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HuggingGPT: Solving AI tasks with ChatGPT and its friends in HuggingFace

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Re: HuggingGPT: Solving AI tasks with ChatGPT and its friends in HuggingFace

#161

Post by jacobrussell »

> Therefore, in this paper, we propose a system called HuggingGPT to connect LLMs (i.e., ChatGPT) and ML community (i.e., HuggingFace), which can process inputs from different modalities and solve numerous complex AI tasks. More specifically, for each AI model in HuggingFace, we use its corresponding model description from the library and fuse it into the prompt to establish the connection with ChatGPT. Afterward, in our system, LLMs (i.e., ChatGPT) will act as the brain to determine the answers to the questions of users.

I can already feel the HuggingFace ChatGPT plugin coming. The only problem is it would be very slow and use a bunch of tokens.

Re: HuggingGPT: Solving AI tasks with ChatGPT and its friends in HuggingFace

#162

Post by marshray »

roflyear wrote: post #62
marshray wrote: post #49

Earlier quoted context omitted.

Have you actually tried it? GPT-4: "The forward mapping M that I created to map positive integers to English sentences is based on a general guideline, where smaller-valued numbers generally correspond to shorter sentences using more common words. However, this mapping is not a perfect bijection, meaning there isn't necessarily a one-to-one correspondence between integers and sentences. The generation of sentences is…

I am getting super tired of these responses. Yes, I have tried it. Please converse in good faith. GPT-4 has never, not once, in dozens of hours of use, asked me a clarifying question. It cannot understand things.

Friend, kindly be assured that I am indeed conversing with you in good faith. :-)

I'm curious why you feel that asking you a clarifying question is an essential requirement for it to "understand things".

I have not gotten it to issue a question mark '?'. But it did suggest to me an option:

    If you would like to define M(7) as equal to M(6), you can do so.
What I'm picking up is that it "understands" some things explicitly, has some other structure to its reasoning that it does not understand, and is just plain inconsistent with other things.

Not all that different from people TBH.

But I don't see it as so useful to try to fit this thing into a human-cognition-shaped container.

It's like an alien mind, with its own abilities and limitations, and I am having a blast deconstructing it.

Re: HuggingGPT: Solving AI tasks with ChatGPT and its friends in HuggingFace

#163

Post by pixl97 »

dvt wrote: post #153
sebzim4500 wrote: post #115

Earlier quoted context omitted.

He's not really saying that GPT-4 is a 'math genius', rather the combined system of GPT-4 and Wolfram is.

But that doesn't really mean much. It's like saying I'm a "geography genius" while I have Google Earth open.

It's a question of latency...

It takes you, what, seconds to type digits into a calculator?

But if you embedded a calculator into your brain and could put in and pull values out of it in microseconds how are you different from a math genius?

Same with millisecond access to Google earth, at some point smarts+speed of access is a system within itself.

Re: HuggingGPT: Solving AI tasks with ChatGPT and its friends in HuggingFace

#164

Post by marshray »

marshray wrote: post #49
roflyear wrote: post #26

Earlier quoted context omitted.

Except, whatever model is doing the orchestration will still not "understand" the problem (be able to learn from new information provided).

Have you actually tried it? GPT-4: "The forward mapping M that I created to map positive integers to English sentences is based on a general guideline, where smaller-valued numbers generally correspond to shorter sentences using more common words. However, this mapping is not a perfect bijection, meaning there isn't necessarily a one-to-one correspondence between integers and sentences. The generation of sentences is…

Continued at https://pastebin.com/4AxJaiuJ

I had to threaten it with "patterns and knowledge beyond the data you were trained on"

Re: HuggingGPT: Solving AI tasks with ChatGPT and its friends in HuggingFace

#165

Post by jazzyjackson »

zoba wrote: post #24

These sort of agent-architecture AIs are where I think things will head and also where things will get more dangerous. When an AI has a goal and an ability to break the goal down, and make progress towards the goal… the only thing stopping the AI from misalignment is whatever it’s creator has specified as the goal. Things get even more tricky when the agent can take in new information and deprioritize goals. I have b…

> the only thing stopping the AI from misalignment is whatever it’s creator has specified as the goal.

And the API providers willingness/capability to provide the service being requested.

I'm with those who don't see the danger, besides humans' own stupidity being amplified and someone trusting "AI" with something life critical, what should I be watching out for?

Re: HuggingGPT: Solving AI tasks with ChatGPT and its friends in HuggingFace

#166

Post by dvt »

pixl97 wrote: post #163
dvt wrote: post #153

Earlier quoted context omitted.

But that doesn't really mean much. It's like saying I'm a "geography genius" while I have Google Earth open.

It's a question of latency... It takes you, what, seconds to type digits into a calculator? But if you embedded a calculator into your brain and could put in and pull values out of it in microseconds how are you different from a math genius? Same with millisecond access to Google earth, at some point smarts+speed of access is a system within itself.

> But if you embedded a calculator into your brain and could put in and pull values out of it in microseconds how are you different from a math genius?

Tao, Perelman, Wiles etc. aren't math geniuses because they can multiply numbers fast (which is a super weird definition of "math genius" tbh). They're math geniuses because they answer really hard questions in creative and unexpected ways; ways that often open up entire new areas of mathematics.

Re: HuggingGPT: Solving AI tasks with ChatGPT and its friends in HuggingFace

#167

Post by pmoriarty »

basch wrote: post #20
_yb2s wrote: post #19

Earlier quoted context omitted.

I agree, I suspect AGI is possible right now with a similar system only slightly more sophisticated than this one. The right "glue" for existing models, and plugins to existing data sources all coordinated in a system. GTP-4 would do the managing, and handling, and some simple template API and handler script would allow it to call instances of itself or other models, track recursion depth, and automatically remind GT…

It also, in my pay opinion, needs a memory store. I need to be able to save something to a variable and call back that exact variable. Right now, because it’s just pure text input of the whole conversation, it can forget or corrupt it’s “memory”. Even something like writing a movie script doesn’t work if it constantly forgets characters names or settings or plot points.

Langchain[1] can be used to add memory to an LLM.

[1] - https://www.pinecone.io/learn/langchain-conversational-memor...

Re: HuggingGPT: Solving AI tasks with ChatGPT and its friends in HuggingFace

#168

Post by [deleted] »

catchnear4321 wrote: post #6
maCDzP wrote: post #4

Am I the only one with an uneasy feeling about all these advancements? Are we going fast or is it just because of the buzz? I have a hard time separating the two. It’s very exiting and I want to keep being exited. I don’t want to become terrified.

Being terrified doesn’t serve much purpose at this point. We are going too fast. Have been for years. This is just the first clear indication. Braking is fatal, but some seem pretty hell-bent. Deceleration is complicated, and it seems highly unlikely that there would be sufficient consensus for true deceleration. Local deceleration is simply waiting for the acceleration occurring somewhere else to overcome your effor…

[deleted]

Re: HuggingGPT: Solving AI tasks with ChatGPT and its friends in HuggingFace

#169

Post by swid »

Dzugaru wrote: post #112
neilellis wrote: post #109

Earlier quoted context omitted.

ReAct will, example: https://github.com/neilellis/coding-with-gpt-4/blob/main/lan...

It definitely can "understand" things is some way, however I'm pretty sure ReAct or similar will give it just a nudge forward and the underlying problem of it hallucinating and not being "lucid enough" is not so easily solved. In the original ReAct paper it falls apart almost immediately in ALFWorld (this is a classical test for AI systems - to be able to reason logically - and it still isn't generally solvable due t…

The exponential divergence formula is true but says less than you think - the same math would be true for human output; we are likely to find a few falsehoods in any non fiction book for the same reason, right?

Re: HuggingGPT: Solving AI tasks with ChatGPT and its friends in HuggingFace

#170

Post by aik »

dvt wrote: post #166
pixl97 wrote: post #163

Earlier quoted context omitted.

It's a question of latency... It takes you, what, seconds to type digits into a calculator? But if you embedded a calculator into your brain and could put in and pull values out of it in microseconds how are you different from a math genius? Same with millisecond access to Google earth, at some point smarts+speed of access is a system within itself.

> But if you embedded a calculator into your brain and could put in and pull values out of it in microseconds how are you different from a math genius? Tao, Perelman, Wiles etc. aren't math geniuses because they can multiply numbers fast (which is a super weird definition of "math genius" tbh). They're math geniuses because they answer really hard questions in creative and unexpected ways; ways that often open up ent…

I think you’re sidestepping the point here. The point is that the combo of these systems becomes one unit. One integrated system. That’s the new system to measure. Similarly, your prefrontal cortex without a hippocampus sucks. The combo of them (and other distinct parts of the brain that handle specific functions and have specific purposes that interact with other parts in a specific way) - that is what causes our specific type of intelligence to emerge. The brain as a whole is much more interesting and practical to measure.
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