“(With) today’s Supreme Court decision on presidential immunity, that fundamentally changed. For all practical purposes, there are virtually no limits on what the president can do. It’s a fundamentally new principle and it’s a dangerous precedent because the power of the office will no longer be constrained by the law...
I have many conversations with people about Large Language Models like ChatGPT and Copilot. The idea that "it makes convincing sentences, but it doesn't know what it's talking about" is a difficult concept to convey or wrap your head around. Because the sentences are so convincing....
Not an ELI5, sorry. I'm an AI PhD, and I want to push back against the premises a lil bit.
Why do you assume they don't know? Like what do you mean by "know"? Are you taking about conscious subjective experience? or consistency of output? or an internal world model?
For consistency of output and internal world models, however, their is mounting evidence to suggest convergence on a shared representation of reality. Eg this paper published 2 days ago: https://arxiv.org/abs/2405.07987
The idea that these models are just stochastic parrots that only probabilisticly repeat their training data isn't correct, although it is often repeated online for some reason.
A little evidence that comes to my mind is this paper showing models can understand rare English grammatical structures even if those structures are deliberately withheld during training: https://arxiv.org/abs/2403.19827
People sometimes act like the models can only reproduce their training data, which is what I'm saying is wrong. They do generalise.
During training the models are trained to predict the next word, but after training the network is always effectively interpolating between the training examples it has memorised. But this interpolation doesn't happen in text space but in a very high dimensional abstract semantic representation space, a 'concept space'.
Now imagine that you have memorised two paragraphs that occupy two points in concept space. And then you interpolate between them. This gives you a new point, potentially unseen during training, a new concept, that is in some ways analogous to the two paragraphs you memorised, but still fundamentally different, and potentially novel.
'There Are No Kings in America': Biden Blasts Supreme Court, Issues Dire Warning After Immunity Ruling ( dailyboulder.com )
“(With) today’s Supreme Court decision on presidential immunity, that fundamentally changed. For all practical purposes, there are virtually no limits on what the president can do. It’s a fundamentally new principle and it’s a dangerous precedent because the power of the office will no longer be constrained by the law...
What is a good eli5 analogy for GenAI not "knowing" what they say?
I have many conversations with people about Large Language Models like ChatGPT and Copilot. The idea that "it makes convincing sentences, but it doesn't know what it's talking about" is a difficult concept to convey or wrap your head around. Because the sentences are so convincing....
North Korean Workers in China Riot over Unpaid Wages; 2,000 Occupy Factory, Kill Plant Manager ( japannews.yomiuri.co.jp )