Reminds me of the story of the old engineer asked to come in and fix some machine in a factory.
The engineer inspects the machine, marks it with some chalk, then strikes the chalk mark with a hammer.
The machine works again.
The company asks for an itemised invoice after seeing the initial invoice for $10k.
To which they received:
hitting chalk mark with hammer: $1.
knowing where to place the chalk mark: $9,999
GPT suffers from garbage-in garbage-out just as much as a search engine does.
Knowing how to find search results to fix your specific situation is a skill.
Utilising GPT for such a task is equally a skill. With the added bonus of GPT randomly pulling the perfect API/Library out of its ass
on a slight tangent, I often think about this piece of writing. in general, but I’ve also started wondering what that picture’s going to look like after the tsunami of LLMs suddenly finds it’s actually made of air and not water
Yeah I feel like once people realize AI chatbots like ChatGPT are largely just search engines with AutoTldrBot built in, they’ll be better at using them. ChatGPT is great for bouncing ideas off of or rubber-ducking through a solution. But just like with StackOverflow answers, you as the developer need to be able to recognize when ChatGPT is just spouting garbage, when it’s getting you close to the answer, what adjustments you need to make to make its answers work for your situation, etc. In it’s current state, it will never just magically hand you a fully developed, robust, well-integrated, complete solution though, as much as tech CEOs want it to.
Sounds like a great solution people will be prepared to pay OpenAI $100B in the future for, and not at all like an incremental upgrade over StackOverflow with extra ecocide added.
Yeah after rereading my comment it’s not super clear, but I’m not trying to endorse ChatGPT/OpenAI. I agree that AI is a pretty terrible solution for the use case of “search engine with a built in AutoTldrBot”, because of all the reasons you mention. I was just trying to point out that it’s being marketed as a replacement for actual software developers, and that’s very very very far from reality at the moment.
GPT and the whole AI bs we have at the moment excels at being convincing. It’s even prepared to back up what it says.
The problem is, that all of that is generated. Not necessarily fact.
It will generate API methods, entire libraries, sources, legal cases, and science publications.
And it will be absolutely convincing as it presents and backs up those claims.
For example, GPT gives some API function of some library that magically solves your issue. Maybe you aren’t hugely familiar with the library, but you don’t trust GPT - so you research this made up API method and find the actual way to do it. Except you have GPT saying this exists and it works the way you want it to. So you research more, dig deeper.
Eventually you end up reading the source code, have a deeper understanding of the API in general and how to actually find useful answers (IE how to search query for it), and end up using the method you found while trying to find the mythical perfect API method.
I mean, I guess that’s a win? You learned some documentation, you solved the problem… Who cares?
Maybe I’m just bitter because that was how I first tried any of the new AI things. And I wasted 2-3 hours instead of actually solving the fucking problem by consulting the facts.
Reminds me of the story of the old engineer asked to come in and fix some machine in a factory.
GPT suffers from garbage-in garbage-out just as much as a search engine does.
Knowing how to find search results to fix your specific situation is a skill.
Utilising GPT for such a task is equally a skill. With the added bonus of GPT randomly pulling the perfect API/Library out of its ass
on a slight tangent, I often think about this piece of writing. in general, but I’ve also started wondering what that picture’s going to look like after the tsunami of LLMs suddenly finds it’s actually made of air and not water
Yeah I feel like once people realize AI chatbots like ChatGPT are largely just search engines with AutoTldrBot built in, they’ll be better at using them. ChatGPT is great for bouncing ideas off of or rubber-ducking through a solution. But just like with StackOverflow answers, you as the developer need to be able to recognize when ChatGPT is just spouting garbage, when it’s getting you close to the answer, what adjustments you need to make to make its answers work for your situation, etc. In it’s current state, it will never just magically hand you a fully developed, robust, well-integrated, complete solution though, as much as tech CEOs want it to.
Sounds like a great solution people will be prepared to pay OpenAI $100B in the future for, and not at all like an incremental upgrade over StackOverflow with extra ecocide added.
Yeah after rereading my comment it’s not super clear, but I’m not trying to endorse ChatGPT/OpenAI. I agree that AI is a pretty terrible solution for the use case of “search engine with a built in AutoTldrBot”, because of all the reasons you mention. I was just trying to point out that it’s being marketed as a replacement for actual software developers, and that’s very very very far from reality at the moment.
easy: all the time
GPT and the whole AI bs we have at the moment excels at being convincing. It’s even prepared to back up what it says.
The problem is, that all of that is generated. Not necessarily fact.
It will generate API methods, entire libraries, sources, legal cases, and science publications.
And it will be absolutely convincing as it presents and backs up those claims.
For example, GPT gives some API function of some library that magically solves your issue. Maybe you aren’t hugely familiar with the library, but you don’t trust GPT - so you research this made up API method and find the actual way to do it. Except you have GPT saying this exists and it works the way you want it to. So you research more, dig deeper.
Eventually you end up reading the source code, have a deeper understanding of the API in general and how to actually find useful answers (IE how to search query for it), and end up using the method you found while trying to find the mythical perfect API method.
I mean, I guess that’s a win? You learned some documentation, you solved the problem… Who cares?
Maybe I’m just bitter because that was how I first tried any of the new AI things. And I wasted 2-3 hours instead of actually solving the fucking problem by consulting the facts.