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Differences between AI and Regular Computing
Yes, AI might be overhyped. Yes, a lot of algorithmic software (regular computing software) claims to be AI when it's not. But I don't think the AI paradigm is being fully understood yet. If you're interested, I found this concise article which summarizes the differences between AI and regular computing:
https://www.rigb.org/explore-science/explore/blog/whats-difference-between-ai-and-regular-computing
Comments
When people say “AI” they are referring to LLMs and machine learning systems. There is no such thing as AGI today.
@Neum, agreed there isn't any Artificial General Intelligence (AGI) today. The article is just summarizing the differences between AI and regular computing software (traditional or classical computing that uses algorithms to perform specific tasks).
the confusion comes from the term AI, the term has been used so often incorrectly that nowadays we have to now say 'general AI/ AGI' which doesn't exist yet and may never exist.
Fwiw, most people in AI use (and have for half a century ) AI to mean a whole family of program methodologies almost none of which are related to AGI… few people in the field think of AI as meaning primarily AGI.
So, it isn’t wrong to refer to things as AI that aren’t AGI.
1997
According to Ben Goertzel, the first person that probably used the term "artificial general intelligence" (in an article related to artificial intelligence) was Mark Avrum Gubrud in the 1997 article Nanotechnology and International Security.
My point was meaning that we started to use AGI because of the confusion that people think AI is AGI
I understand what you want to say and that article, but AI is everything about computing and algorithms.
Well I guess it depends on what you mean by AGI. Is there a specific meaning, well understood meaning for that?
The fact remains that whatever "intelligence" an LLMs like ChatGPT has, it is certainly "generalized".
Previous approaches to artificial intelligence focused on one thing and had no intelligence other than regarding that specific narrow thing. E.g., back in the 1980's IBM's Deep Blue was the first chess-playing AI software that could beat a human chess grandmaster. It could do only one thing: play chess. "Deep Blue's victory is considered a milestone in the history of artificial intelligence." https://en.wikipedia.org/wiki/Deep_Blue_(chess_computer)
ChatGPT can play chess, sort of, according to who you talk to. However, it's nowhere near as good as Deep Blue was 40 years ago. But ChatGPT can also do many other things: write a story, solve a math problem, help write and debug programming language code, help plan a trip, answer questions about nearly any topic. It's not necessarily good at all these things, but the intelligence it has is generalized, can be applied to many different subject matters, many different situations.
From Wikipedia entry on History of Artificial Intelligence:
https://en.wikipedia.org/wiki/History_of_artificial_intelligence#AI_Era,artificial_general_intelligence(2020%E2%80%93present)
@Danny_Mammy : my point is that it isn’t confusion. As computer science developed, it was clear that there was a family of techniques and approaches that made sense for computer scientists to call AI and had nothing to do with AGI…so at some point it made sense to develop the vocabulary. Even in the 70’s , there were computer scientists calling things AI which weren’t related to what people now call AGI.
I will chip in to this thread when a suitably annoying comment that for some reason I think is funny occurs to me. I sense it percolating just below the surface but coaxing it out has so far eluded me.
The farce is strong within you.
“I will chip in” ✅
“annoying comment” ✅
“is funny” ✅
“coaxing it out” ✅
You’re done! 😅
Agree, the statement satisfied itself recursively.