The report comes from StatCounter, which suggests Bing remains the second-most popular search engine with a 6.89 percent market share, while Yahoo, DuckDuckGo, Yandex, and AOL languish...
I’m curious what you use it for, because I try to use it daily for IT related queries and it gets less than half of what I ask correct. I basically have to fact check almost everything it tells me which kind of defeats the purpose. It does shine when I need really abstract instructions though, the other day I asked it how to get into a PERC controller on some old server and Google had nothing helpful, and ChatGPT laid out the instructions to get in there and rebuild a disk perfectly. So while it has some usefulness I generally can’t really trust it fully.
But generally you can’t (shouldn’t) trust web search results fully either. At the end of the day, the onus is on you as the user to do your due diligence.
I’ve seen ChatGPT give me wrong information, and sometimes it would be bad to execute the code or command it generated it, but I know enough to say “are you sure thats correct?”. Hell, you can just challenge it each time or open a new session and ask it “what does this code do: insert-code-it generated here”.
You shouldn’t just paste a search result command from stack overflow into your terminal either. And at least with chatgpt you can ask it to explain the command or code in detail and it will walk you through what each step does.
Also, pasting that command from stack over flow into chatgpt and adding your specific context around it is HUGE. Thats why I say they are different products/use cases but they work well in concert. They just dont work well combined together like bing and google have been doing.
edit: I guess lemmy escapes certain characters and it ate my post.
The point you have to remember is that it is trained on bulk data out there in a very inefficient manner, it needs to see thousands of examples in order to start getting any sort of understanding of something. If you ask it “how do I do {common task} in {popular language}” you will generally get excellent results, but the further you stray from that the more likely to be error prone it is.
Still it is often good to get you looking on the right track when you are unsure to start, and is fantastic for learning a new language. I’ve been using it extensively in learning C# where I know what I want to code but not exactly how to use existing features to do it.
I’m curious what you use it for, because I try to use it daily for IT related queries and it gets less than half of what I ask correct. I basically have to fact check almost everything it tells me which kind of defeats the purpose. It does shine when I need really abstract instructions though, the other day I asked it how to get into a PERC controller on some old server and Google had nothing helpful, and ChatGPT laid out the instructions to get in there and rebuild a disk perfectly. So while it has some usefulness I generally can’t really trust it fully.
But generally you can’t (shouldn’t) trust web search results fully either. At the end of the day, the onus is on you as the user to do your due diligence.
I’ve seen ChatGPT give me wrong information, and sometimes it would be bad to execute the code or command it generated it, but I know enough to say “are you sure thats correct?”. Hell, you can just challenge it each time or open a new session and ask it “what does this code do: insert-code-it generated here”.
You shouldn’t just paste a search result command from stack overflow into your terminal either. And at least with chatgpt you can ask it to explain the command or code in detail and it will walk you through what each step does.
Also, pasting that command from stack over flow into chatgpt and adding your specific context around it is HUGE. Thats why I say they are different products/use cases but they work well in concert. They just dont work well combined together like bing and google have been doing.
edit: I guess lemmy escapes certain characters and it ate my post.
The point you have to remember is that it is trained on bulk data out there in a very inefficient manner, it needs to see thousands of examples in order to start getting any sort of understanding of something. If you ask it “how do I do {common task} in {popular language}” you will generally get excellent results, but the further you stray from that the more likely to be error prone it is.
Still it is often good to get you looking on the right track when you are unsure to start, and is fantastic for learning a new language. I’ve been using it extensively in learning C# where I know what I want to code but not exactly how to use existing features to do it.