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Using ChatGPT to generate a GPT project end-to-end

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Re: Using ChatGPT to generate a GPT project end-to-end

#71

Post by ChatGTP »

smokel wrote: post #37
amelius wrote: post #24

Is anyone letting an LLM code and run its code by itself, then iteratively fix any bugs in it without human intervention until it e.g. passes some black box tests? Would it be possible to significantly improve an LLM using such unsupervised sessions?

You might be interested in Auto-GPT: https://agpt.co/ , an attempt at an autonomous AI based on GPT. It does not feed back information into GPT, so the LLM is not improving. Such a system would require both guts (insanity?) _and_ money to pull off.

I haven’t had much experience with AGPT but all the “AGI is here” and “people use this to make money” posts on their news feed makes my “meat brain” suspicious ha.

Re: Using ChatGPT to generate a GPT project end-to-end

#72

Post by JKCalhoun »

bonzini wrote: post #69
mlboss wrote: post #67

Earlier quoted context omitted.

What does it has to do that will qualify it as artificial intelligence ? In my opinion, all the ingredients are there for artificial intelligence. Somebody just need to stitch everything up. It can understand text, reason about it, identity next steps, can write code to execute the steps, understand error messages and fix the code. That feels like AI.

Be able to say "I don't know".

(You've just excluded a few people I know.)

Re: Using ChatGPT to generate a GPT project end-to-end

#73

Post by duckmysick »

mirekrusin wrote: post #59
lionkor wrote: post #10

Earlier quoted context omitted.

Not much, hence I dont need a dedicated driver to drive my car.

Until bird shits on the camera, your kid vomits in the car, tire is punctured, somebody breaks window, police hails to stop, you're choking with peanut, there is a crash nearby or crash with your car and all other kind of edge cases.

I think the OP meant "I dont need a dedicated driver to drive my car [because I can drive it on my own]".

The process is simplified so you can do it yourself if you have the right tool, instead of relying on dedicated professionals. The process can be traveling or designing and writing an app.

I don't understand the point you're trying to make with those edge cases, especially choking with a peanut, but driving your own car is extremely popular, despite those.

Re: Using ChatGPT to generate a GPT project end-to-end

#74

Post by jimbokun »

gwoolhurme wrote: post #61
c7b wrote: post #56

The technological singularity is approaching fast. It's pretty clear that, given terminal access and an appropriate outer loop, GPT models can iteratively create new GPT models (either by writing and executing Pyhton code, or later versions trained on LLM weights may even be able to output new weights directly). If the inner workings of the loop are sufficiently obfuscated (in the code-based version), it wouldn't nec…

Could you explain in detail how that causes the singularity? I’m lost. I saw a cool tool used to make another cool tool. You saw the singularity. Where is this logic coming from? Why would terminal access which I’m fairly certain I’ve seen in autogpt, change much.

The cool tool makes another cool tool, which in turn makes another cool tool, faster and faster, until we really don't understand at all what the latest cool tool is doing. But it just keeps getting smarter/faster/more effective/whatever it's optimizing for.

That's the basic definition of "the singularity".

Re: Using ChatGPT to generate a GPT project end-to-end

#75

Post by avidphantasm »

c7b wrote: post #56

The technological singularity is approaching fast. It's pretty clear that, given terminal access and an appropriate outer loop, GPT models can iteratively create new GPT models (either by writing and executing Pyhton code, or later versions trained on LLM weights may even be able to output new weights directly). If the inner workings of the loop are sufficiently obfuscated (in the code-based version), it wouldn't nec…

Unless this singularity is able to construct for itself sensors and actuators that can refine existing knowledge and acquire new knowledge, it will forever be hamstrung by the incomplete and static knowledge of the universe that was used to train the initial model. This is where regulation is desperately needed. We must be very careful with the kinds of sensors and actuators that are integrated with these systems. Perhaps none should be allowed.

Re: Using ChatGPT to generate a GPT project end-to-end

#76

Post by [deleted] »

qumpis wrote: post #9
lionkor wrote: post #2

What value does a developer deliver when their entire process is done by an LLM? Is there no desire for a creative process?

The dev gave the initial idea to the LLM. That's the creative process. Everything after that, arguably, is just technical details in order to realize the idea. Sure, implementation requires plenty of creativity, but of different kind.

[deleted]

Re: Using ChatGPT to generate a GPT project end-to-end

#77

Post by qumpis »

jvanderbot wrote: post #22
qumpis wrote: post #9

Earlier quoted context omitted.

The dev gave the initial idea to the LLM. That's the creative process. Everything after that, arguably, is just technical details in order to realize the idea. Sure, implementation requires plenty of creativity, but of different kind.

Believe me, only a dev can get this working. Maybe in the future, LLM wizards will conjure all our technology, but at this point, having a working knowledge of all APIs from 2021 is an assistive technology, not a magical code-machine. I've used LLM to generate a lot of code recently on side projects. It's a 10x jump in productivity, but it can only reliably do 50-80% of the work, and the last tail needs editing, veri…

I hope so, speaking from the perspective of someone who wants to keep their job. But at the same time I feel it's not trivial to bring good arguments against LLMs taking over without resorting to "they can't take into account all the context and might make tiny mistakes". But maybe people can be trained to be verifiers/testers as opposed to code writers.

Re: Using ChatGPT to generate a GPT project end-to-end

#78

Post by c7b »

gwoolhurme wrote: post #61
c7b wrote: post #56

The technological singularity is approaching fast. It's pretty clear that, given terminal access and an appropriate outer loop, GPT models can iteratively create new GPT models (either by writing and executing Pyhton code, or later versions trained on LLM weights may even be able to output new weights directly). If the inner workings of the loop are sufficiently obfuscated (in the code-based version), it wouldn't nec…

Could you explain in detail how that causes the singularity? I’m lost. I saw a cool tool used to make another cool tool. You saw the singularity. Where is this logic coming from? Why would terminal access which I’m fairly certain I’ve seen in autogpt, change much.

The cycle could look something like this: LLMv1 > prompt "get me the code for a better LLM" > paste output to terminal, execute > LLMv2 > repeat.

There are lots of different singularity definitions on wikipedia, most focus on 'intelligence' (eg "an upgradable intelligent agent will eventually enter a 'runaway reaction' of self-improvement cycles, each new and more intelligent generation appearing more and more rapidly"). I think focusing on what 'intelligence' really means, or whether any model is 'truly' intelligent can be be a bit of a distraction. So I just emphasized capabilities in a rather generic sense instead.

It's clear that LLMs can compete with humans on many tasks (coding, creative writing, medical diagnosis, psychotherapy,...), and it is conceivable that they may surpass most humans on those tasks some day. If we have models that can outperform most or all humans on important professional and everyday tasks, and also produce new models that perform even better, maybe at an accelerating rate, through means that are ultimately not interpretable for us, I'd say that's pretty close to a singularity, regardless of whether they're 'truly' intelligent. Even more so if they pass a duck test (walks like a duck, quacks like a duck,...).

Re: Using ChatGPT to generate a GPT project end-to-end

#79

Post by stevenhuang »

noman-land wrote: post #63
pwillia7 wrote: post #41

Cool -- I did something similar with the goal: Imagine and simulate an instrument that doesn't exist and ended up with this -- it even created the assets or prompts for other AIs to make assets where it couldn't, including the model https://pwillia7.github.io/echosculpt3/

How is this an instrument? It looks like a rock.

It beeps with a certain tone depending where on the rock you poke it

Re: Using ChatGPT to generate a GPT project end-to-end

#80

Post by gwoolhurme »

jimbokun wrote: post #74
gwoolhurme wrote: post #61

Earlier quoted context omitted.

Could you explain in detail how that causes the singularity? I’m lost. I saw a cool tool used to make another cool tool. You saw the singularity. Where is this logic coming from? Why would terminal access which I’m fairly certain I’ve seen in autogpt, change much.

The cool tool makes another cool tool, which in turn makes another cool tool, faster and faster, until we really don't understand at all what the latest cool tool is doing. But it just keeps getting smarter/faster/more effective/whatever it's optimizing for. That's the basic definition of "the singularity".

I don’t see that in this specific case for one thing or how we are closer from before. Code generation and auto correction getting closer is very cool, the singularity needs to be spelled out for me how a tool making a tool will get us there. How does that solve all of the hurdles that go into AGI or the singularity. How does it change a large language model.
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