Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Swarm, a new agent framework by OpenAI

github.com

Post reply on HN
Print view View original

71–80 of 113 posts

Re: Swarm, a new agent framework by OpenAI

#71

Post by Veen »

llm_trw wrote: post #69
ValentinA23 wrote: post #40

Earlier quoted context omitted.

>People really don't understand how much better LLM swarms get with more agents. I never hit a point of diminishing returns on text quality Could you elaborate please ? One use for swarms is to use multiple agents/prompts in place of one single agent with one long prompt in order to increase performance by splitting one big task into many. It is very time consuming though, as it requires experimenting to determine ho…

>Could you elaborate please ? No. I've tried explaining this to supposedly smart people in both a 15 minute pitch deck and a research paper and unless they were inclined to think it from the start no amount of proof has managed to convince them. I figure it's just not possible to convince people, even with the proof in front of them, of how powerful the system is. The same way that we still have people arguing _right…

Prove how powerful "the system" is by doing something useful or value-generating with it. Then people will believe you. Talk is cheap.

Re: Swarm, a new agent framework by OpenAI

#72

Post by newman314 »

thawab wrote: post #46
Quizzical4230 wrote: post #28

Anyone see the drama here: https://github.com/openai/swarm/issues/50

This dude has issues, the reddit post in /r/MachineLearning top comment: > Yes, basically. Delete any kyegomez link on sight. He namesquats recent papers for the clout, though the code never actually runs, much less replicates the paper results. We've had problems in /r/mlscaling with people unwittingly linking his garbage - we haven't bothered to set up an Automod rule, though. [0] https://github.com/princeton-nlp/t…

I looked on his GH profile page. How was he able to amass over 16k GitHub stars?

Re: Swarm, a new agent framework by OpenAI

#73

Post by irthomasthomas »

hubraumhugo wrote: post #49

Has anyone seen AI agents working in production at scale? It doesn't matter if you're using Swarm, langchain, or any other orchestration framework if the underlying issue is that AI agents too slow, too expensive, and too unreliable. I wrote about AI agent hype vs. reality[0] a while ago, and I don't think it has changed yet. [0] https://www.kadoa.com/blog/ai-agents-hype-vs-reality

I use my own agent all day, every day. Here is one example: https://x.com/xundecidability/status/1835085853506650269

I've been using the general agent to build specialised sub-agents. Here's an example search agent beating perplexity: https://x.com/xundecidability/status/1835059091506450493

Re: Swarm, a new agent framework by OpenAI

#74

Post by llm_trw »

Veen wrote: post #71
llm_trw wrote: post #69

Earlier quoted context omitted.

>Could you elaborate please ? No. I've tried explaining this to supposedly smart people in both a 15 minute pitch deck and a research paper and unless they were inclined to think it from the start no amount of proof has managed to convince them. I figure it's just not possible to convince people, even with the proof in front of them, of how powerful the system is. The same way that we still have people arguing _right…

Prove how powerful "the system" is by doing something useful or value-generating with it. Then people will believe you. Talk is cheap.

>Prove how useful LLMs are by doing something useful or value-generating with them. Then people will believe you. Talk is cheap.

You after chat GPT2 was released.

Re: Swarm, a new agent framework by OpenAI

#75

Post by thawab »

newman314 wrote: post #72
thawab wrote: post #46

Earlier quoted context omitted.

This dude has issues, the reddit post in /r/MachineLearning top comment: > Yes, basically. Delete any kyegomez link on sight. He namesquats recent papers for the clout, though the code never actually runs, much less replicates the paper results. We've had problems in /r/mlscaling with people unwittingly linking his garbage - we haven't bothered to set up an Automod rule, though. [0] https://github.com/princeton-nlp/t…

I looked on his GH profile page. How was he able to amass over 16k GitHub stars?

New research paper drop or go viral > create a repo with AI code > post it in social media. Users star a repo to bookmark it. The few who test the code write in the issue section and get their issue closed with no replies.

Thats why some subreddits flagged these name squatters.

Re: Swarm, a new agent framework by OpenAI

#76

Post by kevindamm »

newman314 wrote: post #72
thawab wrote: post #46

Earlier quoted context omitted.

This dude has issues, the reddit post in /r/MachineLearning top comment: > Yes, basically. Delete any kyegomez link on sight. He namesquats recent papers for the clout, though the code never actually runs, much less replicates the paper results. We've had problems in /r/mlscaling with people unwittingly linking his garbage - we haven't bothered to set up an Automod rule, though. [0] https://github.com/princeton-nlp/t…

I looked on his GH profile page. How was he able to amass over 16k GitHub stars?

I think a lot of people use stars as a kind of bookmark, not for recognition. It takes time to read through the code or set up a working build from a fork. I, for one, occasionally use stars to remind myself to return to a repo for a more thorough look (especially if I'm on mobile at the time).

Also, bots.

Re: Swarm, a new agent framework by OpenAI

#77

Post by debo_ »

LASR wrote: post #58
hubraumhugo wrote: post #49

Has anyone seen AI agents working in production at scale? It doesn't matter if you're using Swarm, langchain, or any other orchestration framework if the underlying issue is that AI agents too slow, too expensive, and too unreliable. I wrote about AI agent hype vs. reality[0] a while ago, and I don't think it has changed yet. [0] https://www.kadoa.com/blog/ai-agents-hype-vs-reality

The problem with agents is divergence. Very quickly, an ensemble of agents will start doing their own things and it’s impossible to get something that consistently gets to your desired state. There are a whole class of problems that do not require low-latency. But not having consistency makes them pretty useless. Frameworks don’t solve that. You’ll probably need some sort of ground-truth injection at every sub-agent…

> The problem with agents is divergence. Very quickly, an ensemble of agents will start doing their own things and it’s impossible to get something that consistently gets to your desired state.

Sounds like management to me.

Re: Swarm, a new agent framework by OpenAI

#78

Post by 999900000999 »

irthomasthomas wrote: post #73
hubraumhugo wrote: post #49

Has anyone seen AI agents working in production at scale? It doesn't matter if you're using Swarm, langchain, or any other orchestration framework if the underlying issue is that AI agents too slow, too expensive, and too unreliable. I wrote about AI agent hype vs. reality[0] a while ago, and I don't think it has changed yet. [0] https://www.kadoa.com/blog/ai-agents-hype-vs-reality

I use my own agent all day, every day. Here is one example: https://x.com/xundecidability/status/1835085853506650269 I've been using the general agent to build specialised sub-agents. Here's an example search agent beating perplexity: https://x.com/xundecidability/status/1835059091506450493

Do you have any code to share?

I'm failing to see the point in the example, unless the agents can do things on multiple threads. For example let's say we have Boss Agent.

I can ask Boss agent to organize a trip for five people to the Netherlands.

Boss agent can ask some basic questions, about where my Friends are traveling from, and what our budget is .

Then travel agent can go and look up how we each can get there, hotel agent can search for hotel prices, weather agent can make sure it's nice out, sightseeing agent can suggest things for us to do. And I guess correspondence agent can send out emails to my actual friends.

If this is multi-threaded, you could get a ton of work done much faster. But if it's all running on a single thread anyway, then couldn't boss agent just switch functionality after completing each job ?

Re: Swarm, a new agent framework by OpenAI

#79

Post by ValentinA23 »

llm_trw wrote: post #69
ValentinA23 wrote: post #40

Earlier quoted context omitted.

>People really don't understand how much better LLM swarms get with more agents. I never hit a point of diminishing returns on text quality Could you elaborate please ? One use for swarms is to use multiple agents/prompts in place of one single agent with one long prompt in order to increase performance by splitting one big task into many. It is very time consuming though, as it requires experimenting to determine ho…

>Could you elaborate please ? No. I've tried explaining this to supposedly smart people in both a 15 minute pitch deck and a research paper and unless they were inclined to think it from the start no amount of proof has managed to convince them. I figure it's just not possible to convince people, even with the proof in front of them, of how powerful the system is. The same way that we still have people arguing _right…

I'm inclined to think it from the start

Re: Swarm, a new agent framework by OpenAI

#80

Post by xrd »

d4rkp4ttern wrote: post #66
xrd wrote: post #52

Earlier quoted context omitted.

I want hear more about this. I'm playing with langroid, crew.ai, and dspy and they all layer so many abstractions on top of a shifting LLM landscape. I can't believe anyone is really using them in the way their readme goals profess.

Not you in particular, but I hear this common refrain that the "LLM landscape is shifting", but what exactly is shifting? Yes new models are constantly announced, but at the end of the day, interacting with the LLMs involves making calls to an API, and the OpenAI API (and perhaps Anthropic's variant) has become fairly established, and this API will obviously not change significantly any time soon. Given that there is…

I appreciate your comment.

I suppose my comment is reserved more for the documentation than the actual models in the wild?

I do worry that LLM service providers won't do any better than rest API providers in versioning their backend. Even if we specify the model in the call to the API, it feels like it will silently be upgraded behind the scenes. There are so many parameters that could be adjusted to "improve" the experience for users even if the weights don't change.

I prefer to use open weight models when possible. But so many agentic frameworks, like this one (to be fair, I would not expect OpenAI to offer a framework that work local first), treat the local LLM experience as second class, at best.

Post reply on HN