3 ms·

Finally. I've been saying that we need to stop focusing on a single agent getting everything right and instead layer agents for about 16 months now, but it's gr

by kromem 3y ago

Finally. I've been saying that we need to stop focusing on a single agent getting everything right and instead layer agents for about 16 months now, but it's great to have a paper to point to. It's interesting that the diminishing returns for tasks flatten out rapidly around the same size as the ideal human meeting sizes: https://www.researchgate.net/figure/18-Optimal-Meeting-Sizes-1_tbl6_3889414 https://www.researchgate.net/figure/18-Optimal-Meeting-Sizes... If this was done at more granular steps of agent quantity I'm curious just how closely it would match those numbers. I'd also really love to see the eventual follow-up where we see how much more performance can be obtained when the agents are each fine tuned towards slightly different aims. I'd expect there'd even be a performance lift from just having the agents each set at different temperature levels. Very happy to see the research community starting to step in this direction!

piloto_ciego 3y ago
This is how I think humans work. We have 5 or 8 versions of us running around in our skulls or whatever and one of them is somewhat of a supervisor.
- huffmsa 3y ago
  I personally visualize them at a table from time to time.
  - _ink_ 3y ago
    How do they look? Do they look differently?
  - infogulch 3y ago
    Do they have to collaborate to decide who gets to use the forks?
    - Terr_ 3y ago
      That sounds like a culturally bound phenomenon, shouldn't they be using chopsticks?
      - infogulch 3y ago
        Chopsticks makes sense because there's only 5 of them and they have to share the 5 chopsticks.
    - naasking 3y ago
      Of course not, you don't need forks while playing poker.
- suriya-ganesh 3y ago
  And et voila, you have the script of inside out. \s But honestly I do think this is how we operate. Depending on our state of metabolism and other psychological factors, the dominant version changes but as a whole we remain the sum total of all these versions.
  - bamboozled 3y ago
    So there is a number, let's say 42, 42 versions of us running in parallel make consciousness, reasoning and all other useful abilities appear?
    - suriya-ganesh 3y ago
      More like a number within Miller's law[1]. https://en.wikipedia.org/wiki/Miller%27s_law#:~:text=The%20observation%2C%20also%20by%20George https://en.wikipedia.org/wiki/Miller%27s_law#:~:text=The%20o...
- xnx 3y ago
  Multi Homunculus Model
  - piloto_ciego 3y ago
    I was thinking something like Julian Jayne’s Bicameral mind, but you’re always arguing with yourself lol
  - exe34 3y ago
    Sounds like dennett's multiple drafts hypothesis.
- Trasmatta 3y ago
  I think it's way more than 8 even. And it's common to have many working as supervisors, often at conflict with each other. And some act out the automatic trauma responses, as they're stuck in the past when the trauma occurred.
  - piloto_ciego 3y ago
    Right it’s like a random forest or something maybe.
  - champdebloom 3y ago
    This sounds very much like the internal family systems model: https://en.m.wikipedia.org/wiki/Internal_Family_Systems_Model https://en.m.wikipedia.org/wiki/Internal_Family_Systems_Mode...
  - gilmore606 3y ago
    minsky, 'society of mind', everything old is new again
- nickpsecurity 3y ago
  We have tons of specialized components that work together cooperatively and competitively. There’s multiple ways they connect. There also seems to be global processes that happen, like during sleep. There’s over 3,000 cell types per the BRAIN initiative. Every brain forms on it’s own taking shape like something out of a Transformers movie. God’s design is mostly nothing like man’s neural networks. It’s far superior. Brains are also what’s creating all the artificial, neural nets on top of all math, tech, and economic systems that they run on. AI’s got a lot of catching up to do.
- hackable_sand 3y ago
  Maybe. I'm sure one's consciousness corresponds with one's guiding philosophy. I don't think this supervisor model is generally applicable to people with EFD or some forms of Autism, for example.
zarathustreal 3y ago
“Each fine tuned toward slightly different aims” So…a sort of mixture of experts if you will
- kromem 3y ago
  Kind of. More like a mixture of a mixture of experts. The problem is MoE on its own isn't able to use the context as a scratch pad for differentiated CoT trees. So you have a mixture of token suggestions, but a singular chain of thought. A mixture of both is probably going to perform better than just a mixture of the former, especially given everything we know by now regarding in context learning or the degree of transmission synthetic data is carrying.
properbrew 3y ago
I couldn't agree more. You should check out LLMWare's SLIM agents (https://github.com/llmware-ai/llmware/tree/main/examples/SLIM-Agents https://github.com/llmware-ai/llmware/tree/main/examples/SLI...). It's focusing on pretty much exactly this and chaining multiple local LLMs together. A really good topic that ties in with this is the need for deterministic sampling (I may have the terminology a bit incorrect) depending on what the model is indended for. The LLMWare team did a good 2 part video on this here as well (https://www.youtube.com/watch?v=7oMTGhSKuNY https://www.youtube.com/watch?v=7oMTGhSKuNY) I think dedicated miniture LLMs are the way forward. Disclaimer - Not affiliated with them in any way, just think it's a really cool project.
- intended 3y ago
  Great videos. I have one personal niggle: I get annoyed when we end up lying to ourselves. Regarding the 101 section in video 1 - People forgot this the day LLMs came out. I felt this was too generous with the benefit of doubt. This basic point was and remains constantly argued - with “Emergence” and anthropomorphization being the heart of the opposing argument.
jondwillis 3y ago
I was working on multi-agent systems for problem solving via https://github.com/agi-merge/waggle-dance https://github.com/agi-merge/waggle-dance for months last year!
j45 3y ago
It seems funny that the researchers are studying what people are building to experiment. crewAI is one example.
swagmoney1606 3y ago
I've had a POC agent-chain thing written in haskell for about 9 months. this paper is a little different though.

by kromem 3y ago

piloto_ciego 3y ago

This is how I think humans work. We have 5 or 8 versions of us running around in our skulls or whatever and one of them is somewhat of a supervisor.

huffmsa 3y ago
I personally visualize them at a table from time to time.
- _ink_ 3y ago
  How do they look? Do they look differently?
- infogulch 3y ago
  Do they have to collaborate to decide who gets to use the forks?
  - Terr_ 3y ago
    That sounds like a culturally bound phenomenon, shouldn't they be using chopsticks?
    - infogulch 3y ago
      Chopsticks makes sense because there's only 5 of them and they have to share the 5 chopsticks.
  - naasking 3y ago
    Of course not, you don't need forks while playing poker.
suriya-ganesh 3y ago
And et voila, you have the script of inside out. \s But honestly I do think this is how we operate. Depending on our state of metabolism and other psychological factors, the dominant version changes but as a whole we remain the sum total of all these versions.
- bamboozled 3y ago
  So there is a number, let's say 42, 42 versions of us running in parallel make consciousness, reasoning and all other useful abilities appear?
  - suriya-ganesh 3y ago
    More like a number within Miller's law[1]. https://en.wikipedia.org/wiki/Miller%27s_law#:~:text=The%20observation%2C%20also%20by%20George https://en.wikipedia.org/wiki/Miller%27s_law#:~:text=The%20o...
xnx 3y ago
Multi Homunculus Model
- piloto_ciego 3y ago
  I was thinking something like Julian Jayne’s Bicameral mind, but you’re always arguing with yourself lol
- exe34 3y ago
  Sounds like dennett's multiple drafts hypothesis.
Trasmatta 3y ago
I think it's way more than 8 even. And it's common to have many working as supervisors, often at conflict with each other. And some act out the automatic trauma responses, as they're stuck in the past when the trauma occurred.
- piloto_ciego 3y ago
  Right it’s like a random forest or something maybe.
- champdebloom 3y ago
  This sounds very much like the internal family systems model: https://en.m.wikipedia.org/wiki/Internal_Family_Systems_Model https://en.m.wikipedia.org/wiki/Internal_Family_Systems_Mode...
- gilmore606 3y ago
  minsky, 'society of mind', everything old is new again
nickpsecurity 3y ago
We have tons of specialized components that work together cooperatively and competitively. There’s multiple ways they connect. There also seems to be global processes that happen, like during sleep. There’s over 3,000 cell types per the BRAIN initiative. Every brain forms on it’s own taking shape like something out of a Transformers movie. God’s design is mostly nothing like man’s neural networks. It’s far superior. Brains are also what’s creating all the artificial, neural nets on top of all math, tech, and economic systems that they run on. AI’s got a lot of catching up to do.
hackable_sand 3y ago
Maybe. I'm sure one's consciousness corresponds with one's guiding philosophy. I don't think this supervisor model is generally applicable to people with EFD or some forms of Autism, for example.

zarathustreal 3y ago

“Each fine tuned toward slightly different aims” So…a sort of mixture of experts if you will

kromem 3y ago
Kind of. More like a mixture of a mixture of experts. The problem is MoE on its own isn't able to use the context as a scratch pad for differentiated CoT trees. So you have a mixture of token suggestions, but a singular chain of thought. A mixture of both is probably going to perform better than just a mixture of the former, especially given everything we know by now regarding in context learning or the degree of transmission synthetic data is carrying.

properbrew 3y ago

I couldn't agree more. You should check out LLMWare's SLIM agents (https://github.com/llmware-ai/llmware/tree/main/examples/SLIM-Agents https://github.com/llmware-ai/llmware/tree/main/examples/SLI...). It's focusing on pretty much exactly this and chaining multiple local LLMs together. A really good topic that ties in with this is the need for deterministic sampling (I may have the terminology a bit incorrect) depending on what the model is indended for. The LLMWare team did a good 2 part video on this here as well (https://www.youtube.com/watch?v=7oMTGhSKuNY https://www.youtube.com/watch?v=7oMTGhSKuNY) I think dedicated miniture LLMs are the way forward. Disclaimer - Not affiliated with them in any way, just think it's a really cool project.

intended 3y ago
Great videos. I have one personal niggle: I get annoyed when we end up lying to ourselves. Regarding the 101 section in video 1 - People forgot this the day LLMs came out. I felt this was too generous with the benefit of doubt. This basic point was and remains constantly argued - with “Emergence” and anthropomorphization being the heart of the opposing argument.

jondwillis 3y ago

I was working on multi-agent systems for problem solving via https://github.com/agi-merge/waggle-dance https://github.com/agi-merge/waggle-dance for months last year!

j45 3y ago

It seems funny that the researchers are studying what people are building to experiment. crewAI is one example.

swagmoney1606 3y ago

I've had a POC agent-chain thing written in haskell for about 9 months. this paper is a little different though.