Nope, just gotta know what it IS, what it ISN’T, and how to correctly write prompts for it to return data that you can use to formulate your own conclusion.
When using AI, it’s only as smart as the operator.
No you don’t understand. The word AI, which was invented to describe this kind of technology, should not be used to describe this technology. It should instead be reserved for some imaginary magical technology that may exist in the future.
There is no code for language processing, it’s just math approximating results from weights. The whole weight set-up is what’s called ‘artificial intelligence’, because nobody wrote
if prompt like 'python' return ['large snake', 'programming language', 'australian car company']
the model ‘learned’ how to mimic human speech using training, not by 1000s of software engineers adding more branches to the code.
That technique is part of ‘artificial intelligence’, when computers solve problems they were not programmed to do. The neural network learns its knowledge by the code, but the code has no idea what is going on.
Oh, is there an arcane invocation that magically imbues it with reason?
Nope, just gotta know what it IS, what it ISN’T, and how to correctly write prompts for it to return data that you can use to formulate your own conclusion.
When using AI, it’s only as smart as the operator.
Well, it’s not AI, for starters.
Keep going…
No you don’t understand. The word AI, which was invented to describe this kind of technology, should not be used to describe this technology. It should instead be reserved for some imaginary magical technology that may exist in the future.
From what I’ve seen online, most people differentiate between AI and AGI, which is cool.
So then don’t call it AI.
I thought the sarcasm in my comment was self evident 🤔
Ahh.
Can’t blame you when some people non-ironically use that argument all the time
As much as I hate to do this, it is AI, as ML is a part of Artificial Intelligence.
It isn’t AGI, some might say it may be, but they are wrong. But the model is learning.
An LLM is not capable of learning. It won’t hallucinate less with additional training input.
Just the notion of a computer having hallucinations should suggest that it’s doing more than just basic code.
It’s not ‘intelligent’, but it has ‘learned’ enough beyond standard CPU instructions.
That’s why it’s not a General AI, but it’s still an AI.
I also talk about gremlins inside CPUs, but that doesn’t mean I think there are magical critters turning a crank inside them.
It’s called a metaphor, brother.
Regardless, it’s all code that’s eventually run on a CPU, so there isn’t any step where magic is injected.
Sigh.
There is no code for language processing, it’s just math approximating results from weights. The whole weight set-up is what’s called ‘artificial intelligence’, because nobody wrote
if prompt like 'python' return ['large snake', 'programming language', 'australian car company']the model ‘learned’ how to mimic human speech using training, not by 1000s of software engineers adding more branches to the code.
That technique is part of ‘artificial intelligence’, when computers solve problems they were not programmed to do. The neural network learns its knowledge by the code, but the code has no idea what is going on.
How do you think math is implemented on a computer?