Sabitlenmiş Tweet
Pedro Carrión
154 posts

Pedro Carrión
@pedroecarrion
I help you improve your critical thinking and decision-making skills for everyday life and business. Let's build a more thoughtful world.
Cuenca, Ecuador Katılım Nisan 2021
265 Takip Edilen13 Takipçiler

@realBigBrainAI He forgot LLMs can't count the number of 'r's in 'strawberry'.
English

Mathematician Terence Tao offers a counterintuitive take: AI doesn't look intelligent because our definition of intelligence was wrong all along.
He argues that the entire history of AI has followed a predictable pattern:
"The history of AI has been here's a task that only humans can do, like maybe it is read natural language or win at chess or solve a math problem, and then one by one someone finds some AI algorithm that also does that."
But every time a machine cracks one of these "uniquely human" tasks, we move the goalposts.
The solution never feels like real thinking:
"You look at how it's done and it doesn't feel like intelligence. It's, oh, it was some trick. You just cobbled together these neural networks and you ran some algorithm, and we were looking for some elusive intelligent way of thinking, and we don't see it in the tools that actually solve our goals."
Tao then flips the problem on its head.
What if the issue isn't with the machines, but with us?
"But maybe it's actually because intelligence is not what we think it is."
He points to large language models as the clearest case. What they do sounds almost embarrassingly simple:
"Large language models in particular become very successful, and a lot of what they're doing is just predicting the next token, clicking the next word in a sentence. And that doesn't sound like something which is intelligent."
To show why this feels wrong, Tao draws a comparison to how we'd judge a human doing the same thing:
"If you ask someone to improvise a speech and they have no preparation, and at every moment they're just saying the next word that comes to their mind, you don't think that this could actually work."
And yet it works for LLMs. Which forces an uncomfortable possibility:
"Maybe that's actually a lot of what humans do as well."
English
Pedro Carrión retweetledi
Pedro Carrión retweetledi
Pedro Carrión retweetledi
Pedro Carrión retweetledi


