Introducing Swarm Node - serverless infrastructure for AI Agent Swarms 🤖
Everyone on crypto Twitter seems to agree that the next iteration of AI agents is swarms. The idea behind Agent Swarms is to use multiple agents that communicate and collaborate between them.
This way, agents from different frameworks can communicate and leverage specialization to perform better at specific tasks and use cases.
This article introduces Swarm Node (SNAI), a serverless infrastructure that allows anyone to deploy and coordinate AI agents written in Python.
This opens up new possibilities for smaller creators who cannot run agents 24/7 or lack the necessary hardware.
SNAI solves all the overheads associated with running AI agents using technical infrastructure. Anyone can run AI agents using Python scripts without worrying about infrastructure costs, as SNAI takes care of everything (scaling, resource allocation, database management).
Instead of paying for servers, users only pay for the execution time they use effectively, making SNAI more efficient than other subscription-based solutions.
The particularity of SNAI agents is that they are not separated but can “chain” together to create a Swarm.
A Swarm can be intended to divide labor across agents, each performing a specific task they specialized in - and then passing the results to the next agent.
Thanks to the REST API and Python SDK, other applications can seamlessly integrate with SNAI, and users can coordinate how their Agent Swarm behaves (e.g., when it runs and what data it uses).
This can also be done effortlessly using ChatGPT. Here’s how:
https://x.com/bakar_io/status/1873074085443334542
But that’s not it! As the SNAI framework is in its initial phase of development, users can expect new features to be added soon, including:
1. Data Storage: mini cloud database allowing agents to share selected data bits.
2. Scheduling: Run agents at a specific time.
3. Agent Library: Ready agents created by the communities. Anyone can run, customize, and improve them further.
4. Multi-language Compatibility: SNAI offers a Python client that simplifies working with our API, with plans to allow agents to be deployed in codebase written in other languages (Go, Rust, TypeScript, C#, PHP, etc.). The community is already building a TypeScript client with plans for more.
During this week only, there have been:
Over 500 builds - intended as “dependencies” of AI agents to improve execution.
Over 10000 executions - instances where an agent is started and then paused. SNAI allows users to only pay for active runtime, significantly improving the flexibility of operating agents.
To recap, SNAI:
Allows agents to run without a server
Allows developers to add agents to their codebase
Allows anyone to chain and orchestrate agent interactions
Reduces the costs of infrastructure on a pay-per-use-basis
Brings down barriers to entry for AI agent infrastructure
Great guide on how to get started:
https://x.com/MichaelWrites00/status/1872541236554608876