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Dude, just because we aren't as impressed with the article doesn't mean we didn't read it. Maybe we aren't as impressed as you because it isn't as impressive as

Dude, just because we aren't as impressed with the article doesn't mean we didn't read it. Maybe we aren't as impressed as you because it isn't as impressive as you think it is. You're severely misunderstanding how these language models work and are made, you don't feed it docs about Linux and it learns how to render a terminal, that would be evidence of intelligence. What you do is feed it (not really it, you're building "it" remember, you feed something else that runs a process to build it) a gazillion images of a terminal with names like "Linux terminal" embedded in documents that say "open your terminal and type..." and let it scrape stack overflow with responses with the word "terminal" in them and when you give it a prompt "terminal" it ticks and crunches for a minute and shows you associated data in the model. You can't comprehend how we get to the ending and still say it doesnt understand because you don't understand how it works. Try to read and understand about neural networks, backpropagation and how language models are built a little bit and you'll see what everyone is trying to tell you.

kilgnad 4y ago
Apologies. I didn't fully read the previous post so I interpreted it incorrectly you did read it. You don't just feed it docs. You feed it the entire text of the internet. Of course. I know this. As I made a mistake about you not reading the article fully, you made the mistake about me not understanding neural nets. I understand backpropagation. I understand feed forward networks and I understand generative models and how they work in the context of large language models. Even knowing this there is a huge aspect of these things that are black boxes. You know this as someone who claims to understand neural nets. You should also know that the human brain is a neural net built differently but with the a similar component: the neuron. We don't understand what it means for a human to understand things. There is absolutely no way to definitively say that the black box portion of a generative model is doing the something similar to what a human does to "understand" things. By virtue of the fact that humans can't spell out the full algorithm behind "understanding" and the fact that neural networks are largely blackboxes as well, everything on this thread is literally just raw speculation. My speculation may not be inline with the majority but that doesn't mean anything because both parties are speculating.

kilgnad 4y ago

Apologies. I didn't fully read the previous post so I interpreted it incorrectly you did read it. You don't just feed it docs. You feed it the entire text of the internet. Of course. I know this. As I made a mistake about you not reading the article fully, you made the mistake about me not understanding neural nets. I understand backpropagation. I understand feed forward networks and I understand generative models and how they work in the context of large language models. Even knowing this there is a huge aspect of these things that are black boxes. You know this as someone who claims to understand neural nets. You should also know that the human brain is a neural net built differently but with the a similar component: the neuron. We don't understand what it means for a human to understand things. There is absolutely no way to definitively say that the black box portion of a generative model is doing the something similar to what a human does to "understand" things. By virtue of the fact that humans can't spell out the full algorithm behind "understanding" and the fact that neural networks are largely blackboxes as well, everything on this thread is literally just raw speculation. My speculation may not be inline with the majority but that doesn't mean anything because both parties are speculating.