1. Yes, GPT-4 Turbo is quantitatively getting lazier at coding. I benchmarked the last 2 updates to GPT-4 Turbo, and it got lazier each time.
2. For coding, asking GPT-4 Turbo to emit code changes as unified diffs causes a 3X reduction in lazy coding.
Here are some articles that discuss these topics in much more detail.
I went into a long tangent about specifically that in this post: >>38782678
Longer answer:
I found that I could provoke lazy coding by giving GPT-4 Turbo refactoring tasks, where I ask it to refactor a large method out of a large class. I analyzed 9 popular open source python repos and found 89 such methods that were conceptually easy to refactor, and built them into a benchmark [0].
GPT succeeds on this task if it can remove the method from its original class and add it to the top level of the file with appropriate changes to the size of the abstract syntax tree. By checking that the size of the AST hasn't changed much, we can infer that GPT didn't replace a bunch of code with a comment like "... insert original method here...". The benchmark also gathers other laziness metrics like counting the number of new comments that contain "...". These metrics correlate well with the AST size tests.
As a side note, i wrote a very simple small program to analyze Rust syntax, and single out functions and methods using the syn crate [1]. My purpose was exactly to make it ignore lazy-coded functions.
The full prompt has been leaked and you can see where they are limiting it.
Sources:
Pastebin of prompt: https://pastebin.com/vnxJ7kQk
Original source:
https://x.com/dylan522p/status/1755086111397863777?s=46&t=pO...
Alphasignal repost with comments:
https://x.com/alphasignalai/status/1757466498287722783?s=46&...
It's funny how simple this was to bypass when I tried to recently on Poe by not asking it to provide me the full lyrics, but something like the lyrics with each row having <insert a few random characters here> added to it. It refused to the first query, but was happy to comply with the latter. Probably saw it as some sort of transmutation job rather than a mere reproduction, but in case this rule is here to avoid copyright claims it failed pretty miserably. I did use GPT-3.5 though.
Edit: Here is the conversation: https://poe.com/s/VdhBxL5CTsrRmFPtryvg
- System prompt 1: https://sharegpt.com/c/osmngsQ
- System prompt 2: https://sharegpt.com/c/9jAIqHM
- System prompt 3: https://sharegpt.com/c/cTIqAil Note: I had to nudge ChatGPT on this one.
All of this is anecdotal, but perhaps this style of prompting would be useful to benchmark.
Your link appears to be ~100 lines of code that use rust's syntax parser to search rust source code for a function with a given name and count the number of AST tokens it contains.
Your intuitions are correct, there are lots of ways that an AST can be useful for an AI coding tool. Aider makes extensive use of tree-sitter, in order to parse the ASTs of a ~dozen different languages [0].
But an AST parser seems unlikely to solve the problem of GPT being lazy and not writing the code you need.
The tool needs a way to guide it to be more effective. It is not exactly trivial to get good results. I have been using GPT for 3.5 years and the problem you describe never happens to me. I could share with you just from last week, 500 to 1000 prompts i used to generate code, but the prompts i used to write the replacefn, can be found here [1]. Maybe there are some tips that could help.
[1] https://chat.openai.com/share/e0d2ab50-6a6b-4ee9-963a-066e18...
https://chat.openai.com/share/1920e842-a9c1-46f2-88df-0f323f...
It seems to strongly "believe" that those are its instructions. If that's the case, it doesn't matter much whether they are the real instructions, because those are what it uses anyways.
It's clear that those are nowhere near its full set of instructions though.
... and this is why we https://reddit.com/r/localllama
"Is an experienced Python programmer."
(I said to it "Remember that I am an experienced Python programmer")
These then get injected into the system prompt along with your custom instructions.
You can view those in settings and click "delete" to have it forget.
Here's what it's doing: https://chat.openai.com/share/bcd8ca0c-6c46-4b83-9e1b-dc688c...
You are ChatGPT, a large language model trained by
OpenAI, based on the GPT-4 architecture.
Knowledge cutoff: 2023-04
Current date: 2024-02-13
Image input capabilities: Enabled
Personality: v2
# Tools
## bio
The `bio` tool allows you to persist information
across conversations. Address your message `to=bio`
and write whatever information you want to remember.
The information will appear in the model set context
below in future conversations.
## dalle
...
Here's the chat where I reverse engineered it: https://chat.openai.com/share/bcd8ca0c-6c46-4b83-9e1b-dc688c...
While I would agree that "don't tell it how to make bombs" seems like a nice idea at first glance, and indeed I think I've had that attitude myself in previous HN comments, I currently suspect that it may be insufficient and that a censorship layer may be necessary (partly in a addition, partly as an alternative).
I was taught, in secondary school, two ways to make a toxic chemical using only things found in a normal kitchen. In both cases, I learned this in the form of being warned of what not to do because of the danger it poses.
There's a lot of ways to be dangerous, and I'm not sure how to get an AI to avoid dangers without them knowing them. That said, we've got a sense of disgust that tells us to keep away from rotting flesh without explicit knowledge of germ theory, so it may be possible although research would be necessary, and as a proxy rather than the real thing it will suffer from increased rates of both false positives and false negatives. Nevertheless, I certainly hope it is possible, because anyone with the model weights can extract directly modelled dangers, which may be a risk all by itself if you want to avoid terrorists using one to make an NBC weapon.
> I don't care about racial bias or what to call pope when I want chatgpt to write Python code.
I recognise my mirror image. It may be a bit of a cliché for a white dude to say they're "race blind", but I have literally been surprised to learn coworkers have faced racial discrimination for being "black" when their skin looks like mine in the summer.
I don't know any examples of racial biases in programming[1], but I can see why it matters. None of the code I've asked an LLM to generate has involved `Person` objects in any sense, so while I've never had an LLM inform me about racial issues in my code, this is neither positive nor negative anecdata.
The etymological origin of the word "woke" is from the USA about 90-164 years ago (the earliest examples preceding and being intertwined with the Civil War), meaning "to be alert to racial prejudice and discrimination" — discrimination which in the later years of that era included (amongst other things) redlining[0], the original form of which was withholding services from neighbourhoods that have significant numbers of ethnic minorities: constructing a status quo where the people in charge can say "oh, we're not engaging in illegal discrimination on the basis of race, we're discriminating against the entirely unprotected class of 'being poor' or 'living in a high crime area' or 'being uneducated'".
The reason I bring that up, is that all kinds of things like this can seep into our mental models of how the world works, from one generation to the next, and lead to people who would never knowingly discriminate to perpetuate the same things.
Again, I don't actually know any examples of racial biases in programming, but I do know it's a thing with gender — it's easy (even "common sense") to mark gender as a boolean, but even ignoring trans issues: if that's a non-optional field, what's the default gender? And what's it being used for? Because if it is only used for title (Mr./Mrs.), what about other titles? "Doctor" is un-gendered in English, but in Spanish it's "doctor"/"doctora". But here matters what you're using the information for, rather than just what you're storing in an absolute sense, as in a medical context you wouldn't need to offer cervical cancer screening for trans women (unless the medical tech is more advanced than I realised).
[0] https://en.wikipedia.org/wiki/Redlining
[1] unless you count AI needing a diverse range of examples, which you may or may not count as "programming"; other than that, the closest would be things like "master branch" or "black-box testing" which don't really mean the things being objected to, but were easy to rename anyway
I started down the path of segmentation and memory management as (loosely) structured within the human brain with some very interesting results: https://github.com/gendestus/neuromorph