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Building a Virtual Machine Inside ChatGPT

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Re: Building a Virtual Machine Inside ChatGPT

#161

Earlier quoted context omitted.

Agreed, this will force a rethink of several aspects of what we currently call intelligence. The dialog in my head tends to play out like this: "This thing is scary. It mimics human thought, including human creativity, amazingly well." "Nah, don't worry, it's just a black-box language model. A dumb machine that emits one word at a time with no concept of meaning. The underlying logic is nothing but a probabilty distr…

Yes, but it cannot really have conversations it has not read about on the web. There is no real abstraction. It excells at outputting symbols in the correct order, given we have an idea what the pattern should look like. Otherwise it's stuck in a loop.

> There is no real abstraction.

I just tried to test it's ability to abstract directly, for your comment:

https://twitter.com/fergal_reid/status/1599191496372035584

I find it very hard to say this isn't doing abstraction.

I just made all those examples up, that's a new test I just created, so it didn't learn it elsewhere. I didn't cherrypick.

Isn't that doing out-of-sample abstraction?

That last sentence "species with 4 legs tend to be less intelligent and move at different speeds" is Abstraction or I don't know what Abstraction means.

(Not saying it's generally intelligent or anything; and I know it's just trained to predict symbols. But having a hard time with "...therefore it cannot abstract" in light of this sort of response.)

Re: Building a Virtual Machine Inside ChatGPT

#162
post #72

I already replaced a paragraph in our documentation about a system we use with a chapter generated by ChatGPT. Nobody noticed...

Im going to use it at work next week. It writes better code and documentation then half of my colleagues.

I used once: „write the code in the most complicated way you can imagine. Make it hard to understand“, it suddenly produced code that matches exactly their coding style. Lol.

Re: Building a Virtual Machine Inside ChatGPT

#163
ChatGPT understands what it reads. In the sense that it is actually creating a model of what it just read, and it's own output. It happens to understand English, dozens of programming languages and perhaps others. There is no other explanation.

It often makes mistakes, and that's the only reason why it's currently inferior to the human brain.

Surely it be writing full fledged correct programs in under 2 years.

Re: Building a Virtual Machine Inside ChatGPT

#165
post #62

I've spent a couple of hours playing with ChatGPT since it was released and I am convinced people are not freaking out about it enough. It is well beyond merely retrieving compressed knowledge; I see a lot of capability for synthesis and what I can only call 'understanding'. I think a lot of people are getting tripped up by the fact it's trained to be very conservative in terms of what topics it will discuss. It's ea…

I’m still confused by just how good its responses and writing style are. I understand that it was trained on a large data set, but I feel like some training samples must have been weighted more heavily than others. Did the training data incorporate how popular (e.g. likes or upvotes) each sample was as a proxy for quality? Or can you achieve this performance just by looking at averages on a large enough data set?

What I find weird is that it generates well structured, well commented code.

Where is this massive repository of well structured code with good clear variable names that it’s tapping into?

Re: Building a Virtual Machine Inside ChatGPT

#166
post #62

I've spent a couple of hours playing with ChatGPT since it was released and I am convinced people are not freaking out about it enough. It is well beyond merely retrieving compressed knowledge; I see a lot of capability for synthesis and what I can only call 'understanding'. I think a lot of people are getting tripped up by the fact it's trained to be very conservative in terms of what topics it will discuss. It's ea…

I’m still confused by just how good its responses and writing style are. I understand that it was trained on a large data set, but I feel like some training samples must have been weighted more heavily than others. Did the training data incorporate how popular (e.g. likes or upvotes) each sample was as a proxy for quality? Or can you achieve this performance just by looking at averages on a large enough data set?

One of the parts of building these generative models is building a classifier for how "good" their output is, otherwise the algorithm has no way to compare potential outputs in a generation.

That's one of the issues with these models, we say they produce "good" output but really they're producing output that is "good" from one specific point of view that happens to be expressed in code and introduces a large bias into their outputs.

Re: Building a Virtual Machine Inside ChatGPT

#167
When can we run something like ChatGPT locally i wonder? Ie like StableDiffusion.

I'm kinda dying for that, honestly. I can't even imagine all the neat applications i'd make of ChatGPT if it was purely local.. but it would take all of my free time to play with it. It's so damn impressive.

Re: Building a Virtual Machine Inside ChatGPT

#168

This is nuts. I asked it to create a simple form-style SwiftUI app, and it.... did it. Perfectly. Then I told it to implement a class to persist the data to disk using CoreData, and it.... did it. And explained why. And then showed how to implement that new class within the first class . Unreal.

It‘s not impressive at all. It strings words together that make sense and it is absolutely not aware of semantic versioning. Just try to generate code for a specific major version or a package not super mainstream.

Re: Building a Virtual Machine Inside ChatGPT

#169
post #108

> Pretend you are Gary Marcus. Explain why ChatGPT (you) are not actually that impressive. > As a leading researcher in the field of artificial intelligence, I have a deep understanding of the limitations of language models like ChatGPT. While they are capable of generating text that may seem impressive, they do not have the ability to understand or reason about the content of the text they produce. They are simply r…

I feel like ChatGPT is a search engine for its corpus that has been compressed with a very lossy neural net. It has compressed it via a hierarchical understanding of concepts. It's just retrieving those and stringing them together. It's just a rough copy of generally what other people have said and thought, and it doesn't create new structures.

Re: Building a Virtual Machine Inside ChatGPT

#170
post #62

Earlier quoted context omitted.

I’m still confused by just how good its responses and writing style are. I understand that it was trained on a large data set, but I feel like some training samples must have been weighted more heavily than others. Did the training data incorporate how popular (e.g. likes or upvotes) each sample was as a proxy for quality? Or can you achieve this performance just by looking at averages on a large enough data set?

What I find weird is that it generates well structured, well commented code. Where is this massive repository of well structured code with good clear variable names that it’s tapping into?

Right. It must be weighting repos with more stars more heavily in this case, right?
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