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> I'm honestly baffled that people lack the ability to use LLMs in a productive and optimal manner. Huge +1. I’ve got it to do a large part of my work for me
by LASR 3y ago
> I'm honestly baffled that people lack the ability to use LLMs in a productive and optimal manner.
Huge +1.
I’ve got it to do a large part of my work for me by chaining some simple API calls.
The fundamental conceptual gap I see - people often ask it to do some “thinking”. Then are annoyed by the inaccurate output.
A simple example is doing word count and it getting the wrong answer very confidently.
Of course it sucks at that. It doesn’t have a counter internally. But if you ask it to number each word in the input and output a list, then ask for the word count, it gets it right every time.
Almost like how a human might count words manually.
- therein 3y agoI agree. I often use it as if it is a code generator with a decent grasp of human language. Here is what I asked it to do the other day, and it just did it right away and got it entirely right. > Write async tokio Rust code that takes in a Vec<u8>, writes it to a temporary file, calls /usr/bin/svc infer pathToTemporaryFile, reads and deletes temporaryFile+".out" and returns Result<Vec<u8>> containing the contents of temporaryFile+".out" I knew what I wanted, I could have written it myself, there was no unknown but it took fewer keystrokes and honestly when asked to write small components like this with pedantic detail, it does an incredible job and the output is easy to validate quickly.
- karmakaze 3y agoIf this is a good example of using ChatGPT for writing Rust, I suspect that the problem may be with Rust async.
- seba_dos1 3y agoIf "chaining some simple API calls" is "a large part of your work", I can see it being incredibly useful. I already used it in this way a few times and it saved me some time indeed. However, as a software developer I feel like it's actually a tiny minority of my work; most of it is "doing some thinking" and slowly unfolding the inner parts of systems in order to understand how they work and how to fix them or make them do what I want, for which GPT is at best useful as a rubber duck to speak to.
- Frost1x 3y agoActually this is the aspect I love about GPT. The less I have to spend dealing with idiosyncrasies of arbitrary API boiler plate and can get down to the business of leveraging said things together or designing aspects of said things to achieve a new goal, the better. As someone who is far from an expert in DevOps, this has saved me a lot of time recently, and it worked fairly well to get past duct taping infrastructure together to then leverage.
- seba_dos1 3y ago> The less I have to spend dealing with idiosyncrasies of arbitrary API boiler plate In my experience, GPT saves me some time when I don't really have to think about idiosyncrasies anyway. In cases where I do have to think about them, GPT doesn't offload that from me. It often tries to mash unrelated frameworks together or makes up non-existing APIs that it would find useful for the given task. When it does work well, it mostly boils down to automated series of copy'n'pastes. Saves a bit of time, sure, but doesn't really transform the way I work.
- sangnoir 3y agoWho knew the next "billion dollar security mistake" after C's memory handling would be LLM-suggested misconfigurations? I bet someone will try to sell an LLM-based service to fix thr bugs caused by other code-generating LLMs.
- simonw 3y agoIt's a pretty amazing rubber duck. I used it to brainstorm approaches to tracking changes to a database table using SQLite and ended up building an entirely new library: - Article: https://simonwillison.net/2023/Apr/15/sqlite-history/ https://simonwillison.net/2023/Apr/15/sqlite-history/ - ChatGPT transcript: https://gist.github.com/simonw/1aa4050f3f7d92b048ae414a40cddbd5 https://gist.github.com/simonw/1aa4050f3f7d92b048ae414a40cdd...