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Watching the Generative AI Hype Bubble Deflate
(ash.harvard.edu)
This is a most excellent place for technology news and articles.
"It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, 'that's not thinking'"
-Pamela McCorduck
"AI is whatever hasn't been done yet."
- Larry Tesler
That's the curse of the AI Effect.
Nothing will ever be "an actual AI" until we cross the barrier to an actual human-like general artificial intelligence like Cortana from Halo, and even then people will claim it isn't actually intelligent.
Well at least until those who study intelligence and self-awareness actually come up with a comprehensive definition for it. Something we don't even have currently. Which makes the situation even more silly. The people selling LLMs and AGNs as artificial intelligence are the PT Barnum of the modern era. This way to the egress folks come see the magnificent egress!
They already did. AGI - artificial general intelligence.
The thing is, AGI and AI are different things. Like your "LLMs aren't real AI" thing , large language models are a type of machine learning model, and machine learning is a field of study in artificial intelligence.
LLMs are AI. Search engines are AI. Recommendation algorithms are AI. Siri, Alexa, self driving cars, Midjourney, Elevenlabs, every single video game with computer players, they are all AI. Because the term "Artificial Intelligence" by itself is extremely loose, and includes the types of narrow AI all of those are.
Which then get hit by the AI Effect, and become "just another thing computers can do now", and therefore, "not AI".
That just Compares it to human level intelligence. Something which we cannot currently even quantify. Let alone understand. It's ultimately a comparison, a simile not a scientific definition.
Search engines have always been databases. With interfaces programmed by humans. Not ai. They've never suddenly gained new functionality inexplicably. If there's a new feature someone programmed it.
Search engines are however becoming llms and are getting worse for it. Unless you think eating rocks and glue is particularly intelligent. Because there is no comprehension there. It's simply trying to make its output match patterns it recognizes. Which is a precursor step. But is not "intelligence". Unless a program doing what it's programed to do is artificial intelligence. Which is such a meaningless measure because that would mean notepad is artificial intelligence. Windows is artificial intelligence. Linux is artificial intelligence.
You can argue what you think the words should mean in your opinion in the field of artificial intelligence. I agree with some of them.
It just doesn't change what they actually do mean.
You can't just throw out random Wikipedia links. For example, the Article on AGI explicitly says we don't have a definition of what human level cognition actually is. Which is what the person you were replying to was saying. You're doing a fallacious appeal to authority, except that the authority doesn't agree with you.
That's a disturbing handwave. "We don't really know what intelligence is, so therefore, anything we call intelligence is fair game"
A thermometer tells me what temperature it is. It senses the ambient heat energy and responds with a numeric indicator. Is that intelligence?
My microwave stops when it notices steam from my popcorn bag. Is that intelligence?
If I open an encyclopedia book to a page about computers, it tells me a bunch of information about computers. Is that intelligence?
If AI helps us realize that a thermometer fits the definition of Intelligence when it shouldn’t, then it’s entirely valid to refine the definition
I mean, I think intelligence requires the ability to integrate new information into one's knowledge base. LLMs can't do that, they have to be trained on a fixed corpus.
Also, LLMs have a pretty shit-tastic track record of being able to differentiate correct data from bullshit, which is a pretty essential facet of intelligence IMO
LLMs have a perfect track record of doing exactly what they were designed to, take an input and create a plausible output that looks like it was written by a human. They just completely lack the part in the middle that properly understands what it gets as the input and makes sure the output is factually correct, because if it did have that then it wouldn't be an LLM any more, it would be an AGI.
The "artificial" in AI does also stand for the meaning of "fake" - something that looks and feels like it is intelligent, but actually isn't.
Sometimes it seems like the biggest success of AI has been refining the definition of intelligence. But we still have a long way to go