No problem for ChatGPT however which was not only able to write the code, but write it in Rust - the target language Iw as going to. Now I've just found it easier to ask ChatGPT first then go go google.
When you're asking generally about a pretty basic topic which you just happen to not be very familiar with, ChatGPT is not too dissimilar from having an expert in the field you can chat with and ask questions to. I find it to be a very effective way of querying the huge database of information that is its training dataset.
Surprisingly, the one thing it's really terrible at but which I would've expected it to be okay at, is writing config files. I sometimes ask it how to write, say, a systemd service file which does a particular thing, and it usually shows me something which looks roughly sensible but doesn't actually do what I wanted. Its nature of fancy autocomplete with no understanding really shines through in those cases. Its biggest downfall is that it has no way to recognize when it doesn't have an answer and is making stuff up.
And apparently you didn't quite notice the particular inefficiency there...
> But instead of doing that, I just asked ChatGPT the specific questions I needed the answer to.
Yeah, sure, if you want to vet hallucinations in stead of just getting the facts.
Just go directly to Wikipedia instead.
B) Your browser (most probably) has a search function.
I'm sure that recipe exists somewhere on the internet but ChatGPT gave something to me in a very succinct format with none of the usual bullshit you deal with when looking through search results. ChatGPT also thankfully did not include the usual recipe backstory.
how to create a multi line string in a bash script. I needed to encode a human-readable JSON string in a curl call and didn’t know how. Google game me crummy tutorial sites, GPT gave me instructions, and when provided with the target, did all the formatting too.
I found it also understands git well. I use git at work, but I almost never use anything beyond push/pull/commit so crazy rebases or merges and stuff I still have to search for instructions to remember them. Now GPT can just explain to me the steps for my particular case. When I googled things, I’d search for keywords and stuff based on my knowledge and piece together the steps myself.
On a counter example, I recently had an intern who botched their config on VsCode and didn’t know what settings to fix. I found it was easier to google search how to reset things than use GPT. Ymmv.
For example, today I asked ChatGPT how to write a class method in Ruby and to explain the class << self idiom. Super simple stuff, but it gives accurate answers and it's way more convenient than Google.
For this class of simple queries there's a lot of overhead to do a Google search and then try to filter out bullshit and padded results vs a super simple prompt to ChatGPT.
Geographical information about a region.
What is the name of a song I have in my mind.
Virtually anything else. I'm studying architecture and read about associations of feelings that cardinal points transmit in a house (north, south, east, west). Like, east is associated with youth because of sunrise. At first it wasn't obvious why, so I asked ChatGPT and it explained everything brilliantly to me.
It takes me an order of magnitude less time to educate myself on ChatGPT comparing to Google.
Personally — and having not tried ChatGPT for this — I don't think ChatGPT would do well with resolving the kinds of queries I consider Google "good at."
To me, the place where Google wins over Bing, DDG, etc. is when I know there must exist some page that uniquely talks about some extremely niche overlap of concepts; but I don't know any specific "natural key" keywords to refer to the that overlapped-set-of-concepts, and instead only have a "cloud of highly-correlated keywords for the individual concepts involved" to throw into the search box.
For example, if I'm trying to conjure from the aether a discussion people are having about an issue I'm facing with some buggy behavior in an API — where that buggy behavior doesn't spit out any distinctive error message to use in the search.
I could see ChatGPT being good at a limited version of this problem, where I could give it e.g. several definitions of a word (= correlated keywords), and it could tell me the word that fits those definitions.
But the full version of the problem — pointing you at (or regurgitating) the one unique conversation that most highly correlates with your keyword cloud — essentially implies an Internet-scale "language model": one where there are unique vertices for every unique URL. Which, if you think about it, is what a traditional search engine's index is: a very dumb, but very large correlational language model, where that "dumbness" is a valuable constraint meaning that queries are able to be run map-reduced across many nodes.
Is there something I'm missing here, that makes Bing+ChatGPT better at these types of queries than Google is?
Or are the advantages ChatGPT is bringing to the table here, in areas that have nothing to do with making search engines better at the things they're already "the best tool for the job" at, and instead are in solving problems that could be solved any number of other ways (e.g. querying a search assistant such as Siri/Alexa; or pulling up an encyclopedia article or textbook relevant to the subject and just reading it) such that a search engine wouldn't necessarily be the first tool you'd search for?