DiscoverDeep PapersSwarm: OpenAI's Experimental Approach to Multi-Agent Systems
Swarm: OpenAI's Experimental Approach to Multi-Agent Systems

Swarm: OpenAI's Experimental Approach to Multi-Agent Systems

Update: 2024-10-29
Share

Description

As multi-agent systems grow in importance for fields ranging from customer support to autonomous decision-making, OpenAI has introduced Swarm, an experimental framework that simplifies the process of building and managing these systems. Swarm, a lightweight Python library, is designed for educational purposes, stripping away complex abstractions to reveal the foundational concepts of multi-agent architectures. In this podcast, we explore Swarm’s design, its practical applications, and how it stacks up against other frameworks. Whether you’re new to multi-agent systems or looking to deepen your understanding, Swarm offers a straightforward, hands-on way to get started.

Learn more about AI observability and evaluation in our course, join the Arize AI Slack community or get the latest on LinkedIn and X.

Comments 
In Channel
KV Cache Explained

KV Cache Explained

2024-10-2404:19

loading
00:00
00:00
x

0.5x

0.8x

1.0x

1.25x

1.5x

2.0x

3.0x

Sleep Timer

Off

End of Episode

5 Minutes

10 Minutes

15 Minutes

30 Minutes

45 Minutes

60 Minutes

120 Minutes

Swarm: OpenAI's Experimental Approach to Multi-Agent Systems

Swarm: OpenAI's Experimental Approach to Multi-Agent Systems

Arize AI