenty of fantastic engineers that use LLM tools as code assistants. I’m not sure when and why reading documentation and man pages became a sign of a lack of skill. Watch a presentation by someone like Brian Kernighan and you’ll see him joke about looking up certain compiler flags for the thousandth time! Personally I work in C, C#, F#, Java, Kotlin, Swift, R, Ruby, Python, Postgres SQL, MySQL SQL, TypeScript,…

Add Golang and rust and JavaScript and next.js and react to the list for me. ;) If you live and work and breathe in the same kernel, operating system, and user space, and don't end up memorizing the various bits of minutiae, I'd judge you (and me) too, but it's not the 2000's, or the 90's or even the 80's anymore, and some of us don't have the luxury, or have chosen not to, live in one small niche for our entire career. At the end of the day, the client doesn't care what language you use, or the framework, or even the code quality, as long as it works. What they don't want to pay for is overage, and taking the previous developer's work and refactoring it and rewriting it in your preferred language isn't high value work, so you pick up whatever they used and run with it. Yeah that makes me less fluent in that one particular thing, not having done the same thing for 20+ years, but that's not where I deliver value. Some people do, and that's great for them and their employers, but my expertise lies elsewhere. I got real good at MFC, back in the day, and then WX and Qt and I'm working on getting good at react and such.

Re: AI engineers claim new algorithm reduces AI power consumption by 95%

#146

Post by jimmaswell »

namaria wrote: post #116
atq2119 wrote: post #110

Earlier quoted context omitted.

> I almost forgot how much it sucks having to jump to google every other minute Even allowing for some hyperbole, your programming experience is extremely different from mine. Looking anything up outside the IDE, let alone via Google, is by far the exception for me rather than the rule. I've long suspected that this kind of difference explains a lot of the difference in how Copilot is perceived.

Claiming LLMs are a massive boost for coding productivity is becoming a red flag that the claimant has a tenuous grasp on the skills necessary. Yeah if you have to look up everything all the time and you can't tell the AI slop isn't very good, you can put out code quite fast.

At the risk of sounding like an inflated ego: I'm very good at what I do, the rest of my team frequently looks to me for guidance, my boss and boss's boss etc. have repeatedly said I'm among the most valuable people around, and I'm the one turned to in emergencies, for difficult architectural decisions, and to lead projects. I conceptually understand the ecosystem I work in very well at every layer.

What I'm not good at is memorizing API's and libraries that all use different verbs and nouns for the same thing, and other such things that are immaterial to the actual work. How do you use a mutation observer again? Hell if I remember the syntax but I know the concept, and copilot will probably spit out what I want, and I'll easily verify the output. Or how do you copy an array in JS? Or print a stack trace? Or do a node walk? You can either wade through google and stackoverflow, or copilot can tell you instantly. And I can very quickly tell if the code copilot gave me is sensible or not.

Re: AI engineers claim new algorithm reduces AI power consumption by 95%

#147

Post by giraffe_lady »

JonChesterfield wrote: post #122
giraffe_lady wrote: post #87

Earlier quoted context omitted.

"Even just in programming" the jury is still out. None of my coworkers using these are noticeably more productive than the ones who don't. Outside of programming no one gives a shit except scammers and hype chasers.

The people writing articles for journals that aggregate and approximate other sources are in mortal terror of LLMs. Likewise graphic designers and anyone working in (human language) translation. I don't fear that LLMs are going to take my job as a developer. I'm pretty sure they mark a further decrease in the quality and coherence of software, along with a rapid increase in the quantity of code out there, and that se…

They're not scared of LLMs because of anything about LLMs. It's just that everyone with power is publicly horny to delete the remaining middle class jobs and are happy to use LLMs as a justification whether it can functionally replace those workers or not. So it's not that everyone has evaluated chatgpt and cannily realized it can do their job, they're just reading the room.

Re: AI engineers claim new algorithm reduces AI power consumption by 95%

#148

Post by Ygg2 »

soulofmischief wrote: post #143
Ygg2 wrote: post #141

Earlier quoted context omitted.

> Quotation marks are usually reserved for direct quotes, Not on HN. Customary is to use > paragraph quotes like you did. However I will keep that in mind. > Cool. I have, and many others have. I'm unsure why your experience justifies invalidating the experiences of others If we're both grading a single student (LLM) in same field (programming), and you find it great and I find it disappointing, it means one of us is…

> Not on HN. Customary is to use > paragraph quotes like you did. However I will keep that in mind. Hacker News is not some strange place where the normal rules of discourse don't apply. I assume you are familiar with the function of quotation marks. > If we're both grading a single student (LLM) in same field (programming), and you find it great and I find it disappointing, it means one of us is scoring it wrong. No…

> Hacker News is not some strange place where the normal rules of discourse don't apply. I assume you are familiar with the function of quotation marks.

Language is all about context. I wasn't trying to be deceitful. And on HN I've never seen anyone using quotation marks to quote people.

> Writing good documentation is certainly a challenging task.

Doctests isn't same as writing documentation. Doctest are the simplest form of documentation. Given function named so and so write API doc + example. It could not even write example that passed syntax check.

> Actually, I do this all the time and it works great. Keep practicing!

Then you haven't given it interesting/complex enough problems.

Also this isn't about practice. It's about its capabilities.

> In general, the stochastic parrot argument is oft-repeated but fails to recognize the general capabilities of machine learning.

I gave it write YAML parser given Yaml org spec, and it wrote following struct:

   enum Yaml {
      Scalar(String),
      List(Vec>),
      Map(HashMap>),
   }
This is the stochastic parrot in action. Why? Because it tried to pass of JSON like structure as YAML.

Whatever LLM's are they aren't intelligent. Or they have attention spans of a fruit fly and can't figure out basic differences.

Re: AI engineers claim new algorithm reduces AI power consumption by 95%

#150

Post by williamcotton »

Ygg2 wrote: post #148
soulofmischief wrote: post #143

Earlier quoted context omitted.

> Not on HN. Customary is to use > paragraph quotes like you did. However I will keep that in mind. Hacker News is not some strange place where the normal rules of discourse don't apply. I assume you are familiar with the function of quotation marks. > If we're both grading a single student (LLM) in same field (programming), and you find it great and I find it disappointing, it means one of us is scoring it wrong. No…

> Hacker News is not some strange place where the normal rules of discourse don't apply. I assume you are familiar with the function of quotation marks. Language is all about context. I wasn't trying to be deceitful. And on HN I've never seen anyone using quotation marks to quote people. > Writing good documentation is certainly a challenging task. Doctests isn't same as writing documentation. Doctest are the simples…

That’s not a good prompt, my friend!
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