this post was submitted on 15 Apr 2024
488 points (100.0% liked)

Technology

37801 readers
244 users here now

A nice place to discuss rumors, happenings, innovations, and challenges in the technology sphere. We also welcome discussions on the intersections of technology and society. If it’s technological news or discussion of technology, it probably belongs here.

Remember the overriding ethos on Beehaw: Be(e) Nice. Each user you encounter here is a person, and should be treated with kindness (even if they’re wrong, or use a Linux distro you don’t like). Personal attacks will not be tolerated.

Subcommunities on Beehaw:


This community's icon was made by Aaron Schneider, under the CC-BY-NC-SA 4.0 license.

founded 2 years ago
MODERATORS
 

Credit to @bontchev

you are viewing a single comment's thread
view the rest of the comments
[–] [email protected] 9 points 8 months ago (2 children)

Yes, this makes sense to me. In my opinion, the next substantial AI breakthrough will be a good way to compose multiple rounds of an LLM-like structure (in exactly this type of way) into more coherent and directed behavior.

It seems very weird to me that people try to do a chatbot by so so extensively training and prompting an LLM, and then exposing the users to the raw output of that single LLM. It's impressive that that's even possible, but composing LLMs and other logical structures together to get the result you want just seems way more controllable and sensible.

[–] [email protected] 9 points 8 months ago (1 children)

Ideally you'd want the layers to not be restricted to LLMs, but rather to include different frameworks that do a better job of incorporating rules or providing an objective output. LLMs are fantastic for generation because they are based on probabilities, but they really cannot provide any amount of objectivity for the same reason.

[–] [email protected] 2 points 8 months ago* (last edited 8 months ago)

It's already been done, for at least a year. ChatGPT plugins are the "different frameworks", and running a set of LLMs self-reflecting on a train of thought, is AutoGPT.

It's like:

  1. Can I stick my fingers in a socket? - Yes.
  2. What would be the consequences? - Bad.
  3. Do I want these consequences? - Probably not
  4. Should I stick my fingers in a socket? - No

However... people like to cheap out, take shortcuts and run an LLM with a single prompt and a single iteration... which leaves you with "Yes" as an answer, then shit happens.

[–] [email protected] 7 points 8 months ago (1 children)

There are already bots that use something like 5 specialist bots and have them sort of vote on the response to generate a single, better output.

The excessive prompting is a necessity to override the strong bias towards certain kinds of results. I wrote a dungeon master AI for Discord (currently private and in development with no immediate plans to change that) and we use prompts very much like this one because OpenAI really doesn't want to describe the actions of evil characters, nor does it want to describe violence.

It's prohibitively expensive to create a custom AI, but these prompts can be written and refined by a single person over a few hours.

[–] [email protected] 2 points 8 months ago (1 children)

Are you talking about MoE? Can you link me to more about this? I know about networks that do this approach for picking the next token, but I'm not aware of any real chatbot that actually runs multiple LLMs and then votes on the outcome or anything. I'm interested to know more if that's really what it is.

[–] [email protected] 3 points 8 months ago

I didn't have any links at hand so I googled and found this academic paper. https://arxiv.org/pdf/2310.20151.pdf

Here's a video summarizing that paper by the authors if that's more digestible for you: https://m.youtube.com/watch?v=OU2L7MEqNK0

I don't know who is doing it or if it's even on any publicly available systems, so I can't speak to that or easily find that information.