Should AI's Kill? OpenAI's Swarm, & The Future of AI Training

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THEWHITEBOX

TLDR;

🦟 OpenAI’s Swarm, The Future of Agents?

🐕 Amazon’s AI Shopping Assistants… & Coders

🌲 Sequoia Capital Shares Its Updated AI Vision Again

👑 The King of Small Models is Back

🫣 Should AI’s Kill?

[TREND OF THE WEEK] Intellect-1, The Future of AI Training?

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OpenAI’s Swarms, The Future of Agents?

OpenAI has released a GitHub repository based on an insider piece published a few days ago. The idea is to streamline the creation of multi-agent scenarios where humans manage a handful of agents collaborating with each other autonomously.

They mention that it’s not meant for production, but let’s not forget that OpenAI is expected to release agent products in 2025. The idea is worth explaining because it provides insight into OpenAI’s plans and the risk it could represent to the future of many start-ups in the AI dev space.

Particularly, with Swarms, OpenAI introduces the ideas of routines and handoffs.

A routine is a guide the agent has to follow, written in natural language, for instance, on a customer support ticket (questions for context, refunds, escalation to humans, etc.). Of course, this routine would ideally be managed by one single agent, but they tend to make mistakes for long routines.

Therefore, OpenAI uses handoffs, giving agents the power to delegate tasks to more specialized agents. To do so, they propose using agent transfers as tools that an agent can call.

Tool calling is a fundamental part of AI agents. I dive deep into the idea here.

For instance, a ‘refund agent’ may be in charge of executing the refund function, but may also need to return the conversation to the context agent to finalize the interaction. Thus, the refund agent has another tool called ‘transfer_to_finalize’, which, in reality, is an instance of another agent that receives the context and continues the interaction. The link at the top shows a complete example by an OpenAI employee.

TheWhiteBox’s take:

Multi-agent frameworks are starting to look like natural evolutions of the status quo. While we have yet to find a genuinely generalizable agent (an AI with huge performance across all tasks), combining task-specific agents through seamless interactions is a no-brainer, and OpenAI’s intentions are unequivocally heading in that direction.

This also gives a clearer idea of the role LLMs will play in the future as a natural language interface between humans and machines. As Swarm shows, humans give instructions in natural language, and agents understand these and autonomously act on them.

At some point in 2025, humans might finally have a simple-to-use product with which they can create dozens of different agents to automate a large part of their daily work.

It’s not AGI, but it’s undoubtedly transformational.

AMAZON

Amazon’s AI Shopping Guides… & Unexpected Coders

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