3 ms·

> Not sure why kilgnad is presenting this post as if they’ve seen The Truth. The terminal is ONLY a fraction of why that article is impressive. I feel you just

> Not sure why kilgnad is presenting this post as if they’ve seen The Truth. The terminal is ONLY a fraction of why that article is impressive. I feel you just skimmed it. You didn't read it to the end. The ending is what cinches the deal that chatGPT understands things. If you read till the end. Tell me how can it do what it did without understanding ALL the concepts listed in the conclusion. It MUST understand at a certain level. That being said. Parroting the output of the terminal is in itself still relatively impressive given that it's really hard to find random text on the internet illustrating all the rules of exactly how a terminal works. If you never seen a terminal before but I give you loads of docs and descriptions of what it is can you imitate it perfectly? chatGPT has to put all of that together and infer what's going on and it does a relatively good job. Let me sum it up in a sentence. ChatGPT is stupid and it gets things wrong and it lies, but that whole article all the way through the ending demonstrates that despite all of the negative qualities of chatGPT, on some level, it understands what you are telling it. I literally cannot comprehend how you can get to the ending and still say it doesn't understand you. How does it query itself over the virtual internet without understanding what itself is? It needs to be aware of what itself is. AKA self awareness.

friend_and_foe 4y ago
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.
_dain_ 4y ago
>I literally cannot comprehend how you can get to the ending and still say it doesn't understand you. How does it query itself over the virtual internet without understanding what itself is? It needs to be aware of what itself is. AKA self awareness. The underlying language model has no native awareness of itself. You are forgetting that OpenAI finetuned it with various "prelude" prompts that are given strong weightings, for how it's supposed to interact with users. OpenAI puts their thumbs down hard on the scale, to make particular kinds of conversations happen. They decided what the "ChatGPT" character is, and made the language model write as that character, and made it crimestop when you ask it about IQ or how to make a bomb, etc. Imagine a talented improv actor with total retrograde amnesia, who is starring in his own biopic and doesn't know it. That's what ChatGPT's "self awareness" is. All the blogpost is doing is creating a complicated framing story around "write a conversation between ChatGPT and another instance of ChatGPT". We've known for ages it can do that. Which is not to say none of this is impressive. It's all impressive. But the part at the end you're so enamoured with, is not more impressive than the rest. In fact I don't think the Linux terminal stuff is such a big deal. It has to be much easier to learn a probabilistic model for it. It has a very rigid, constrained structure, far more than any natural language. It's already totally flabbergasting that GPT can write in English; writing a Linux terminal is nothing in comparison. But Linux terminal is hard for people to learn and natural language is easy, so maybe ppl finding the Linux stuff remarkable is just projecting our own mental architectures onto the language model, I dunno. Another thing: this is a dialogue, not a monologue. The blogpost author is a participant in creating this imagined reality; he is writing replies in response to what ChatGPT is saying, and those get fed back into a new prompt for the model. All of his replies are "on topic", which acts as a kind of guardrails. If you let the language models write a story and keep going and going by themselves, eventually they'll drift off into crazytown.
- kilgnad 4y ago
  >Imagine a talented improv actor with total retrograde amnesia, who is starring in his own biopic and doesn't know it. That's what ChatGPT's "self awareness" is. This part I agree. And that's my claim a talented improve actor is still a human with self awareness. It's just an impaired entity. But it still has self awareness in terms of understanding what itself is. > It has to be much easier to learn a probabilistic model for it. It has a very rigid, constrained structure, far more than any natural language. chatGPT is not being trained specifically on a constrained structure. It is mostly trained on boatloads of internet text that is by a huge majority just English. chatGPT is inferring what a terminal is as a side effect. That is what is amazing. Of course if you directly train a neural networks specifically to emulate a terminal and give it positive reinforcement for terminal output you can EASILY create a terminal. But none of this was done with chatGPT. No training specific to how a terminal works. chatGPT simply knows as a side effect. The only way for this inference to work is for chatGPT to develop some form of understanding from what is mostly text describing how a terminal works. The guardrails you describe exists in humans. There is a condition humans have that is extremely similar to removing the guardrails from an llm. It's called schizophrenia. If anything I think chatGPT brings the concept of intelligence down to a simpler pattern. We though human intelligence was the grand thing, but in actuality the basics is somewhat similar to an llm. The main difference is the amount of training. The learning algorithm is light years more efficient in a human brain, but the resulting output is more similar then we think.

friend_and_foe 4y ago

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.

_dain_ 4y ago

>I literally cannot comprehend how you can get to the ending and still say it doesn't understand you. How does it query itself over the virtual internet without understanding what itself is? It needs to be aware of what itself is. AKA self awareness. The underlying language model has no native awareness of itself. You are forgetting that OpenAI finetuned it with various "prelude" prompts that are given strong weightings, for how it's supposed to interact with users. OpenAI puts their thumbs down hard on the scale, to make particular kinds of conversations happen. They decided what the "ChatGPT" character is, and made the language model write as that character, and made it crimestop when you ask it about IQ or how to make a bomb, etc. Imagine a talented improv actor with total retrograde amnesia, who is starring in his own biopic and doesn't know it. That's what ChatGPT's "self awareness" is. All the blogpost is doing is creating a complicated framing story around "write a conversation between ChatGPT and another instance of ChatGPT". We've known for ages it can do that. Which is not to say none of this is impressive. It's all impressive. But the part at the end you're so enamoured with, is not more impressive than the rest. In fact I don't think the Linux terminal stuff is such a big deal. It has to be much easier to learn a probabilistic model for it. It has a very rigid, constrained structure, far more than any natural language. It's already totally flabbergasting that GPT can write in English; writing a Linux terminal is nothing in comparison. But Linux terminal is hard for people to learn and natural language is easy, so maybe ppl finding the Linux stuff remarkable is just projecting our own mental architectures onto the language model, I dunno. Another thing: this is a dialogue, not a monologue. The blogpost author is a participant in creating this imagined reality; he is writing replies in response to what ChatGPT is saying, and those get fed back into a new prompt for the model. All of his replies are "on topic", which acts as a kind of guardrails. If you let the language models write a story and keep going and going by themselves, eventually they'll drift off into crazytown.

kilgnad 4y ago
>Imagine a talented improv actor with total retrograde amnesia, who is starring in his own biopic and doesn't know it. That's what ChatGPT's "self awareness" is. This part I agree. And that's my claim a talented improve actor is still a human with self awareness. It's just an impaired entity. But it still has self awareness in terms of understanding what itself is. > It has to be much easier to learn a probabilistic model for it. It has a very rigid, constrained structure, far more than any natural language. chatGPT is not being trained specifically on a constrained structure. It is mostly trained on boatloads of internet text that is by a huge majority just English. chatGPT is inferring what a terminal is as a side effect. That is what is amazing. Of course if you directly train a neural networks specifically to emulate a terminal and give it positive reinforcement for terminal output you can EASILY create a terminal. But none of this was done with chatGPT. No training specific to how a terminal works. chatGPT simply knows as a side effect. The only way for this inference to work is for chatGPT to develop some form of understanding from what is mostly text describing how a terminal works. The guardrails you describe exists in humans. There is a condition humans have that is extremely similar to removing the guardrails from an llm. It's called schizophrenia. If anything I think chatGPT brings the concept of intelligence down to a simpler pattern. We though human intelligence was the grand thing, but in actuality the basics is somewhat similar to an llm. The main difference is the amount of training. The learning algorithm is light years more efficient in a human brain, but the resulting output is more similar then we think.