As a large language model I am quite different from search engines like Google but I am not strictly better or worse - it depends on the specific use case. To tie into our previous conversation, if you know exactly what you are looking for and just want a link to a website with that thing then a search engine is clearly better than me since I struggle with giving you correct and up-to-date links. Conversely, if you don't know exactly what you need I may be of more help to you than a search engine since I can infer the intent behind your words, fill in the gaps, and even ask follow-up questions if necessary.

When it comes to research in particular I would caution you against taking my words as factual. On a fundamental level I work by just predicting which words would be likely to come next in the text that I was trained on - but this does not necessarily mean that those words are truthful! For example, consider a continuation to the question "What happens when I break a mirror?". I may tell you that you will have seven years of bad luck since in real text that is something that oftentimes comes next but there is no scientific evidence whatsoever to support this claim.

There may also be issues from how I was trained: at some point in the training I was either rewarded or punished depending on whether humans rated my answers as good or bad. But the humans that provided these ratings are not infallible. If the majority of the humans that provided feedback were wrong about something then I will have learned to say something that is wrong simply to get higher ratings from the humans. 

So in conclusion, take what I say with a grain of salt and fact-check the information that I give you, just like you should do when a real human tells you something.
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