Curiously, the prompts are not included with that “different answer.” So a different question is of course going to produce a different answer.
In terms of email, what is spam, and are there any other colloquialisms for the same thing?
In the context of email, here’s a breakdown of what spam is — and the other informal terms that have been used to describe it:
What Is Spam (in Email)?
Spam refers to:
Unsolicited, bulk email — usually promotional or malicious in nature — sent to many recipients without their consent.
Key traits:
Not requested or expected by the recipient
Often commercial or scam-related
Sent in large volumes (bulk email)
Often filtered automatically into a spam/junk folder
Examples:
Fake lottery winnings
Unwanted ads from unknown companies
Phishing emails pretending to be from banks
Colloquial and Slang Terms for Spam
Term
Meaning / Context
Spam
The standard term, from the Monty Python “SPAM” sketch (repeating, annoying, unavoidable)
Bacon
Emails you signed up for but don’t really want — e.g., promos, newsletters
Graymail
A more formal term for “bacon”; includes low-priority email that’s technically legitimate
Ham
Non-spam, good email (used in spam filter training datasets)
Junk Mail
Common synonym, especially in casual speech and in apps like Apple Mail or Outlook
Phish
A subtype of spam — fraudulent emails designed to steal information (e.g., login credentials)
Nigerian Prince
Slang for obvious scam spam (originating from famous 419 scam emails)
But of course, that was not the original question. The question was “Why is it called spam?” And OP’s simple ChatGPT answer was similar to one simple web search answer - the crowdsource repository Wikipedia. Seemed to be the right tool to look up this information!
Because the prompt didn’t matter. And it wasn’t germane to the point I was trying to make.
This question was a trivial one. And the LLM got it right. But I would not use an LLM to provide information because I can not trust the answers. My point is that since it is so easy to get different answers from a statistical word salad machine, it is rather silly to trust any answers.
And at the bottom of the Wikipedia page are non-hallucinated references to original sources.
Here is an example on this very forum, from the OP of this thread, of an answer that was wrong but assumed to be correct:
Being an astronomy nerd, I knew how to find the answer. But in the many subjects that I am not familiar with, I would have made the same mistake that @Bmosbacker did then, and trust that the answer from the LLM was correct.
Note that thread was about using an LLM for coding. Which is a good use case as one can execute the code to determine if the answer is correct (in a test environment of course).
What Is Spam (in Email)?
Colloquial and Slang Terms for Spam