6 ms·

Or just not bother. It sounds pretty useless if it flunks on basic tasks like this. Perhaps you’ve been sold a lie?

ivape 1y ago
Well, you see it hallucinates on long precise strings, but if we ignore that, and focus on what it’s powerful at, we can do something powerful. In this case, by the time it gets to outputting the url, it already determined the correct intent or next action (print out a url). You use this intent to do a tool call to generate a url. Small aside, it’s ability to figure what and why is pure magic, for those still peddling the glorified autocomplete narrative. You have to be able to see what this thing can actually do, as opposed to what it can’t.
- sebtron 1y ago
  > Well, you see it hallucinates on long precise strings But all code is "long precise strings".
  - ogogmad 1y ago
    He obviously means random unstructured strings, which code is usually not.
- grey-area 1y ago
  I can’t even tell if you’re being sarcastic about a terrible tool or are hyping up LLMs as intelligent assistants and telling me we’re all holding it wrong.
IanCal 1y ago
They're moderately unreliable text copying machines if you need exact copying of long arbitrary strings. If that's what you want, don't use LLMs. I don't think they were ever really sold as that, and we have better tools for that. On the other hand, I've had them easily build useful code, answer questions and debug issues complex enough to escape good engineers for at least several hours. Depends what you want. They're also bad (for computers) at complex arithmetic off the bat, but then again we have calculators.
- goalieca 1y ago
  > I don't think they were ever really sold as that, and we have better tools for that. We have OpenAI calling gpt5 as having PhD level of intelligence and others like Anthropoc saying it will write all our code within months. Some are claiming it’s already writing 70%. I say they are being sold as a magical do everything tool.
  - buildbot 1y ago
    Would you hire a PhD to copy URLs by hand? Would them having PhD make it less likely they’d make a mistake than an high school student doing the same?
    - goalieca 1y ago
      Grad students and even post docs often do a lot of this manual labour for data entry and formatting. Been there, done that.
      - IanCal 1y ago
        Manual data entry has lots of errors. All good workflows around this base themselves on this fact.
    - parineum 1y ago
      A high school student would use copy/paste and the urls would be perfect duplicates..
      - IanCal 1y ago
        > A high school student would use copy/paste and the urls would be perfect duplicates.. Did the LLM have this?
      - baq 1y ago
        LLMs aren’t high school students, they’re blobs of numbers which happen to speak English if you poke them right. Use the tool when it’s good at what it does.
seanw265 1y ago
I suspect you haven't tried a modern mid-to-large-LLM & Agent pair for writing code. They're quite capable, even if not suited for all tasks.
baq 1y ago
Read about the jagged frontier. IanCal is right: this is a perfect example of using the tool wrong; you’ve focused on a very narrow use case which is surprisingly hard for the matmuls to not mess up and extrapolate, but extrapolation is incorrect here because the capability frontier is fractal and not continuous.
- grey-area 1y ago
  It’s not surprisingly hard at all, when you consider they have no understanding of the tasks they do nor of the subject material. It’s just a good example of the types of tasks (anything requiring reliability or correct results) that they are fundamentally unsuited to. Sadly it seems the best use-case for LLMs at this point is bamboozling humans.
  - baq 1y ago
    When you take a step back it's surprising that these tools can be actually useful at all in nontrivial tasks, but being surprised doesn't matter in the grand scheme of things. Bamboozling rarely enough for harnesses to keep them in line and ability to inference-time self-correct when bamboozling is detected either by the model itself or by the harness is very useful at least in my work. It's a question of using the tool correctly and understanding its limitations, which is hard if you aren't willing to explore the boundaries and commit to doing it every month basically.

Well, you see it hallucinates on long precise strings, but if we ignore that, and focus on what it’s powerful at, we can do something powerful. In this case, by the time it gets to outputting the url, it already determined the correct intent or next action (print out a url). You use this intent to do a tool call to generate a url. Small aside, it’s ability to figure what and why is pure magic, for those still peddling the glorified autocomplete narrative. You have to be able to see what this thing can actually do, as opposed to what it can’t.

sebtron 1y ago
> Well, you see it hallucinates on long precise strings But all code is "long precise strings".
- ogogmad 1y ago
  He obviously means random unstructured strings, which code is usually not.
grey-area 1y ago
I can’t even tell if you’re being sarcastic about a terrible tool or are hyping up LLMs as intelligent assistants and telling me we’re all holding it wrong.

IanCal 1y ago

They're moderately unreliable text copying machines if you need exact copying of long arbitrary strings. If that's what you want, don't use LLMs. I don't think they were ever really sold as that, and we have better tools for that. On the other hand, I've had them easily build useful code, answer questions and debug issues complex enough to escape good engineers for at least several hours. Depends what you want. They're also bad (for computers) at complex arithmetic off the bat, but then again we have calculators.

goalieca 1y ago
> I don't think they were ever really sold as that, and we have better tools for that. We have OpenAI calling gpt5 as having PhD level of intelligence and others like Anthropoc saying it will write all our code within months. Some are claiming it’s already writing 70%. I say they are being sold as a magical do everything tool.
- buildbot 1y ago
  Would you hire a PhD to copy URLs by hand? Would them having PhD make it less likely they’d make a mistake than an high school student doing the same?
  - goalieca 1y ago
    Grad students and even post docs often do a lot of this manual labour for data entry and formatting. Been there, done that.
    - IanCal 1y ago
      Manual data entry has lots of errors. All good workflows around this base themselves on this fact.
  - parineum 1y ago
    A high school student would use copy/paste and the urls would be perfect duplicates..
    - IanCal 1y ago
      > A high school student would use copy/paste and the urls would be perfect duplicates.. Did the LLM have this?
    - baq 1y ago
      LLMs aren’t high school students, they’re blobs of numbers which happen to speak English if you poke them right. Use the tool when it’s good at what it does.

seanw265 1y ago

I suspect you haven't tried a modern mid-to-large-LLM & Agent pair for writing code. They're quite capable, even if not suited for all tasks.

baq 1y ago

Read about the jagged frontier. IanCal is right: this is a perfect example of using the tool wrong; you’ve focused on a very narrow use case which is surprisingly hard for the matmuls to not mess up and extrapolate, but extrapolation is incorrect here because the capability frontier is fractal and not continuous.

grey-area 1y ago
It’s not surprisingly hard at all, when you consider they have no understanding of the tasks they do nor of the subject material. It’s just a good example of the types of tasks (anything requiring reliability or correct results) that they are fundamentally unsuited to. Sadly it seems the best use-case for LLMs at this point is bamboozling humans.
- baq 1y ago
  When you take a step back it's surprising that these tools can be actually useful at all in nontrivial tasks, but being surprised doesn't matter in the grand scheme of things. Bamboozling rarely enough for harnesses to keep them in line and ability to inference-time self-correct when bamboozling is detected either by the model itself or by the harness is very useful at least in my work. It's a question of using the tool correctly and understanding its limitations, which is hard if you aren't willing to explore the boundaries and commit to doing it every month basically.