Comment by thepasswordis
4 years ago
I mean not to veer to far into the philosophical side of this, but what does it actually mean to know or understand something?
Did you see the demo the other day that was posted here of using stylographic analysis to identify alt accounts? Most of the comments were some form of "holy shit this is unbelievable", and the OP explained that he had used a very simple type of analysis to generate the matches.
We aren't quite as unique as we think was my takeaway from that. My takeawy from this, as well as the SD, DALL-E stuff is that we're all just basically taking what we heard from the past, modifying it a teeny bit, and spitting it back out.
Ok, sure.
…but people are getting the mistaken impression that this is an actual system, running actual commands.
I can also emulate a docker container. I’ll just write down the commands you send me and respond with some believable crap.
…but no one is going to run their web server on me, because that’s stupid. I can respond hundreds of times a second and maintain the internal state required for that.
Neither can this model.
It’s good, and interesting, but it’s not running code, it’s predicting sentences and when you’re running software it was to be accurate, fast, consistent and have a large internal data state.
Trying to run docker in gpt is fun. Trying to use docker in gpt to do work is stupid.
It’s never going to work as well as actually running docker.
It’s just for fun.
Models that write code and the execute that code will be in every way superior to models that try to memorise the cli api of applications.
It’s an almost pointless use of the technology.
Gpt may have “learnt” python; that’s actually interesting!
Docker is not interesting.
If I want to use the docker api, I can type `docker` on my computer and use it.
It's pretty sad that the thing that excites people the most about an amazing new language model is that it can do trivial command line actions, that you can do without the model.
Spending millions of dollars to produce a model that can do what you can already trivially do is very seriously not what openai just did.
> I can also emulate a docker container. I’ll just write down the commands you send me and respond with some believable crap.
Right. The thing that is impressive is that ChapGPT can do this effectively. This means that it has some "understanding" of how `pwd`, `ls`, `apt`, `docker`, etc all work. In some sense, this is an AI that knows how to read code like a human instead of like a machine.
> In some sense, this is an AI that knows how to read code like a human instead of like a machine.
It's literally spitting out responses like a machine. Isn't that the opposite of what you wanted?
> The thing that is impressive is that ChapGPT can do this effectively.
? What is impressive about it?
Forget this is an AI model for a moment. Lets say I give you a black box, and you can type in shell commands and get results. Sometimes the results don't make sense.
Are you impressed?
I am not impressed.
I could implement the blackbox with an actual computer running and actual shell and the results would be better. Why would I ever use a LLM for this?
It's like discovering that the large hadron collider can detect the sun. Yes, it can. Wow, that's interesting, I didn't realize it could do that. I can also look up at the sun, and see the sun. mmm... well, that was fun, but pointless.
There are so many other things GPT can do, this... it's just quite ridiculous people are so amazed by it.
It is not indicative of any of the other breakthrough functionality that's in this model.
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Give it some medium complexity code that isn't something you can find a variation of online and see if it can explain it.
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"It’s never going to work as well as actually running X. It’s just for fun." You must realize that X was also built by some kind of neural networks, i.e. humans, and the only reason we can't run an entire Linux kernel "in our heads" is mostly due to hardware, i.e. brains, limitations. Although, I do remember Brian Kernighan saying in an interview how he was able to run entire C programs "in his head" faster than the 1980s CPUs.
The point is that the future programming language will probably be the human language as an extremely high-level specification language, being able to hallucinate/invent/develop entire technological stacks (from protocols to operating systems to applications) on the fly.
Well, you don't have to convince me, I am pretty sure we are just deterministic machines, meerly responding to stimuli.
> what does it actually mean to know or understand something?
I think it means that you're able to apply the information to make predictions about the world. For example, you'll encounter something novel and be able to make accurate guesses about its behavior. Or, conversely, you will have high likelihood of inventing something novel yourself, based on the information you acquired (rather than through brute force).
do you mind linking to the demo you were talking about please? i didnt see it and it didnt come up in an algolia search