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Whenever someone brings up "AI", I tell them AI is not real AI. Machine learning is a more apt buzzword. And real AI is probably like fusion. Its always 10 years away.
I took an AI class in 2001. We learned all sorts of algorithms classified as AI. Including various ML techniques. Under which included perceptrons.
Whenever someone brings up "AI", I tell them AI is not real AI. Machine learning is a more apt buzzword. And real AI is probably like fusion. Its always 10 years away.
Machine learning as a descriptive phrase has stopped being relevant. It implies the discovery of information in a training set. The pre-training of an LLM is most definitely machine learning. But what people are excited and interested in is the use of this learned data in generative AI. “Machine learning” doesn’t capture that aspect.
Are researchers scared to just come out and say it because they'll be labeled as wrong if the extreme tail case happens?
If you’re correct, there’s not much reward aside from the “I told you so” bragging rights, if you’re wrong though - boy oh boy, you’ll be deemed unworthy.
You only need to get one extreme prediction right (stock market collapse, AI taking over, etc ), then you’ll be seen as “the guru”, the expert, the one who saw it coming. You’ll be rewarded by being invited to boards, panels and government councils to share your wisdom, and be handsomely paid to explain, in hindsight, why it was obvious to you, and express how baffling it was that no one else could see what you saw.
On the other hand, if predict an extreme case and you get it wrong, there’s virtually 0 penalties, no one will hold that against you, and no one even remembers.
So yeah, fame and fortune is in taking many shots at predicting disasters, not the other way around.
Whenever someone brings up "AI", I tell them AI is not real AI. Machine learning is a more apt buzzword. And real AI is probably like fusion. Its always 10 years away.
AI is an overloaded term. I took an AI class in 2001. We learned all sorts of algorithms classified as AI. Including various ML techniques. Under which included perceptrons.
Earlier quoted context omitted.
Machine learning as a descriptive phrase has stopped being relevant. It implies the discovery of information in a training set. The pre-training of an LLM is most definitely machine learning. But what people are excited and interested in is the use of this learned data in generative AI. “Machine learning” doesn’t capture that aspect.
It's a valid term that is worth introducing to the layperson IMO. Let them know how the magic works, and how it doesn't.
Are researchers scared to just come out and say it because they'll be labeled as wrong if the extreme tail case happens?
Whenever someone brings up "AI", I tell them AI is not real AI. Machine learning is a more apt buzzword. And real AI is probably like fusion. Its always 10 years away.
> Whenever someone brings up "AI", I tell them AI is not real AI. You and also everyone since the beginning of AI. https://quoteinvestigator.com/2024/06/20/not-ai/
The common thread between those who take things as "AI is anything that doesn't work yet" and "what we have is still not yet AI" is "this current technology could probably have used a less distracting marketing name choice, where we talk about what it delivers rather than what it's supposed to be delivering".
AI has now been revealed to the masses. When AGI arrives most people will barely notice. It will just feel like slightly better LLMs to them. They will have already cemented notions of how it works and how it affects their lives.